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Ph.D. Dissertations

Abdulla
Rose
Fertig
Zhou
Mauch
Horowitz
Lueken
Hittinger
Klima
Siler-Evans
Peterson
Gresham
Katzenstein
Pattanariyankool
Samaras
Gilmore
Lima de Azevedo
Chan
Spees
Newcomer
Walawalkar
McCoy
Jaramillo
Hines
Marriott
Morrow
Stolaroff
Echeverri
King
Blumsack
Chen
Bergerson
Vajjhala
DeCarolis
Perekhodtsev
Zerriffi

Exploring the Deployment Potential of Small Modular Reactors, Ahmed Abdulla, 2014
This thesis reports the results of several investigations into the viability of an emergent technology. Due to the lack of data in such cases, and the sensitivity surrounding nuclear power, exploring the potential of small modular reactors (SMRs) proved challenging. Moreover, these reactors come in a wide range of sizes and can employ a number of technologies, which made investigating the category as a whole difficult.
We started by looking at a subset of SMRs that were the most promising candidates for near to mid-term deployment: integral light water SMRs. We conducted a technically detailed elicitation of expert assessments of their capital costs and construction duration, focusing on five reactor deployment scenarios that involved a large reactor and two light water SMRs. Consistent with the uncertainty introduced by past cost overruns and construction delays, median estimates of the cost of new large plants varied by more than a factor of 2.5. Expert judgments about likely SMR costs displayed an even wider range. There was consensus that an SMR plant’s construction duration would be shorter than a large reactor’s. Experts identified more affordable unit cost, factory fabrication, and shorter construction schedules as factors that may make light water SMRs economically viable, though these reactors do not constitute a paradigm shift when it comes to nuclear power’s safety and security.
Using these expert assessments of cost and construction duration, we calculated levelized cost of electricity values for four of the five scenarios. For the large plant, median levelized cost estimates ranged from $56 to $120 per MWh. Median estimates of levelized cost ranged from $77 to $240 per MWh for a 45MWe SMR, and from $65 to $120 per MWh for a 225MWe unit. We concluded that controlling construction duration is important, though not as important a factor in the analysis as capital cost, and, given the price of electricity in some parts of the U.S., it is possible to construct an argument for deploying SMRs in certain locations.
We then decided to investigate the technical and institutional barriers hampering the development and deployment of a subset of six SMRs, including two light water designs and four non-light water advanced designs. We organized an invitational workshop that became an integrated assessment of various designs and of the institutional innovations required to bring SMRs to market.
Some valuable insights were gleaned from the workshop: there is consensus that many of the challenges facing advanced SMRs are rooted in institutional biases in favor of the light water economy, as opposed to technical ones. The institutional factors that are judged to pose the greatest challenge to the mass deployment of SMRs are: the lack of a greenhouse gas control regime; political and financial instability; public concerns about nuclear safety and waste; and inadequate national and international institutions.
When asked what factors most help promote SMR adoption in OECD and developing countries, economic factors dominate the list of characteristics that most contribute to their promotion in OECD countries but, when it comes to developing countries, institutional factors are regarded as being of highest import. Safety of design and safety in operation are judged the most important characteristic on both lists.
Contact:
Ahmed Y. Abdulla
aya1@cmu.edu

 

Assessing the Costs and Risks of Novel Wind Turbine Applications, Stephen Rose, 2013
This thesis addresses the cost-effectiveness of curtailing a wind farm to regulate the electrical grid frequency and the hurricane risk to offshore wind farms in the eastern United States. Additionally, this thesis presents a new method to generate long periods of non-stationary wind speed time series data sampled at high rates by combining measured and simulated data.
Paper 1 calculates the cost of curtailing the power output of a wind farm to provide a reserve of power to regulate the electrical grid frequency, as required by grid operators in several countries with high wind-power penetrations. The simulations in Paper 1 show that it is most efficient to curtail a few turbines deeply rather than curtail all turbines in a wind farm equally. Compared to regulation prices in the Texas (ERCOT) market in 2007-2009, a curtailed wind farm would be cost-competitive with conventional generators less than 1% of the time.
Paper 2 supports the simulations in Paper 1 by developing a method to combine long periods of low-frequency wind speed data with realistic simulated high-frequency turbulence. The combined time series of wind speeds retains the non-stationary characteristics of wind speed, such as diurnal variations, the passing of weather fronts, and seasonal variations, but gives a much higher sampling rate.
Papers 3 and 4 estimate the hurricane risks to current designs of offshore wind turbines in the U.S. Paper 3 develops analytical probability distributions based on historical hurricane records to predict the distribution of damages to a single wind farm in a given location. Paper 4 uses simulated hurricanes with realistic statistical properties to estimate the correlated risks to all the wind farms in a region and estimate the distribution of aggregate losses over different periods. Both papers find hurricane risks are small for current turbine designs in New England and the Mid-Atlantic, but the vi risks in the Gulf of Mexico and the Southeast are significant enough to warrant new, stronger designs. Hurricane risks could be reduced almost an order of magnitude by ensuring that turbines can continue yawing to track the wind direction even if grid power is lost.
Contact:
Stephen Rose
srose@andrew.cmu.edu

 

Facilitating the Development and Integration of Low-Carbon Energy Technologies, Emily Fertig, 2013
Climate change mitigation will require extensive decarbonization of the electricity sector. This thesis addresses both large-scale wind integration (Papers 1 - 3) and development of new energy technologies (Paper 4) in service of this goal.
Compressed air energy storage (CAES) could be paired with a wind farm to provide rm, dispatchable baseload power, or serve as a peaking plant and capture upswings in electricity prices. Paper 1 presents a rm-level engineering-economic analysis of a wind/CAES system with a wind farm in central Texas, load in either Dallas or Houston, and a CAES plant whose location is pro t-optimized. Of a range of market scenarios considered, the CAES plant is found to be pro table only given the existence of large and infrequent price spikes. Social bene ts of wind/CAES include avoided construction of new generation capacity, improved air quality during peak demand, and increased economic surplus, but may not outweigh the private cost of the CAES system nor justify a subsidy.
Like CAES, pumped hydropower storage (PHS) ramps quickly enough to smooth wind power and could pro t from arbitrage on short-term price uctuations exacerbated by large-scale wind. Germany has aggressive plans for wind power expansion, and Paper 2 analyzes an investment opportunity in a PHS facility in Norway that practices arbitrage in the German spot market. Price forecasts given increased wind capacity are used to calculate pro t-maximizing production schedules and annual revenue streams. Real options theory is used to value the investment opportunity, since unlike net present value, it accounts for uncertainty and intertemporal choice. Results show that the optimal investment strategy under the base scenario is to wait approximately eight years then i Abstract ii invest in the largest available plant.
Paper 3 examines long-distance interconnection as an alternate method of wind power smoothing. Frequency-domain analysis indicates that interconnection of aggregate regional wind plants across much of the western and mid-western U.S. would not result in signi cantly greater smoothing than interconnection within a single region. Time-domain analysis shows that interconnection across regions reduces the magnitude of low-probability step changes and doubles rm power output (capacity available at least 92 % of the time) compared with a single region. An approximate cost analysis indicates that despite these bene ts, balancing wind and providing rm power with local natural gas turbines would be more cost-e ective than with transmission interconnection.
Papers 1 and 3 demonstrate the need for further RD&D (research, development, and deployment) of low-carbon energy technologies. Energy technology development is highly uncertain but most often modeled as deterministic, which neglects the ability both to adapt RD&D strategy to changing conditions and to invest in initially high-cost technologies with small breakthrough probabilities. Paper 4 develops an analytical stochastic dynamic programming framework in which RD&D spending decreases the expected value of the stochastic cost of a technology. Results for a two-factor cost model (which separates RD&D into R&D and learning-by-doing) applied to carbon capture and sequestration (CCS) indicate that given 15 years until large-scale deployment, investment in the RD&D program is optimal over a very broad range of initial mitigation costs ($10{$380/tCO2). While the NPV of the program is zero if initial mitigation cost is $100/tCO2, under uncertainty the program is worth about $7 billion. If initial mitigation cost is high, the program is worth most if cost reductions exogenous to the program (e.g. due to private sector activity) are also high. Factors that promote R&D spending over learning-by-doing include more imminent deployment, high initial cost, lower exogenous cost reductions, and lower program funds available.
Contact:
Emily Fertig
emily.fertig@gmail.com

Managing Wind-based Electricity Generation and Storage, Helen Zhou, 2012
Among the many issues that profoundly affect the world economy every day, energy is one of the most prominent. Countries such as the U.S. strive to reduce reliance on the import of fossil fuels, and to meet increasing electricity demand without harming the environment.
Two of the most promising solutions for the energy issue are to rely on renewable energy, and to develop efficient electricity storage. Renewable energy—such as wind energy and solar energy—is free, abundant, and most importantly, does not exacerbate the global warming problem. However, most renewable energy is inherently intermittent and variable, and thus can benefit greatly from coupling with electricity storage, such as grid-level industrial batteries. Grid storage can also help match the supply and demand of an entire electricity market. In addition, electricity storage such as car batteries can help reduce dependence on oil, as it can enable the development of Plug-in Hybrid Electric Vehicles, and Battery Electric Vehicles. This thesis focuses on understanding how to manage renewable energy and electricity storage properly together, and electricity storage alone.
In Chapter 2, I study how to manage renewable energy, specifically wind energy. Managing wind energy is conceptually straightforward: generate and sell as much electricity as possible when prices are positive, and do nothing otherwise. However, this leads to curtailment when wind energy exceeds the transmission capacity, and possible revenue dilution when current prices are low but are expected to increase in the future. Electricity storage is being considered as a means to alleviate these problems, and also enables buying electricity from the market for later resale. But the presence of storage complicates the management of electricity generation from wind, and the value of storage for a wind-based generator is not entirely understood.
I demonstrate that for such a combined generation and storage system the optimal policy does not have any apparent structure, and that using overly simple policies can be considerably suboptimal. I thus develop and analyze a triple-threshold policy that I show to be nearoptimal. Using a financial engineering price model and calibrating it to data from the New York Independent System Operator, I show that storage can substantially increase the monetary value of a wind farm: If transmission capacity is tight, the majority of this value arises from reducing curtailment and time-shifting generation; if transmission capacity is abundant this value stems primarily from time-shifting generation and arbitrage. In addition, I find that while more storage capacity always increases the average energy sold to the market, it may actually decrease the average wind energy sold when transmission capacity is abundant.
In Chapter 3, I examine how electricity storage can be used to help match electricity supply and demand. Conventional wisdom suggests that when supply exceeds demand, any electricity surpluses should be stored for future resale. However, because electricity prices can be negative, another potential strategy of dealing with surpluses is to destroy them. Using real data, I find that for a merchant who trades electricity in a market, the strategy of destroying surpluses is potentially more valuable than the conventional strategy of storing surpluses.
In Chapter 4, I study how the operation and valuation of electricity storage facilities can be affected by their physical characteristics and operating dynamics. Examples are the degradation of energy capacity over time and the variation of round-trip efficiency at different charging/discharging rates. These dynamics are often ignored in the literature, thus it has not been established whether it is important to model these characteristics. Specifically, it remains an open question whether modeling these dynamics might materially change the prescribed operating policy and the resulting valuation of a storage facility. I answer this question using a representative setting, in which a battery is utilized to trade electricity in an energy arbitrage market.
Using engineering models, I capture energy capacity degradation and efficiency variation explicitly, evaluating three types of batteries: lead acid, lithium-ion, and Aqueous Hybrid Ion— a new commercial battery technology. I calibrate the model for each battery to manufacturers’ data and value these batteries using the same calibrated financial engineering price model as in Chapter 2. My analysis shows that: (a) it is quite suboptimal to operate each battery as if it did not degrade, particularly for lead acid and lithium-ion; (b) reducing degradation and efficiency variation have a complimentary effect: the value of reducing both together is greater than the sum of the value of reducing one individually; and (c) decreasing degradation may have a bigger effect than decreasing efficiency variation.
Contact:
Helen Zhou Yangfang
Assistant Professor of Operations Management
Lee Kong Chian School of Business, Singapore Management University
helenzhou@smu.edu.sg

 

Managing Wind Power Forecast Uncertainty in Electric Grids, Brandon Mauch, 2012
Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter 2 presents a model of a wind farm with compressed air energy storage (CAES) participating freely in the day-ahead electricity market without the benefit of a renewable portfolio standard or production tax credit. CAES is used to reduce the risk of committing uncertain quantities of wind energy and to shift dispatch of wind generation to high price periods. Using wind forecast data and market prices from 2006 – 2009, we find that the annual income for the modeled wind-CAES system would not cover annualized capital costs. We also estimate market prices with a carbon price of $20 and $50 per tonne CO2 and find that the revenue would still not cover the capital costs. The implied cost per tonne of avoided CO2 to make a wind-CAES profitable from trading on the day-ahead market is roughly $100, with large variability due to electric power prices.
Wind power forecast errors for aggregated wind farms are often modeled with Gaussian distributions. However, data from several studies have shown this to be inaccurate. Further, the distribution of wind power forecast errors largely depends on the wind power forecast value. The few papers that account for this dependence bin the wind forecast data and fit parametric distributions to the actual wind power in each bin. A method to model wind power forecast uncertainty as a single closed-form solution using a logit transformation of historical wind power forecast and actual wind power data is presented in Chapter 3. Once transformed, the data become close to jointly normally distributed. We show the process of calculating confidence intervals for wind power forecast errors using the jointly normally distributed logit transformed data. This method has the advantage of fitting the entire dataset with five parameters while also providing the ability to make calculations conditioned on the value of the wind power forecast.
The model present in Chapter 3 is applied in Chapter 4 to calculate increases in net load uncertainty introduced from day-ahead wind power forecasts. Our analyses uses data from two different electric grids in the U.S. having similar levels of installed wind capacity with large differences in wind and load forecast accuracy due to geographic characteristics. A probabilistic method to calculate the dispatchable generation capacity required to balance day-ahead wind and load forecast errors for a given level of reliability is presented. Using empirical data we show that the capacity requirements for 95% day-ahead reliability range from 2100 MW to 5600 MW for ERCOT and 1900 MW to 4500 MW for MISO, depending on the amount of wind and load forecast for the next day. We briefly discuss the additional requirements for higher reliability levels and the effect of correlated wind and load forecast errors. Additionally, we show that each MW of additional wind power capacity in ERCOT must be matched by a 0.30 MW day-ahead dispatchable generation capacity to cover 95% of day-ahead uncertainty. Due to the lower wind forecast uncertainty in MISO, the value drops to 0.13 MW of dispatchable capacity for each MW of additional wind capacity.
Direct load control (DLC) has received a lot of attention lately as an enabler of wind power. One major benefit of DLC is the added flexibility it brings to the grid. Utilities in some parts of the U.S. can bid the load reduction from DLC into energy markets. Forecasts of the resource available for DLC assist in determining load reduction quantities to offer. In Chapter 5, we present a censored regression model to forecast load from residential air conditioners using historical load data, hour of the day, and ambient temperature. We tested the forecast model with hourly data from 467 air conditioners located in three different utilities. We used two months of data to train the model and then ran day-ahead forecasts over a six week period. Mean square errors ranged from 4% to 8% of mean air conditioner load. This method produced accurate forecasts with much lower data requirements than physics based forecast models.
Contact:
Brandon Mauch
Utility Regulation Engineer
Iowa Utilities Board
1375 E. Court Ave.
Des Moines, IA 50319
brandon.mauch@iub.iowa.gov

 

Topics in Residential Electric Demand Response, Shira R. Horowitz, 2012
Demand response and dynamic pricing are touted as ways to empower consumers, save consumers money, and capitalize on the "smart grid" and expensive advanced meter infrastructure. In this work, I attempt to show that demand response and dynamic pricing are more nuanced. Dynamic pricing is very appealing in theory but the reality of it is less clear. Customers do not always respond to prices. Price differentials are not always large enough for customers to save money. Quantifying energy that was not used is difficult.
In chapter 2, I go into more detail on the potential benefits of demand response. I include a literature review of residential dynamic pilots and tariffs to see if there is evidence that consumers respond to dynamic rates, and assess the conditions that lead to a response.
Chapter 3 explores equity issues with dynamic pricing. Flat rates have an inherent cross-subsidy built in because more peaky customers (who use proportionally more power when marginal price is high) and less peaky customers pay the same rates, regardless of the cost they impose on the system. A switch to dynamic pricing would remove this cross subsidy and have a significant distributional impact. I analyze this distributional impact under different levels of elasticity and capacity savings.
Chapter 4 is an econometric analysis of the Commonwealth Edison RTP tariff. I show that it is extremely difficult to find the small signal of consumer response to price in all of the noise of everyday residential electricity usage.
Chapter 5 looks at methods for forecasting, measuring, and verifying demand response in direct load control of air-conditioners. Forecasting is important for system planning. Measurement and verification are necessary to ensure that payments are fair. I have developed a new, censored regression based model for forecasting the available direct load control resource. This forecast can be used for measurement and verification to determine AC load in the counterfactual where DLC is not applied. This method is more accurate than the typical moving averages used by most ISO's, and is simple, easy, and cheap to implement.
Contact:
Shira Horowitz
PJM Interconnection, Inc.
horows@pjm.com

 

Integrating Variable Renewables into the Electric Grid: An Evaluation of Challenges and Potential Solutions, Colleen A. Lueken, 2012
Renewable energy poses a challenge to electricity grid operators due to its variability and intermittency. In this thesis I quantify the cost of variability of different renewable energy technologies and then explore the use of reconfigurable distribution grids and pumped hydro electricity storage to integrate renewable energy into the electricity grid.
Cost of Variability
I calculate the cost of variability of solar thermal, solar photovoltaic, and wind by summing the costs of ancillary services and the energy required to compensate for variability and intermittency. I also calculate the cost of variability per unit of displaced CO2 emissions. The costs of variability are dependent on technology type. Variability cost for solar PV is $8-11/MWh, for solar thermal it is $5/MWh, and for wind it is around $4/MWh. Variability adds ~$15/tonne CO2 to the cost of abatement for solar thermal power, $25 for wind, and $33-$40 for PV.
Distribution Grid Reconfiguration
A reconfigurable network can change its topology by opening and closing switches on power lines. I show that reconfiguration allows a grid operator to reduce operational losses as well as accept more intermittent renewable generation than a static configuration can. Net present value analysis of automated switch technology shows that the return on investment is negative for this test network when considering loss reduction, but that the return is positive under certain conditions when reconfiguration is used to minimize curtailment of a renewable energy resource.
Pumped Hydro Storage in Portugal
Portugal is planning to build five new pumped hydro storage facilities to balance its growing wind capacity. I calculate the arbitrage potential of the storage capacity from the perspective of an independent storage owner, a thermal fleet owner, and a consumer-oriented storage owner. This research quantifies the effect storage ownership has on CO2 emissions, consumer electricity expenditure, and thermal generator profits. I find that in the Portuguese electricity market, an independent storage owner could not recoup its investment in storage using arbitrage only, but a thermal fleet owner or consumer-oriented owner may get a positive return on investment.
Contact:
Colleen Lueken
cahorin@gmail.com

 

Energy Storage on the Grid and the Short-term Variability of Wind, Eric Hittinger, 2012
Wind generation presents variability on every time scale, which must be accommodated by the electric grid. Limited quantities of wind power can be successfully integrated by the current generation and demand-side response mix but, as deployment of variable resources increases, the resulting variability becomes increasingly difficult and costly to mitigate. In Chapter 2, we model a co-located power generation/energy storage block composed of wind generation, a gas turbine, and fast-ramping energy storage. A scenario analysis identifies system configurations that can generate power with 30% of energy from wind, a variability of less than 0.5% of the desired power level, and an average cost around $70/MWh.
While energy storage technologies have existed for decades, fast-ramping grid-level storage is still an immature industry and is experiencing relatively rapid improvements in performance and cost across a variety of technologies. Decreased capital cost, increased power capability, and increased efficiency all would improve the value of an energy storage technology and each has cost implications that vary by application, but there has not yet been an investigation of the marginal rate of technical substitution between storage properties. The analysis in chapter 3 uses engineering-economic models of four emerging fast-ramping energy storage technologies to determine which storage properties have the greatest effect on cost-ofservice. We find that capital cost of storage is consistently important, and identify applications for which power/energy limitations are important.
In some systems with a large amount of wind power, the costs of wind integration have become significant and market rules have been slowly changing in order to internalize or control the variability of wind generation. Chapter 4 examines several potential market strategies for mitigating the effects of wind variability and estimate the effect that each strategy would have on the operation and profitability of wind farms. We find that market scenarios using existing v price signals to motivate wind to reduce variability allow wind generators to participate in variability reduction when the market conditions are favorable, and can reduce short-term (30- minute) fluctuations while having little effect on wind farm revenue.
Contact:
Eric Hittinger
Assistant Professor of Public Policy
Rochester Institute of Technology
Office: Eastman 1-1313
92 Lomb Memorial Drive
Rochester, NY 14623-5604
eshgpt@rit.edu

 

Does Tropical Cyclone Modification Make Sense? A Decision Analytic Perspective, Kelly Klima, 2012
Recent dramatic increases in damages caused by tropical cyclones (TCs) and improved understanding of TC physics have led the Department of Homeland Security to fund research on intentional hurricane modification. Here I present a decision analytic assessment of whether hurricane modification is potentially cost effective in South Florida.
First, for a single storm I compare hardening buildings to lowering the wind speed of a TC by reducing sea surface temperatures with wind-wave pumps. I find that if it were feasible and properly implemented, modification could reduce net wind losses from an intense storm more than hardening structures. However, hardening provides "fail safe" protection for average storms that might not be achieved if the only option were modification. The effect of natural variability is larger than that of either strategy.
Second, for multiple storms over a given return period, I investigate TC wind and storm surge damage reduction by hardening buildings and by wind-wave pumps. The coastal areas examined experience more surge damages for short return periods, and more wind damages for long periods. Surge damages are best reduced through a surge barrier. Wind damages are best reduced by a portfolio of techniques including wind-wave pumps, assuming they work and are correctly deployed. Damages in areas outside of the floodplain will likely be dominated by wind damages, and hence a similar portfolio will likely be best in these areas.
Since hurricane modification might become a feasible strategy for reducing hurricane damages, to facilitate an informed and constructive discourse on implementation, policy makers need to understand how people perceive hurricane modification. Therefore using the mental models approach, I identified Florida residents’ perceptions of hurricane modification techniques. First, hurricane modification was perceived as a relatively ineffective strategy for vi damage reduction. Second, hurricane modification was expected to lead to changes in path, but not necessarily strength. Third, reported anger at hurricane modification was weaker when path was unaltered and the damages equal to or less than projected. Fourth, individuals who recognized the uncertainty inherent in hurricane prediction reported more anger at scientists across modification scenarios.
Contact:
Kelly Klima
Climate Adaptation Policy Advisor
Center for Clean Air Policy
750 First Street NE
Washington, D.C. 20002
kklima@ccap.org

 

Evaluating Interventions in the U.S. Electricity System: Assessments of Energy Efficiency, Renewable Energy, and Small-Scale Cogeneration, Kyle Siler-Evans, 2012
There is growing interest in reducing the environmental and human-health impacts resulting from electricity generation. Renewable energy, energy efficiency, and energy conservation are all commonly suggested solutions. Such interventions may provide health and environmental benefits by displacing emissions from conventional power plants. However, the generation mix varies considerably from region to region and emissions vary by the type and age of a generator. Thus, the benefits of an intervention will depend on the specific generators that are displaced, which vary depending on the timing and location of the intervention.
Marginal emissions factors (MEFs) give a consistent measure of the avoided emissions per megawatt-hour of displaced electricity, which can be used to evaluate the change in emissions resulting from a variety of interventions. This thesis presents the first systematic calculation of MEFs for the U.S. electricity system. Using regressions of hourly generation and emissions data from 2006 through 2011, I estimate regional MEFs for CO2, NOx, and SO2, as well as the share of marginal generation from coal-, gas-, and oil-fired generators. This work highlights significant regional differences in the emissions benefits of displacing a unit of electricity: compared to the West, displacing one megawatt-hour of electricity in the Midwest is expected to avoid roughly 70% more CO2, 12 times more SO2, and 3 times more NOx emissions.
I go on to explore regional variations in the performance of wind turbines and solar panels, where performance is measured relative to three objectives: energy production, avoided CO2 emissions, and avoided health and environmental iii damages from criteria pollutants. For 22 regions of the United States, I use regressions of historic emissions and generation data to estimate marginal impact factors, a measure of the avoided health and environmental damages per megawatthour of displaced electricity. Marginal impact factors are used to evaluate the effects of an additional wind turbine or solar panel in the U.S. electricity system. I find that the most attractive sites for renewables depend strongly on one’s objective. A solar panel in Iowa displaces 20% more CO2 emissions than a panel in Arizona, though energy production from the Iowa panel is 25% less. Similarly, despite a modest wind resource, a wind turbine in West Virginia is expected to displace 7 times more health and environmental damages than a wind turbine in Oklahoma.
Finally, I shift focus and explore the economics of small-scale cogeneration, which has long been recognized as a more efficient alternative to central-station power. Although the benefits of distributed cogeneration are widely cited, adoption has been slow in the U.S. Adoption could be encouraged by making cogeneration more economically attractive, either by increasing the expected returns or decreasing the risks of such investments. I present a case study of a 300-kilowatt cogeneration unit and evaluate the expected returns from: demand response, capacity markets, regulation markets, accelerated depreciation, a price on CO2 emissions, and net metering. In addition, I explore the effectiveness of feed-in tariffs at mitigating the energy-price risks to cogeneration projects.
Contact:
Kyle Siler-Evans
Carnegie Mellon University
ksilerevans@gmail.com

 

Plug-In Hybrid Electric Vehicles: Battery Degradation, Grid Support, Emissions, and Battery Size Tradeoffs, Scott B. Peterson, 2012
Plug-in hybrid electric vehicles (PHEVs) may become a substantial part of the transportation fleet on time scales of a decade or two. This dissertation investigates battery degradation, and how the introduction of PHEVs may influence the electricity grid, emissions, and petroleum use in the US. It examines the effects of combined driving and vehicle-to-grid (V2G) usage on the lifetime performance of relevant commercial Li-ion cells. The loss of battery capacity was quantified as a function of driving days as well as a function of integrated capacity and energy processed by the cells. The cells tested showed promising capacity fade performance: more than 95% of the original cell capacity remains after thousands of driving days worth of use. Statistical analyses indicate that rapid vehicle motive cycling degraded the cells more than slower, V2G galvanostatic cycling. These data are used to examine the potential economic implications of using vehicle batteries to store grid electricity generated at off-peak hours for off-vehicle use during peak hours. The maximum annual profit with perfect market information and no battery degradation cost ranged from ~US$140 to $250 in the three cities. If the measured battery degradation is applied, however, the maximum annual profit decreases to ~$10–120. The dissertation details the increase in electric grid load and emissions due to vehicle battery charging in PJM and NYISO with the current generation mix, the current mix with a $50/tonne CO2 price, and this case but with existing coal generators retrofitted with 80% CO2 capture. It also models emissions using natural gas or wind+gas. PHEV fleet percentages between 0.4 and 50% are examined. When compared to 2020 CAFE standards, net CO2 emissions in New York are reduced by switching from gasoline to electricity; coal-heavy PJM shows somewhat smaller benefits unless coal units are fitted with CCS or replaced with lower CO2 generation. NOX is reduced in both RTOs, but there is upward pressure on SO2 emissions or allowance prices under a cap. Finally the dissertation compares increasing the all-electric range (AER) of PHEVs to installing charging infrastructure. Fuel use was modeled using the National Household Travel Survey and Greenhouse Gasses, Regulated Emissions, and Energy Use in Transportation model. It was found that increasing AER of plug-in hybrids was a more cost effective solution to reducing gasoline consumption than installing charging infrastructure. Comparison of results to current subsidy structure shows various options to improve future PHEV or other vehicle subsidy programs.
Contact:
Scott Peterson
Carnegie Mellon University
sxotty@gmail.com

 

Geologic CO2 Sequestration and Subsurface Property Rights: A Legal and Economic Analysis, Robert Lee Gresham, 2010
Carbon dioxide emissions (CO2) from the combustion of fossil fuels must be reduced on a large scale to mitigate the effects of global climate change. Carbon capture and sequestration
(CCS) has the potential to allow the continued use of fossil fuels with little or no emissions until alternative, low-to-zero emission sources of energy are more widely deployed. This thesis considers the legal and economic implications of securing the right to use geologic pore space-the microscopic space in subsurface rock matrixes-in an effort to sequester
CO2 deep underground to mitigate climate change. The findings and conclusions drawn in this thesis are intended to help guide discussion, research, and decision-making processes undertaken by policymakers and industry leaders with respect to the commercial-scale deployment of CCS. Prior to the commencement of sequestration, a project developer/operator must have authorization to access and use pore space to avoid liability for subsurface trespass. This authorization can be acquired via bilateral contract, where monetary compensation is remitted to the property owner in exchange for the right to use pore space.
However, the question remains open as to whether the use of pore space for geologic CO2 sequestration (GCS) is a trespass requiring compensation under the law. In fact, there is ample legal precedent in the context of underground injection activities such as enhanced hydrocarbon recovery, fluid waste disposal, and freshwater storage to support the supposition that the invasion of pore space by injected is compensable only when substantial harm or interference with an existing or non-speculative, investment-backed future use of the subsurface results from the injection of such fluids. This thesis shows that if CCS is widely deployed, the cost of electricity and power plant profitability could be adversely affected by a legal requirement that pore space owners must be compensated for GCS in all circumstances.
Moreover, absent unrealistically high electricity prices or some form of sequestration subsidy, pore space has no net-positive, intrinsic economic value to electric generators that can be passed along to property owners. Therefore, while paying property owners to use of pore space for geologic CO2 sequestration may very well foster public acceptance and appease staunch private property rights advocates, there is no demonstrable legal or economic rationale for compensating property owners who have no current or nonspeculative, investment-backed future use of the subsurface where pore space targeted for sequestration is located. A pragmatic and equitable solution for constraining the potential negative economic effects associated with acquiring pore space rights would be for state or federal legislatures, or courts, to limit required compensation to only those instances where the injection and migration of CO2 materially impairs current or non-speculative, investment backed future uses of the subsurface. Future work should include a detailed analysis of takings law and the anticipated long-term constitutional and economic implications of various approaches to pore space property rights governance before new CCS-specific laws are enacted. The models presented in this thesis should also be applied to additional site specific geologic data for saline aquifer sequestration targets. Additionally, the implications of GCS paired with enhanced oil recovery (EOR) on power plant economics should be studied.
Contact
Robert Lee Gresham
rgresham@andrew.cmu.edu
(412) 953-4617

 

Wind Power Variability, Its Cost, and Effect on Power Plant Emissions, Warren Katzenstein, 2010
The recent growth in wind power is transforming the operation of electricity systems by introducing variability into utilities’ generator assets. System operators are not experienced in utilizing significant sources of variable power to meet their loads and have struggled at times to keep their systems stable. As a result, system operators are learning in real-time how to incorporate wind power and its variability. This thesis is meant to help system operators have a better understanding of wind power variability and its implications for their electricity system.
Characterizing Wind Power Variability
We present the first frequency-dependent analyses of the geographic smoothing of wind power's variability, analyzing the interconnected measured output of 20 wind plants in Texas. Reductions in variability occur at frequencies corresponding to times shorter than ~24 hours and are quantified by measuring the departure from a Kolmogorov spectrum. At a frequency of 2.8x10-4 Hz (corresponding to 1 hour), an 87% reduction of the variability of a single wind plant is obtained by interconnecting 4 wind plants. Interconnecting the remaining 16 wind plants produces only an additional 8% reduction. We use step-change analyses and correlation coefficients to compare our results with previous studies, finding that wind power ramps up faster than it ramps down for each of the step change intervals analyzed and that correlation between the power output of wind plants 200 km away is half that of co-located wind plants. To examine variability at very low frequencies, we estimate yearly wind energy production in the Great Plains region of the United States from automated wind observations at airports covering 36 years. The estimated wind power has significant inter-annual variability and the severity of wind drought years is estimated to be about half that observed nationally for hydroelectric power.
Estimating the Cost of Wind Power Variability
We develop a metric to quantify the sub-hourly variability cost of individual wind plants and show its use in valuing reductions in wind power variability. Our method partitions wind energy into hourly and sub-hourly components and uses corresponding market prices to determine the cost of variability. The metric is applicable to variability at all time scales faster than hourly, and can be applied to long-period forecast errors. We use publically available data at 15 minute time resolution to apply the method to ERCOT, the largest wind power production region in the United States. The range of variability costs arising from 15 minute to 1 hour variations (termed load following) for 20 wind plants in ERCOT was $6.79 to 11.5 per MWh (mean of $8.73 ±$1.26 per MWh) in 2008 and $3.16 to 5.12 per MWh (mean of $3.90 ±$0.52 per MWh) in 2009. Load following variability costs decrease as wind plant capacity factors increase, indicating wind plants sited in locations with good wind resources cost a system less to integrate. Twenty interconnected wind plants have a variability cost of $4.35 per MWh in 2008. The marginal benefit of interconnecting another wind plant diminishes
rapidly: it is less than $3.43 per MWh for systems with 2 wind plants already interconnected, less than $0.7 per MWh for 4-7 wind plants, and less than $0.2 per MWh for 8 or more wind plants. This method can be used to value the installation of storage and other techniques to mitigate wind variability.
Estimating How Wind Power Variability Affects Power Plant Emissions
Renewables portfolio standards (RPS) encourage large scale deployment of wind and solar electric power, whose power output varies rapidly even when several sites are added together. In many locations, natural gas generators are the lowest cost resource available to compensate for this variability, and must ramp up and down quickly to keep the grid stable, affecting their emissions of NOx and CO2. We model a wind or solar photovoltaic plus gas system using measured 1-minute time resolved emissions and heat rate data from two types of natural gas generators, and power data from four wind plants and one solar plant. Over a wide range of renewable penetration, we find CO2 emissions achieve ~80% of the emissions reductions expected if the power fluctuations caused no additional emissions. Pairing multiple turbines with a wind plant achieves ~77 to 95% of the emissions reductions expected. Using steam
injection, gas generators achieve only 30-50% of expected NOx emissions reductions, and with dry control NOx emissions increase substantially. We quantify the interaction between state RPSs and constraints such as the NOx Clean Air Interstate Rule (CAIR), finding that states with substantial RPSs could see upward pressure on CAIR NOx permit prices, if the gas turbines we modeled are representative of the plants used to mitigate wind and solar power variability.
Contact:
Warren Katzenstein
Associate
The Brattle Group
44 Brattle Street
Cambridge, MA 02138
wkatzenstein@gmail.com


 

Essays on Power Systems Economics, Sompop Pattanariyankool, 2010
We explore the optimal size of the transmission line from distant wind farms, modeling the tradeoff between transmission cost and benefit from delivered wind power.
We also examine the benefit of connecting a second wind farm, requiring additional transmission, in order to increase output smoothness. Since a wind farm has a low capacity factor, the transmission line would not be heavily loaded, on average; depending on the time profile of generation, for wind farms with capacity factor of 29-34%, profit is maximized for a line that is about ¾ of the nameplate capacity of the wind farm.
Although wind generation is inexpensive at a good site, transmitting wind power over 1,000 miles (about the distance from Wyoming to Los Angeles) doubles the delivered cost of power. As the price for power rises, the optimal capacity of transmission increases. Connecting wind farms lowers delivered cost when the wind farms are close, despite the high correlation of output over time. Imposing a penalty for failing to deliver minimum contracted supply leads to connecting more distant wind farms.
Chapter 2: The optimal baseload generation portfolio under CO2 regulation and fuel price uncertainties We solve for the power generation portfolio that minimizes cost and variability among existing and near-term baseload technologies under scenarios that vary the carbon tax, fuel prices, capital cost and CO2 capture cost. The variability of fuel prices and uncertainty of CO2 regulation favor technologies with low variable cost and low CO2 emission. The qualitative results are expected; stringent CO2 regulation cost leads to more technology with little carbon emissions, such as nuclear and IGCC CCS, while penalizing coal. However, the variability of fuel prices and the correlation among fuel prices are the principal attributes shaping the optimal portfolio mix. We also model a Bayesian approach that allows the planner to express his belief on the future cost of power generation technology.
Contact:
Sompop Pattanariyankool
Ministry of Energy, Thailand
sompop.pattana@gmail.com

 

A Life Cycle Approach to Technology, Infrastructure, and Climate Policy Decision Making: Transitioning to Plug-in Hybrid Electric Vehicles and Low-Carbon Electricity, Costa Samaras, 2009
In order to mitigate the most severe effects of climate change, large global reductions in the current levels of anthropogenic greenhouse gas (GHG) emissions are required in this century to stabilize atmospheric carbon dioxide (CO2) concentrations at less than double pre-industrial levels. The Intergovernmental Panel on Climate Change (IPCC) fourth assessment report states that GHG emissions should be reduced to 50-80% of 2000 levels by 2050 to increase the likelihood of stabilizing atmospheric CO2 concentrations. In order to achieve the large GHG reductions by 2050 recommended by the IPCC, a fundamental shift and evolution will be required in the energy system. Because the electric power and transportation sectors represent the largest GHG emissions sources in the United States, a unique opportunity for coupling these systems via electrified transportation could achieve synergistic environmental (GHG emissions reductions) and energy security (petroleum displacement) benefits. Plug-in hybrid electric vehicles (PHEVs), which use electricity from the grid to power a portion of travel, could play a major role in reducing greenhouse gas emissions from the transport sector.
However, this thesis finds that life cycle GHG emissions from PHEVs depend on the electricity source that is used to charge the battery, so meaningful GHG emissions reductions with PHEVs are conditional on low-carbon electricity sources. Power plants and their associated GHGs are long-lived, and this work argues that decisions made regarding new electricity supplies within the next ten years will affect the potential of PHEVs to play a role in a low-carbon future in the coming decades. This thesis investigates the life cycle engineering, economic, and policy decisions involved in transitioning to PHEVs and low-carbon electricity.
The government has a vast array of policy options to promote low-carbon technologies, some of which have proven to be more successful than others. This thesis uses life cycle assessment to evaluate options and opportunities for large GHG reductions from plug-in hybrids. After the options and uncertainties are framed, engineering economic analysis is used to evaluate the policy actions required for adoption of PHEVs at scale and the implications for low-carbon electricity investments. A logistic PHEV adoption model is constructed to parameterize implications for low-carbon electricity infrastructure investments and climate policy. This thesis concludes with an examination of what lessons can be learned for climate, innovation, and low-carbon energy policies from the evolution of wind power from an emerging alternative energy technology to a utilityscale power source. Policies to promote PHEVs and other emerging energy technologies can take lessons learned from the successes and challenges of wind power’s development to optimize low-carbon energy policy and R&D programs going forward.
The need for integrated climate policy, energy policy, sustainability, and urban mobility solutions will accelerate in the next two decades as concerns regarding GHG emissions and petroleum resources continue to be environmental and economic priorities. To assist in informing the discussions on climate policy and low-carbon energy R&D, this research and its methods will provide stakeholders in government and industry with plug-in hybrid and energy policy choices based on life cycle assessment, engineering economics, and systems analysis.
Contact:
Dr. Costa Samaras
RAND Corporation
4750 Fifth Avenue, Suite 600
Pittsburgh, PA 15213
tel: 412.683.2300 x4666
csamaras@rand.org

Integrating Comprehensive Air Quality Modeling with Policy Analysis: Applications for Distributed Electricity Generation, Elisabeth Gilmore, 2009
Small scale and located close to the point of demand, distributed electricity generation (DG) could reduce the cost of electricity, improve grid reliability and support renewable technologies. These facilities also shift the magnitude, timing and location of air quality emissions. The costs from adverse human health effects caused by changes in air quality may outweigh any benefits. In this work, I evaluate the air quality, human health effects and costs for two DG applications. I transform the emissions into ambient concentrations using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx), and dispersion plumes. I then translate the concentrations into health effects with concentration-response functions. Finally, I express the health effects as a social cost reflecting the “willingness to pay” to avoid these effects.
First, I investigate using installed backup generators instead of a more expensive peaking turbine for meeting peak electricity demand. Many of generators are uncontrolled diesel engines which have a high social cost. Adding a diesel particulate filter with exhaust gas recirculation to reduce fine particulate matter and nitrogen oxides can mitigate these costs. This result holds in four urban centers over a range of specified health endpoints and when accounting of uncertainty in the representation of the formation of secondary PM2.5 in PMCAMx. I conclude that properly controlled generators can be employed for meeting peak electricity demand without substantial harm to human health.
Second, I evaluate the changes in the net and distribution of social cost from integrating a utility-scale battery into the New York State electricity grid. Located in New York City, the battery would discharge when electricity prices are high and charge with cheaper generation during off peak hours. For most types of charging plants, I calculate a net social benefit from displacing dirtier fuel oil peaking plants, but a net social cost from displacing natural gas peaking plants. In the short term, the upstate population experiences a social cost from the charging plant. In the long term, however, the battery may support renewable generation such as night time wind power resulting in benefits locally and statewide.
Contact
Dr. Elisabeth Gilmore
eagilmor@andrew.cmu.edu

 

Energy Efficiency in the U.S. Residential Sector: An Engineering and Economic Assessment of Opportunities for Large Energy Savings and Greenhouse Gas Emissions Reductions, Inês Margarida Lima de Azevedo, 2009
Addressing the issue of climate change mitigation will be one of the most daunting tasks of our generation. A large set of strategies for carbon mitigation are needed on a global scale to reduce greenhouse gas (GHG) emissions by 80% below 1990 levels by 2050, in order to avoid global irreversible consequences of climate change. In light of possible near-term GHG regulations, the US Government is now paying more attention to various options for carbon mitigation. Energy efficiency and conservation is a very promising part of a portfolio of strategies. Today, US residential buildings sector account for nearly 17% of US GHG emissions and several new technologies and energy efficiency measures offer potential for large energy savings. While energy efficiency options are currently being deployed or considered as a means of reducing carbon emissions, there is still large uncertainty about the effect of such measures on overall carbon savings.
The first part of this thesis provides an assessment, at the national level, of the energy efficiency potential in the residential sector. I estimate the 2009 energy efficiency potential for the residential sector and its costs under several different scenarios. These include assuming that consumers bear the costs of new technologies, assuming that utilities are incentivized to promote energy efficiency, and estimating the societal costs and benefits of energy efficiency.
Throughout this work, I build the argument that energy efficiency policies cannot consider efficiency gains in energy, electricity or carbon dioxide alone. Instead, the effects of each of these three indicators should be considered in energy efficiency assessments.
I conclude that there is a large potential for energy efficiency in the U.S. residential sector, but large investments are needed realize this potential, since consumers are unlikely to voluntary adopt the most efficient end-use devices.
The second part of this thesis deals with a detailed assessment of the potential for whitelight LEDs for energy and carbon dioxide savings in the U.S. commercial and residential sectors. Lighting constitutes more than 20% of total U.S. electricity consumption, a similar fraction in the E.U., and an even a larger fraction in many developing countries.
Because many current lighting technologies are highly inefficient, improved technologies for lighting hold great potential for energy savings and for reducing associated greenhouse gas emissions. Solid-state lighting shows great promise as a source of efficient, affordable, color-balanced white light.
Indeed, assuming market discount rates, engineering-economic analysis demonstrates that white solid-state lighting already has a lower levelized annual cost (LAC) than incandescent bulbs. The LAC for white solid-state lighting will be lower than that of the most efficient fluorescent bulbs by the end of this decade. However, a large literature indicates that households do not make their decisions in terms of simple expected economic value.
After a review of the technology, I compare the electricity consumption, carbon emissions and cost-effectiveness of current lighting technologies, accounting for expected performance evolution through 2015. I then simulate the lighting electricity consumption and implicit greenhouse gases emissions for the U.S. residential and commercial sectors through 2015 under different policy scenarios: voluntary solid-state lighting adoption, implementation of lighting standards in new construction and rebate programs or equivalent subsidies. Finally, I provide a measure of cost-effectiveness for solid-state lighting in the context of other climate change abatement policies.
Contact:
Inês Margarida Lima de Azevedo
iazevedo@cmu.edu

Coal Supply and Cost Under Technological and Environmental Uncertainty, Melissa Chan, 2009
This thesis estimates available coal resources, recoverability, mining costs, environmental impacts, and environmental control costs for the United States under technological and environmental uncertainty. It argues for a comprehensive, well-planned research program that will resolve resource uncertainty, and innovate new technologies to improve recovery and environmental performance. A stochastic process and cost (constant 2005$) model for longwall, continuous, and surface mines based on current technology and mining practice data was constructed. It estimates production and cost ranges within 5 – 11 percent of 2006 prices and production rates. The model was applied to the National Coal Resource Assessment. Assuming the cheapest mining method is chosen to extract coal, 250 – 320 billion tons are recoverable. Two-thirds to all coal resource can be mined at a cost less than $4/mmBTU. If U.S. coal demand substantially increases, as projected by alternate Energy Information Administration (EIA), resources might not last more than 100 years. By scheduling cost to meet EIA projected demand, estimated cost uncertainty increases over time. It costs less than $15/ton to mine in the first 10 years of a 100 year time period, $10-$30/ton in the following 50 years, and $15-$90/ton thereafter.
Environmental impacts assessed are subsidence from underground mines, surface mine pit area, erosion, acid mine drainage, air pollutant and methane emissions. The analysis reveals that environmental impacts are significant and increasing as coal demand increases. Control technologies recommended to reduce these impacts are backfilling underground mines, surface pit reclamation, substitution of robotic underground mining systems for surface pit mining, soil replacement for erosion, placing barriers between exposed coal and the elements to avoid acid formation, and coalbed methane development to avoid methane emissions during mining. The costs to apply these technologies to meet more stringent environmental regulation scenarios are estimated. The results show that the cost of meeting these regulatory scenarios could increase mining costs two to six times the business as usual cost, which could significantly affect the cost of coal-powered electricity generation.
This thesis provides a first estimate of resource availability, mining cost, and environmental impact assessment and cost analysis. Available resource is not completely reported, so the available estimate is lower than actual resource. Mining costs are optimized, so provide a low estimate of potential costs. Environmental impact estimates are on the high end of potential impact that may be incurred because it is assumed that impact is unavoidable. Control costs vary. Estimated cost to control subsidence and surface mine pit impacts are suitable estimates of the cost to reduce land impacts. Erosion control and robotic mining system costs are lower, and methane and acid mine drainage control costs are higher, than they may be in the case that these impacts must be reduced.
Contact
Melissa Chan
Kennedy School of Government
Harvard University
79 JFK Street
Cambridge MA 02138
melissa_chan@ksg.harvard.edu

Meeting Electric Peak on the Demand Side: Wholesale and Retail Market Impacts of Real-Time Pricing and Peak Load Management Policy, Kathleen Spees, 2008
Traditionally, the participation of customers in the electric market has been weak or non-existent. Almost all customers have paid a flat rate for power without variations based on the time of their consumption, so these customers have had no incentive to reduce their usage during times of capacity shortage and very high wholesale prices. Perhaps even more importantly, customers have not participated in forward decisions about whether it would be better to build additional capacity at very high cost or to commit to peak load reductions during a few peak hours each year. In this thesis I present the status of efforts to incorporate customer decisions into the electric market place and calculate the possible system benefits.
In Part I I discuss recent activities relating to demand response and demand-side management. Although interest in demand response is growing among policy-makers and industry participants, the process of making this possible will be a complicated navigation among the incentives of involved parties and the jurisdictions of state and federal regulators. One of the key problems in developing a coordinated policy is that the wholesale markets covering generation and transmission are under the jurisdiction of the federal government represented by the Federal Energy Regulatory Commission while electric distribution and retail markets are under the jurisdiction of the state, represented by state public utility commissions (PUC).
In Part II I investigate the value to the system of reducing peak demand and compare this value to the current costs of peak load reductions. Peak load reductions are currently being achieved at $21/kW∙y, or less than one fourth of the $94/kW∙y it costs to build new capacity. Similarly, energy efficiency is being achieved at $29/MWh, or roughly one third of the $92/MWh retail price for electricity. At current rates, peak load could be cost-effectively reduced by some 17%, although I expect that at greater levels of peak reductions the marginal cost of achieving more reductions will increase, it is clear that significant peak load reductions can be achieved cost-effectively.
I further investigate the value to the system of shifting the burden of uncertainty in peak load on to customers and the utilities acting on their behalves who have the most ability to determine what peak load will be. The traditional means of accounting for uncertainty in peak load has been to build enough excess capacity that the chance of shortages is low. I calculate that a right-sizing peak capacity to the best estimate of peak load would reduce the amount cost of supplying capacity by 8.5% below the current level.
In Part III I investigate the short-run economic impacts of a policy change from flat-rate retail electric pricing to real-time prices (RTP) or time-of-use (TOU) prices. If retail prices reflected hourly wholesale market prices, customers would shift consumption away from peak hours and installed capacity could drop. I use hourly price and load data from Pennsylvania-New Jersey-Maryland Regional Transmission Organization (RTO) to estimate consumer and producer savings from a change toward RTP or TOU. Surprisingly, neither RTP nor TOU has much effect on average price under plausible short-term consumer responses. Consumer plus producer surplus rises 2.8%-4.4% with RTP and 0.6%-1.0% with TOU. Peak capacity savings are seven times larger with RTP. Peak load drops by 10.4%-17.7% with RTP and only 1.1%-2.4% with TOU. Half of all possible customer savings from load shifting are obtained by shifting only 1.7% of all MWh to another time of day, indicating that only the largest customers need be responsive to get the majority of the short-run savings.
Placing customers on an RTP can benefit them through lower average rates for energy and capacity, but the advanced metering infrastructure (AMI) required to make RTP and customer response possible is a large investment. In Part IV I determine how many customers can be cost-effectively placed on RTP from the perspective of a PUC. I calculate that for wide scale implementation of AMI, all customers above 2.5 kW in coincident peak load (about 40% of all customers, representing all industrial, all commercial, and large residential customers) could be cost-effectively placed on RTP if there are no benefits to the AMI other than demand response from RTP. For the customers below size 0.31-0.73 kW (the smallest 10%-20% of customers, representing small residential loads), installing an AMI is not cost effective even under the most favorable assumptions about other AMI benefits and highly responsive customers. For intermediate-size customers the investment would be justified in some cases but not others.
Contact:
Kathleen Spees
Kathleen.Spees@brattle.com

Limiting the Financial Risks of Electricity Generation Capital Investments Under Carbon Constraints: Applications and Opportunities for Public Policies and Private Investments, Adam Newcomer, 2008
Increasing demand for electricity and an aging fleet of generators are the principal drivers behind an increasing need for a large amount of capital investments in the US electric power sector in the near term. The decisions (or lack thereof) by firms, regulators and policy makers in response to this challenge have long lasting consequences, incur large economic and environmental risks, and must be made despite large uncertainties about the future operating and business environment. Capital investment decisions are complex: rates of return are not guaranteed; significant uncertainties about future environmental legislation and regulations exist at both the state and national levels - particularly about carbon dioxide emissions; there is an increasing number of shareholder mandates requiring public utilities to reduce their exposure to potentially large losses from stricter environmental regulations; and there are significant concerns about electricity and fuel price levels, supplies, and security.
Large scale, low carbon electricity generation facilities using coal, such as integrated gasification combined cycle (IGCC) facilities coupled with carbon capture and sequestration (CCS) technologies, have been technically proven but are unprofitable in the current regulatory and business environment where there is no explicit or implicit price on carbon dioxide emissions.
The paper examines two separate scenarios that are actively discussed by policy and decision makers at corporate, state and national levels: a future US electricity system where coal plays a role; and one where the role of coal is limited or nonexistent. The thesis intends to provide guidance for firms and policy makers and outline applications and opportunities for public policies and for private investment decisions to limit financial risks of electricity generation capital investments under carbon constraints.
Contact:
Adam Newcomer
Exelon Power Team
10 South Dearborn Street
Chicago, IL 60603
Adam.Newcomer@exeloncorp.com

Emerging Electric Energy Storage Technologies and Demand Response in Deregulated Electricity Markets, Rahul S. Walawalkar, 2008.
Unlike markets for storable commodities, electricity markets depend on the real-time balance of supply and demand. Although much of the present-day grid operates effectively without storage, cost-effective ways of storing electrical energy can help make the grid more efficient and reliable. I have investigated the economics of two emerging electric energy storage (EES) technologies: sodium sulfur (NaS) batteries and flywheels in the electricity markets operated by the New York Independent System Operator (NYISO) and the PJM Interconnection (PJM). The analysis indicates that there is a strong economic case for flywheel installations in both the PJM and NYISO markets for providing regulation services. The economic case for NaS batteries for energy arbitrage is weak in both NYISO and PJM. Some of the uncertainties regarding regulation market rules are one of the reasons for lack of investment in flywheels. On the other hand, some market participants have already made investments in NaS batteries due to anticipated system upgrade deferral benefits. Capital cost reduction and efficiency are important factors that will influence the economics of NaS batteries for energy arbitrage in deregulated electricity markets.
I have also analyzed the economic demand response program offered by PJM.
PJM's program provided subsidies to customers who reduced load in response to price signals before 2008. The program incorporated a "trigger point", set at a locational marginal price of $75/MWh, at or beyond which payments for load reduction included a subsidy payment. Particularly during peak hours, such a program saves money for the system, but the subsidies involved may introduce distortions into the market. I have simulated demand-side bidding into the PJM market, and compare the economic welfare gains with the subsidies paid to price-responsive load using load and price data for year 2006. The largest economic effect is wealth transfers from generators to non price-responsive loads. Based on the incentive payment structure that was in effect through the end of 2007, I estimate that the social welfare gains exceeded the subsidies during 2006. Lowering the trigger point increases the transfer from generators to consumers, but may result in the subsidy outweighing the social welfare gains due to load curtailment.
Contact:
Rahul S. Walawalkar
Customized Energy Solutions Ltd.
100 North 17th Street, 14th Floor
Philadelphia, PA 19103 USA
rahul@walawalkar.com

The Economics of CO2 Transport by Pipeline and Storage in Saline Aquifers and Oil Reservoirs, Sean T. McCoy, 2008
Large reductions in carbon dioxide (CO2) emissions are needed to mitigate the impacts of climate change. One method of achieving such reductions is
CO2 capture and storage (CCS). CCS requires the capture of carbon dioxide
(CO2) at a large industrial facility, such as a power plant, and its transport to a geological storage site where CO2 is sequestered. If implemented, CCS could allow fossil fuels to be used with little or no CO2 emissions until alternative energy sources are more widely deployed. Large volumes of CO2 are most efficiently transported by pipeline and stored either in deep saline aquifers or in oil reservoirs, where CO2 is used for enhanced oil recovery (EOR). This thesis describes a suite of models developed to estimate the project-specific cost of CO2 transport and storage. Engineering-economic models of pipeline CO2 transport, CO2-flood EOR, and aquifer storage were developed for this purpose. The models incorporate a probabilistic analysis capability that is used to quantify the sensitivity of transport and storage cost to variability and uncertainty in the model input parameters. The cost of CO2 pipeline transport is shown to be sensitive to the region of construction, in addition to factors such as the length and design capacity of the pipeline. The cost of CO2 storage in saline aquifers is shown to be most sensitive to factors affecting site characterization cost. For EOR projects, CO2 storage has traditionally been a secondary effect of oil recovery; thus, a levelized cost of CO2 storage cannot be defined. Instead EOR projects were evaluated based on the breakeven price of CO2 (i.e., the price of CO2 at which the project net present value is zero). The breakeven CO2 price is shown to be most sensitive to oil prices, losses of CO2 outside the productive zone of the reservoir, and reservoir pressure. Future research should include collection and aggregation of more specific data characterizing possible sites for aquifer storage and applications of these models to this data. The implications of alternative regulations and requirements for site characterization should also be studied to more fully assess cost impacts.
Contact:
Sean T. McCoy
Department of Engineering & Public Policy Carnegie Mellon University stmccoy@andrew.cmu.edu

A Life Cycle Comparison of Coal and Natural Gas for Electricity
Generation and the Production of Transportation Fuels
, Paulina Jaramillo, 2007
Demand for electricity is expected to increase in the next 25 years. Currently, 50% of the electricity generated in the U.S. is produced using coal. Although natural gas has traditionally been used by the commercial, industrial and residential sector, demand for natural gas for electricity generation has increased in the past decade and this growth is expected to continue in the next 25 years. Since demand is growing but North American supply is expected to remain constant, alternative sources of natural gas will need to be developed. LNG has been identified as one alternative, and plans to increase imports of this fuel are underway. In addition, synthetic natural gas could be produced from coal to meet some of the increasing demand for natural gas.
The demand for natural gas by the transportation sector is currently negligible, but
worldwide interest on natural gas-derived transportation fuels (such as natural gas based Fischer-Tropsh Liquids and Compressed Natural Gas) is increasing. The U.S. could either produce these fuels internally, requiring larger imports of LNG, or import them from natural gas-rich countries. Alternatively, the U.S. could produce transportation fuels from coal. Although non-existent in 2005, by 2030 coal-to-liquid-fuel producers are expected to consume as much coal as coke plants. Thus, the production of transportation fuels is an additional end-use where coal and natural gas could compete as the fuel of choice.
The goal of this research is to compare coal and natural gas for use by the electric power sector and for the production of transportation fuels in the next 25 years. This comparison concentrates on the life cycle GHG emissions of these fuels. In addition to comparing natural gas and coal to determine which fuel is better suited for each end-use, a comparison of each end-use will also be performed in order to help determine which is a better use of each fuel.
Two main results arise from this research. First, it was found that in a future where
advanced power plant technologies with carbon capture and sequestration are used, coal and globally sourced natural gas could have very similar life cycle GHG emissions. This begs the question of whether investing billions of dollars in LNG/SNG infrastructure will lock us into an undesirable energy path that could make future energy decisions costlier than ever expected and increase the environmental burden from our energy infrastructure. Second, it was found that the use of transportation fuels derived from coal and natural gas will not help the U.S. reduce the GHG emissions associated with the life cycle of transportation fuels, and in a worse case scenario, the use of these alternative fuels could in fact increase these GHG emissions. In addition, it was found that there is high uncertainty associated with the energy security benefits that could be associated with the consumption of transportation fuels derived from coal.
Contact:
Paulina Jaramillo
Department of Civil and Environmental Engineering
Carnegie Mellon University
pjaramil@andrew.cmu.edu

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"A Decentralized Approach to Reducing the Social Costs of Cascading Failures", Paul Hines, 2007.
Large cascading failures in electrical power networks come with enormous social costs. These can be direct financial costs, such as the loss of refrigerated foods in grocery stores, or more indirect social costs, such as the traffic congestion that results from the failure of traffic signals. While engineers and policy makers have made numerous technical and organizational changes to reduce the frequency and impact of large cascading failures, the existing data, as described in Chapter 2 of this work, indicate that the overall frequency and impact of large electrical blackouts in the United States are not decreasing. Motivated by the cascading failure problem, this thesis describes a new method for Distributed Model Predictive Control and a power systems application. The central goal of the method, when applied to power systems, is to reduce the social costs of cascading failures by making small, targeted reductions in load and generation and changes to generator voltage set points. Unlike some existing schemes that operate from centrally located control centers, the method is operated by software agents located at substations distributed throughout the power network. The resulting multi-agent control system is a new approach to decentralized control, combining Distributed Model Predictive Control and Reciprocal Altruism.
Experimental results indicate that this scheme can in fact decrease the average size, and thus social costs, of cascading failures. Over 100 randomly generated disturbances to a model of the IEEE 300 bus test network, the method resulted in nearly an order of magnitude decrease in average event size (measured in cost) relative to cascading failure simulations without remedial control actions. Additionally, the communication requirements for the method are measured, and found to be within the bandwidth capabilities of current communications technology (on the order of 100kB/second). Experiments on several resistor networks with varying structures, including a random graph, a scale-free network and a power grid indicate that the effectiveness of decentralized control schemes, like the method proposed here, is a function of the structure of the network that is to be controlled.
Contact:
Paul Hines
Assistant Professor
School of Engineering
301 Votey Hall
University of Vermont
33 Colchester Ave.
Burlington, VT 05405
phines@cems.uvm.edu

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"An Electricity-focused Economic Input-output Model: Life-cycle Assessment and Policy Implications of Future Electricity Generation Scenarios", Joe Marriott, 2007
The electricity industry is extremely important to both our economy and our environment: we would like to examine the economic, environmental and policy implications of both future electricity technologies and the interaction of this industry with the rest of the economy. However, the tools which currently exist to analyze the potential impacts are either too complex or too aggregated to provide this type of information.
Because of its importance, and the surprising lack of associated detail in the inputoutput model of the U.S. economy, the power generation sector is an excellent candidate for disaggregation. This work builds upon an existing economic inputoutput tool, by adding detail about the electricity industry, specifically by differentiating among the various functions of the sector, and the different means of generating power.
We build a flexible framework for creating new industry sectors, supply chains and emission factors for the generation, transmission and distribution portions of the electricity industry. In addition, a systematic method for creating updated state level and sector generation mixes is developed.
The results of the analysis show that the generation assets in a region have a large impact on the environmental impacts associated with electricity consumption, and that interstate trading tends to make the differences smaller. The results also show that most sector mixes are very close to the U.S. average due to geographic dispersion of industries, but that some sectors are different, and they tend to be important raw material extraction or primary manufacturing industries. Further, in scenarios of the present and future, for electricity and for particular products, results show environmental impacts split up by generation type, and with full supply chain detail. For analyses of the current electricity system and products, economic and environmental results match well with external verification sources, but for analyses of the future, there is significant uncertainty. Future work in this area must address the inherent uncertainty of using an economic model to generate emissions values, although the framework of the model allows for infinite expansion and adjustment of assumptions.
Contact:
Joe Marriott
jmm185@pitt.edu

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"U.S. Biomass Energy: An Assessment of Costs & Infrastructure for Alternative Uses of Biomass Energy Crops as an Energy Feedstock", William Morrow, 2006
Reduction of the negative environmental and human health externalities resulting from both the electricity and transportation sectors can be achieved through technologies such as clean coal, natural gas, nuclear, hydro, wind, and solar photovoltaic technologies for electricity; reformulated gasoline and other fossil fuels, hydrogen, and electrical options for transportation. Negative externalities can also be reduced through demand reductions and efficiency improvements in both sectors. However, most of these options come with cost increases for two primary reasons: (1) most environmental and human health consequences have historically and are currently excluded from energy prices; (2) fossil energy markets have been optimizing costs for over 100 years and thus have achieved dramatic cost savings over time. Comparing the benefits and costs of alternatives requires understanding of the tradeoffs associated with competing technology and lifestyle choices.
Bioenergy advocates propose its use as an alternative energy resource for electricity generation and transportation fuel production, primarily focusing on ethanol. These advocates argue that bioenergy offers environmental and economic benefits over current fossil energy use in each of these two sectors as well as in the U.S. agriculture sector. However, estimates of bioenergy resource reveal that bioenergy is only capable of offsetting a portion of current fossil consumption in each sector. As bioenergy is proposed as a large-scale feedstock within the United States, a question of “best use” of bioenergy becomes important. Unfortunately, bioenergy research has offered very few comparisons of these two alternative uses. This thesis helps fill this gap.
This thesis compares the economics of bioenergy utilization by a method for estimating total financial costs for each proposed bioenergy use. Locations for potential feedstocks and bio-processing facilities (co-firing switchgrass and coal in existing coal fired power plants and new ethanol refineries) are estimated and linear programs are developed to estimate large-scale transportation infrastructure costs for each sector. Each linear program minimizes required bioenergy distribution and infrastructure costs. Truck and rail are the only two transportation modes allowed as they are the most likely bioenergy transportation modes. Switchgrass is chosen as a single bioenergy feedstock. All resulting costs are presented in units which reflect current energy markets price norms (¢/kWh, $/gal). The use of a common metric, carbon-dioxide emissions, allows a comparison of the two proposed uses. Additional analysis is provided to address aspects of each proposed use which are not reflected by a carbon-dioxide reduction metric. Using switchgrass as an electricity generation feedstock offers more than twice the amount of carbon-dioxide emission reductions as using switchgrass as an ethanol feedstock (370 versus 160 million short tons per year respectively; representing 14% and 12% of electricity and transportation sector annual CO2 emissions). Total costs, including capital, labor, feedstock, and transportation, is more certain for electricity production than for ethanol; 20 - 45 $/ton CO2 mitigated versus free - 80 $/ton CO2 mitigated respectively. In both cases, mitigation cost is a variable of fossil energy costs. Coal price are very stable as compared to crude oil prices and therefore, more risk is inherent in ethanol economics than in electricity economics.
Additional analysis comparing life-cycle benefits and burdens though full-cost accounting methods also favors bioenergy for electricity production. Agricultural impacts are neutral, while criteria pollutants increase with ethanol use and decrease with bioenergy electricity production. Moreover, ethanol use could cause an increase in groundwater toxicity, a risk that is not associated with electricity production. Considering other available alternative technologies, switchgrass co-firing in existing coal power plants is the least costs retrofitting option available to existing coal fired power plants wishing to lower their carbon emissions. Plug hybrids offer increased system efficiencies over current gasoline-propulsion systems, thereby lowering criteria pollutants and greenhouse gas emissions all at a cost less than or comparable to ethanol. However, shifting transportation energy demands into the United States’ antiquated electrical grid will require large-scale electricity infrastructure investments. The economic impact of a large-scale transfer of energy from petroleum to electricity should be a topic of future research.
Contact
William R. Morrow, III, Ph.D., P.E.
Senior Consultant
Energy and Environmental Economics, Inc.
101 Montgomery Street, Suite 1600
San Francisco, CA 94104
415-391-5100 (phone)
415-391-6500 (fax)
bill@ethree.com

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"Capturing CO2 From Ambient Air: A Feasibility Assessment", Joshuah K. Stolaroff, 2006.
In order to mitigate climate change, deep reductions in CO2 emissions will be required in the coming decades. Carbon capture and storage will likely play an important role in these reductions. As a compliment to capturing CO2 from point sources, CO2 can be captured from ambient air ("air capture"), offsetting emissions from distributed sources or reducing atmospheric concentrations when emissions have already been constrained. In this thesis, we show that CO2 capture from air is physically and thermodynamically feasible, discuss the various routes available, and explain why NaOH solution is a viable sorbent for largescale capture. An example system using NaOH spray is presented. With experimental data and a variety of numerical techniques, the use of NaOH spray for air capture is assessed and an example contacting system developed. The cost and energy requirements of the example contacting system are estimated. Contactor estimates are combined with estimates from industry and other research to estimate the cost of a complete air capture system. We find that the cost of capturing CO2 with the complete system would fall between 80 and 250 $/t-CO2, and improvements are suggested which reduce the upper-bound cost to 130 $/t-CO2. Even at the high calculated cost, air capture has implications for climate policy, however dedicated engineering and technological innovation have potential to produce much lower-cost systems.
Contact:
Joshuah K. Stolaroff
Center for Program Analysis
Office of Solid Waste and Emergency Response
Environmental Protection Agency
1200 Pennsylvania Ave NW
Mailcode: 5101T
Washington, DC 20460
stolaroff.joshuah@epa.gov

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"Valuing Risk-Reduction: Three applications in the Electricity Industry.", Dalia Patiño Echeverri, 2006.
This dissertation is motivated by the belief that it is possible for regulators to attenuate some of the uncertainties that surround the operation of electricity markets, and therefore understanding the sources, implications and costs of these uncertainties can help shape policies in the field. At least in some cases, the quantification of the effects of uncertainty can serve as an incentive for industry participants and regulators to make a common front against unnecessary costs.Options theory and the method of risk-neutral valuation provide a framework to quantify the value of hedging against uncertainty. By incorporating options theory –widely used in the financial world- this thesis contributes a framework to quantify the risks and value accordingly the instruments or strategies that provide hedging. Having an idea of what the fair cost of hedging is, we will have better tools to identify inefficiencies and opportunities for regulation improvement.
This dissertation looks at three cases of uncertainty in the electricity industry, related to generation, transmission and ancillary services, and proposes a method to quantify the cost of this uncertainty and use this value to inform policy making. In the three cases, there is a strategy or contract that can be seen as a hedging instrument and valued as such. In the ambit of electricity transmission, Financial Transmission Rights (FTRs) can be seen as hedging instruments that provide protection against highly volatile transmission congestion costs. An FTR is essentially a contract that allows (or obligates) the holder to get the monetary difference between the marginal price of electricity at the point where it is withdrawn to the marginal price electricity at its source. In the ambit of electricity generation, the investment in environmental-control-devices or cleaner generation technologies can be seen as protection against the risk of not being able to comply with potential stringent air-emission regulations. In the ambit of ancillary services, the provision of reliability-support resources can be seen as reduction of the risk of not being able to deal with contingencies that treat the instantaneous balance between supply and demand.
Contact
Dalia Patiño Echeverri
Assistant Professor
Nicholas School of the Environment and Earth Sciences
Box 90328
Duke University
Durham, NC 27708
919.613.8000

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Electric Power Micro-grids: Opportunities and Challenges for an Emerging Distributed Energy Architecture, Douglas E. King, 2006
Distributed energy resources (DERs) have become the focus of considerable research and investigation, as well as commercial interest in the U.S. and around the world. Despite a significant body of research that explores the potential benefits associated with DERs, several factors have combined to make progress toward serious adoption in the US very slow. These include:
technical challenges; the absence of suppliers who can provide "turn-key"
systems; real and perceived risks associated with the large-scale integration of DERs; the reluctance of legacy utilities to allow new entrants into markets in which, up until now, they have enjoyed a monopoly; and general deliberation and caution on the part of state utility regulators.
One emerging concept that holds considerable potential for improving the value of DERs is the micro-grid architecture, which builds on conventional continuous-use DER applications by aggregating and interconnecting small groups of customers onto a local grid. Some of the advantages of this kind of aggregation parallel the advantages of the centralized grid system - better resource utilization, increased redundancy and system robustness, and possible economies of scale. Other advantages include: increased levels of reliability, much greater net energy-use efficiency through the use of combined-heat-and-power applications, and increased customer choice and flexibility. Although progress has been made by both the regulatory and business community that has led to limited growth of conventional continuous-use DER applications, the micro-grid concept has yet to attract much commercial attention in the U.S.
Chapter 2 presents the results of the micro-grid customer engineering-economic model (MCEEM), developed by the author. In some cases, micro-grids can be good investments with current utility rate structures, reducing net present energy costs over a 25-year period by 5-10% in many of the cases studied and by over 20% in the best cases. The economic value of a micro-grid is shown to be greater for customers that have a value for highly-reliable electric power supply. The cost of natural gas and electricity is a significant factor in estimating the value of micro-grids, and continually rising natural gas prices may decrease their value, but other factors are also shown to be very significant. A sensitivity analysis reveals that the choice of micro-grid customer mix also has a large impact on system economics, whereas climate plays only a modest role. Economies of scale are shown to be fairly modest for the scenarios studied, but micro-grids do show clear benefits over traditional single customer distributed generation (DG). If performance goals of current United States Department of Energy (US DOE) research programs for IC engines and micro-turbines are met, rates of return for micro-grid investments increase 10-20%.
In Chapter 3, the regulatory environment for micro-grids is examined using results from a survey of state regulatory officials conducted in Fall 2004.
Only 17 of 27 participating states indicated that the installation and operation of a micro-grid is probably or definitely legal, and only under certain circumstances and subject to varying stipulations that make for an unattractive market environment. Among those 17 states, only 4 indicated that existing laws for the interconnection and operation of DERs would apply to micro-grid systems. No states have clear guidance for the regulatory oversight of micro-grid systems once they are installed, and most respondents indicated that such oversight would be conducted on a case-by-case basis. A series of recommendations for regulatory change are provided that could reduce uncertainty and lead to a much more hospitable environment for microgrid market development.
Chapter 4 addresses the question of how electric utilities can best recover net costs from customer generators. The problem of tariff design for customer-generators is introduced, with an overview of the competing goals of utility tariffs and the various mechanisms (i.e. tariff components) for cost recovery. The various costs and benefits that customer-generators can impose on electric utilities are discussed, along with a framework for how both benefits and costs can and should be quantified and incorporated into the rate-setting process. Results from the MCEEM are presented that demonstrate how well (or poorly) different tariff components achieve the goals of a utility tariff, and the implications of these results are discussed. Standby rates are shown to increase customer peak period consumption by customer-generators, and represent a poor choice for cost-recovery in most cases. Increased demand charges are shown to be the best option for cost-recovery by utilities in most cases.
Chapter 5 examines the argument that a market based on DERs will have higher rates of innovation and new technology adoption than conventional, centralized supply. Data from the electricity industry are provided that demonstrate historically low rates of innovation and adoption. The characteristics that distinguish DERs from centralized supply - small size, dispersed resources, and modular design - are described, and relevant literature from the fields of economics and management science is discussed.
This literature provides theoretical support for the claim that DERs will encourage greater innovative activity, but the claim is not tested empirically.
Contact:
Douglas E. King
Building Knowledge, Inc.
425 Orange Street, Apt. 401
Oakland, CA 94610
douglaseking@gmail.com

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Network Topologies and Transmission Investment Under Electric-Industry Restructuring, Seth Adam Blumsack, 2006
A number of factors, including the U.S. blackout of August, 2003, have convinced even some skeptics that the North American power grid is under increasing stress, and that restructuring has failed to attract sufficient transmission investment in areas controlled by regional transmission organizations (RTOs). The architects of electricity restructuring hoped that the energy markets run by RTOs would encourage a vibrant non-utility transmission segment of the industry. Analyses by Hogan (1992) and Bushnell and Stoft (1996) suggest compensating transmission investors by awarding them financial rights to a portion of the congestion rent along a given network path. An allocation of these financial rights that respects the physical constraints of the network will yield the proper incentives for market-based transmission planning.
This thesis addresses several issues in transmission planning and investment in the restructured electricity industry. In particular, the thesis exploits topological structures common in actual power networks to highlight some problems with market-based transmission planning.
The topological analysis of the power grid focuses on identifying and analyzing Wheatstone structures embedded in larger systems. In other networks (such as water or gas pipes, the internet, and even crowd control), the Wheatstone network is associated with the Braess Paradox, a phenomenon where adding links to a network increases congestion throughout the network. This thesis provides the first quantitative analysis of how the presence of a Wheatstone structure can affect the flow of power through electric networks, and develops a fast heuristic algorithm to identify embedded Wheatstone structures, which are quite common in real networks.
In power systems that use locational pricing signals to manage congestion and promote investment, the presence of an embedded Wheatstone network drives a wedge between the price signal and the underlying physical state of the grid. Locational prices fail to identify the active system constraint; simply upgrading the transmission line with the highest congestion price fails to relieve physical congestion in the system. The thesis derives conditions under which this phenomenon occurs. One consequence is that even if financial congestion contracts are allocated according to the method suggested by Hogan (1992), investors can still profit from exploiting the Braess Paradox – that is, by constructing transmission lines that cause congestion rather than relieving congestion.
Wheatstone networks can cause congestion, but they may be justified on the grounds that they increase the reliability of the network, helping to reduce the frequency of blackouts. Models of market-based transmission investment labor under the assumption that congestion and reliability are independent attributes in power networks. New transmission links can be justified as providing either a reliability benefit or an economic (congestion-relief) benefit. The cost of investments made for reliability should be socialized, while market incentives will provide for economic investments. This thesis provides the first quantitative assessment of the claim that reliability and congestion are independent. The thesis develops metrics to decompose a line’s reliability benefit from its impact on network congestion, and applies these metrics to four embedded Wheatstone sub-networks in the IEEE 118-bus test system. While it is possible to account separately for a transmission line’s effect on system reliability and congestion, the two are almost never independent quantities. Further, the benefit of a particular transmission line to the network varies highly with the level of demand and the topological state of the rest of the system.
From a policy standpoint, the analysis of Wheatstone networks in this thesis suggests that the debate over transmission investment, at least in areas that have undertaken restructuring, has been misguided. The principal problem is not with non-utility transmission, but in the way that RTOs have proposed to compensate non-utility transmission investments. RTOs should stop trying to attract transmission investment by offering financial contracts based on locational spot-market prices. RTOs and their regulators also need to realize that the network benefit of a given transmission project depends critically on identifying the relevant range of demand and the state of the system, both at the time of construction and into the future. Under restructuring, the transmission planning problem has been cast as a problem of encouraging competition under peak demand conditions. It should be re-cast as a problem in risk management. The question of who (utilities, non-utility transmission companies, or RTOs) should bear the responsibility for transmission investment is a matter of who can manage this risk at the lowest cost.
Contact:
Seth Blumsack
Assistant Professor of Energy Policy and Economics
Department of Energy and Mineral Engineering
Penn State Institute for Energy and the Environment
The Pennsylvania State University
University Park, PA 16802
blumsack@psu.edu

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A Technical and Economic Assessment of CO2 Capture Technology for IGCC Power Plants, Chao Chen, 2005
As an emerging technology for electric power generation, Integrated Gasification Combined Cycle (IGCC) power plants are of increasing interest because of their potential advantage for CO2 capture in addition to conventional pollution control. To further explore this technology, this thesis develops a general modeling framework to provide tools for assessing gasification-based energy conversion systems with various CO2 capture options on a systematic and consistent basis.
Many factors influence the performance and cost of an IGCC power plant.
Simulation studies of an oxygen-blown Texaco quench gasifier system with a water gas shift (WGS) reactor and Selexol CO2 capture unit indicated that the CO2 avoidance cost is lowest when the CO2 removal efficiency is in the range of 85%-90%. The overall cost of IGCC systems with and without CO2 and storage varied significantly with coal quality and plant size (among other factors). For low rank coals (sub-bituminous and lignite) costs increased significantly relative to the nominal case with bituminous coal. It was also found that larger IGCC plants have slightly higher thermal efficiency and lower capital cost. Without incentive financing, however, an IGCC power plant without CO2 capture was found to be less competitive (more costly) than PC and NGCC power plants in terms of both the total capital requirement and cost of electricity production. However, IGCC plants with CO2 capture were competitive with PC and NGCC capture plants without incentive financing.
This thesis also provides an overview of available options and decisions factors for using IGCC technology to repower aging PC power plants. Studies in this thesis show that IGCC repowering is less capital intensive than greenfield plants, but the feasibility of repowering is very site-specific.
Under suitable conditions, IGCC repowering may be an economically attractive option for existing PC plants.
This thesis also attempts to characterize key uncertainties affecting the performance and cost of IGCC systems with CO2 capture through data mining and Monte Carlo simulation. Most of the capital cost uncertainty in an IGCC capture plant comes from the IGCC process, rather than the CO2 capture process. Considering the historical variability of capacity factor and coal price for large U.S. coal plants, the COE of an IGCC capture plant may be higher than the expected value based on typical deterministic assumptions.
This thesis also presents preliminary evaluations of IGCC systems using two advanced technologies, the Ion Transport Membrane (ITM) system for oxygen production and the GE H-class gas turbine system for power generation. Study results show that these two technologies can significantly improve the competitiveness of IGCC systems and will influence the application of IGCC technologies in the near future.
Contact:
Chao Chen
Chao.Chen@WorleyParsons.com

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Future Electricity Generation: An Economic and Environmental Life Cycle Perspective on Near-, Mid- and Long-Term Technology Options and Policy Implications, Joule Andrea Bergerson 2005
The U.S. electricity industry is currently experiencing and adapting to enormous change including concerns related to security, reliability, increasing demand, aging infrastructure, competition and environmental impacts. Decisions that are made over the next decade will be critical in determining how economically and environmentally sustainable the industry will be in the next 50 to 100 years. For this reason, it is imperative to look at investment and policy decisions from a holistic perspective, i.e., considering various time horizons, the technical constraints within the system and the environmental impacts of each technology and policy option from an economic and environmental life cycle perspective.
This thesis evaluates the cost and environmental tradeoffs of current and future electricity generation options from a life cycle perspective. Policy and technology options are considered for each critical time horizon (near-, mid-, and long-term). The framework developed for this analysis is a hybrid life cycle analysis which integrates several models and frameworks including process and input-output life cycle analysis, an integrated environmental control model, social costing, forecasting and future energy scenario analysis.
The near-term analysis shows that several recent LCA studies of electricity options have contributed to our understanding of the technologies available and their relative environmental impacts. Several promising options could satisfy our electricity demands. Other options remain unproven or too costly to encourage investment in the near term but show promise for future use (e.g. photovoltaic, fuel cells). Public concerns could impede the use of some desirable technologies (e.g. hydro, nuclear). Finally, less tangible issues such as intermittency of some renewable technologies, social equity and visual and land use impacts, while difficult to quantify, must be considered in the investment decision process.
Coal is a particularly important fuel to consider in the U.S. and is the main focus of this thesis. A hybrid life cycle analysis including the use of process level data, Economic Input-Output Life Cycle Assessment (EIOLCA) and the Integrated Environmental Control Model (IECM) quantify a range of potential impacts for new power plants. This method provides a more complete and consistent basis for comparing different technologies. While Integrated Coal Gasification Combined Cycle (IGCC) technology has clear environmental benefits for bituminous coals over conventional pulverized coal plants, the advantages are less clear for the lower ranked coals at present. Near-term implementation of this technology is hampered by concerns about its reliability and performance. A full scale U.S. installation of this technology would settle the performance concerns while more stringent emissions standards would increase its value. In the mid-term analysis, this thesis explores alternative methods for transport of coal energy. A hybrid life cycle analysis is critical for evaluating the cost, efficiency and environmental tradeoffs of the entire system. If a small amount of additional coal is to be shipped, current rail infrastructure should be used where possible. If entirely new infrastructure is required, the mine mouth generation options are cheaper but have increased environmental impact due to the increased generation required to compensate for transmission line losses. Gasifying the coal to produce methane also shows promise in terms of lowering environmental emissions.
The long-term analysis focuses on the implications of a high coal use future. This scenario analysis focuses on life cycle issues and considers various generation and control technologies. When advanced technologies such as gasification with carbon capture and sequestration are used, emissions during generation decrease to a level where environmental discharges from extraction, processing and transportation become the dominant concern. The location of coal, coal composition and mining method are important in determining the overall impacts.
Coal is an inherently dirty fuel. However, for the next half century, coal is likely to play a major role in electricity generation. In deciding how much coal to use, the U.S. must understand the cost and environmental implications of the technologies available, including the whole life cycle of the fuel and the facilities used from extraction, transport, generation, and use or disposal of by products.
Contact:
Dr. Joule A. Bergerson
University of Calgary
Chemical and Petroleum Engineering
2500 University Drive NW, Room 602
Earth Sciences Building
Calgary, Alberta T2N 1N4
Canada
jbergers@ucalgary.ca

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Mapping Alternatives: Facilitating Citizen Participation in Development Planning and Environmental Decision Making, Shalini P. Vajjhala 2005
Recent decades have seen a growing international awareness of the need for major development projects in tandem with a call for more environmentally sensitive decision making; however, many technical infrastructure projects currently face widespread difficulty associated with facilities siting. This rising difficulty is due to a variety of causes, including public opposition and not-in-my-backyard (NIMBY) protests. Efforts to mitigate public opposition have focused on improving citizen participation, but many participatory programs have still resulted in opposition and project delays. Taken as a whole, there is a growing need for 1) better characterizations of siting difficulty and the relative role of public opposition and 2) new strategies for facilitating timely, inclusive, and effective public participation.
The five main chapters of this dissertation bring together these interrelated problems. Each chapter consists of a stand-alone paper that together offer an integrated view of participatory development planning and environmental decision-making. Chapter 1 presents an introduction that connects the fields of planning and participation. Chapters 2 and 3 develop a policy-level quantitative evaluation of facilities siting difficulty and its major causes, including public opposition, based on a case study of electric transmission line siting. Next Chapter 4 proposes a conceptual framework of the basic components of participatory processes to link these agency-level analyses on siting difficulty and public opposition to local level participation. Chapters 5 and 6 then provide a counterpart to this top-down view through a series of community-level mapping studies to understand local priorities, perceptions, and preferences for “the backyard.” These studies further evaluate a combination of community mapping and Geographic Information Systems (GIS) as a new tool for facilitating participation. Finally, Chapter 7 concludes with a discussion of additional applications of the proposed mapping methods and avenues for future research.
Major results from all chapters include a state-level quantitative model for predicting siting difficulty and its dominant causes across the U.S. Results of siting analyses in Chapter 2 and 3 reveal large variations in state-level transmission line siting difficulty and demand. These variations have the potential to negatively impact the long-term success of current policy proposals such as Regional Transmission Organizations (RTOs) and federal eminent domain authority. Furthermore, perceptions of siting difficulty and siting constraints, including public opposition, vary significantly among stakeholders associated with different phases of project timelines. In spite of these variations, public opposition is identified as the dominant constraint on transmission siting from both qualitative survey results and related quantitative assessments.
These results bring the focus to the role of citizen participation as a means of addressing public concerns and improving siting decisions. Toward this end, the studies in Chapters 5 and 6 offer a complement to these agency-level findings. The results from these chapters provide strong support for the proposed combination of participatory mapping and GIS as an effective tool for 1) facilitating project information exchange, 2) enabling broader feedback and stakeholder communication, and 3) supporting participatory decision-making in development planning. Finally, Chapter 7 extends the proposed methods and findings to an ongoing transport planning project in Lesotho, Southern Africa.
Taken as a whole, this dissertation examines a sequence of important and interconnected issues: the need for new infrastructures, the causes of siting difficulty, the related call for participation, and strategies for improving public involvement. The integration of the top-down and bottom-up evaluations within this research provides a necessary transition from designing and informing effective policies to coordinating and implementing locally relevant solutions.
Contact:
Dr. Shalini Vajjhala
Resources for the Future
1616 P Street, NW
Washington, DC 20036-1400
shalini@rff.org

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The Economics and Environmental Impacts of Large-Scale Wind Power in a Carbon Constrained World, Joseph DeCarolis, 2004
Serious climate change mitigation aimed at stabilizing atmospheric concentrations of CO2 will require a radical shift to a decarbonized energy supply. The electric power sector will be a primary target for deep reductions in CO2 emissions because electric power plants are among the largest and most manageable point sources of emissions. With respect to new capacity, wind power is currently one of the most inexpensive ways to produce electricity without CO2 emissions and it may have a significant role to play in a carbon constrained world. Yet most research in the wind industry remains focused on near term issues, while energy system models that focus on century-long time horizons undervalue wind by imposing exogenous limits on growth. This thesis fills a critical gap in the literature by taking a closer look at the cost and environmental impacts of large-scale wind.
Estimates of the average cost of wind generation – now roughly 4¢/kWh – do not address the costs arising from the spatial distribution and intermittency of wind. Even when wind serves an infinitesimal fraction of demand, its intermittency imposes costs beyond the average cost of delivered wind power. This thesis develops a theoretical framework for assessing the intermittency cost of wind. In addition, an economic characterization of a wind system is provided in which long-distance electricity transmission, storage, and gas turbines are used to supplement variable wind power output to meet a time-varying load. With somewhat optimistic assumptions about the cost of wind turbines, the use of wind to serve 50% of demand adds ~1-2¢/kWh to the cost of electricity, a cost comparable to that of other largescale low carbon technologies.
This thesis also explores the environmental impacts posed by large-scale wind. Though avian mortality and noise caused controversy in the early years of wind iv development, improved technology and exhaustive siting assessments have minimized their impact. The aesthetic valuation of wind farms can be improved significantly with better design, siting, construction, and maintenance procedures, but opposition may increase as wind is developed on a large scale. Finally, this thesis summarizes collaborative work utilizing general circulation models to determine whether wind turbines have an impact of climate. The results suggest that the climatic impact is non-negligible at continental scales, but further research is warranted.
Contact:
Dr. Joseph DeCarolis
Atmospheric Protection Branch
Office of Research and Development
U.S. Environmental Protection Agency
Mail Drop E305-02
109 TW Alexander Drive
Research Triangle Park, NC 27711
decarolis.joseph@epa.gov

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Two Essays on Problems of Deregulated Electricity Markets, Dmitri Perekhodtsev, 2004
1. The data from California energy crisis of 2000 suggests that the largest departures of observed electricity prices from the estimates of the competitive price occur when demand approaches market capacity. This paper studies models of unilateral and collusive market power applicable to electricity markets. Both suggest a unique mechanism explaining the increase of the price-cost margin with demand. The empirical test of these models provides more evidence for unilateral market power than for behavior suggesting tacit collusion.
2. In order to preserve the stability of electricity supply, electric generators have to provide ancillary services in addition to energy production. Hydro generators are believed to be the most efficient source of ancillary services because of their good dynamic flexibility. This paper studies optimal operation decisions for river dams and pumped storage facilities operating in markets for energy and ancillary services as well as the change in the water shadow price in presence of ancillary services markets. The analysis is applied to valuation of the ancillary services provided by hydro resources in the Tennessee Valley Authority. A simulation of ancillary services markets shows that TVA’s hydro resources providing ancillary services can allow for substantial savings in total costs of energy provision. Optimal hydro scheduling in markets for energy and ancillary services increases the value of TVA’s hydro resources by 9% on average and up to 26% for particular units. As a result of hydro participation in ancillary services markets water shadow prices of river dams drop significantly allowing for tightening hydro constraints in favor of other water uses.
Contact:
Dr. Dmitri Perekhodtsev
LECG
66 Avenue de New York
75116 Paris
France
DPerekhodtsev@lecg.com

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Electric Power Systems Under Stress: An Evaluation of Centralized Versus Distributed System Architectures, Hisham Zerriffi, 2004
The issue of electric power systems under persistent and high stress conditions and possible changes to electric power systems to deal with this issue is the subject of this dissertation. The stresses considered here are not the single event type of disruptions that occur as a result of a hurricane or other extreme weather event or the large blackouts that result from a particular set of circumstances. Instead the focus is on conditions that cause systematic and long-term performance degradation of the system such as underinvestment in infrastructure, poor maintenance, and military conflict.
While it has long been recognized that persistent stresses such as conflict and war can have a large impact on electric power systems, there has been few systematic analyses of the problem. The first goal of this research was to model and quantify the reliability and economic differences between centralized and distributed energy systems for providing electricity and heat, particularly under stress conditions. This goal was met through the development of Monte Carlo reliability simulations, applied to different system network topologies. The results of those models show significant potential improvements in energy delivery with distributed systems.
The second goal was to determine the impact of heterogeneity of local loads on the desired level of decentralization of the system and the impact of decentralization on the network requirements. This goal was met through a combination of Monte Carlo simulations applied to systems with differentiated and non-coincident loads and an optimal power flow applied to a more realistic network topology. The results of those models show the potential for improvements when loads are non-coincident and micro-grids can share power as well as the fact that the power sharing may be largely limited to local clusters of micro-grids. This research also showed the need for incorporation of stress in power systems modeling and a method for characterizing stress.
Contact:
Hisham Zeriffi
Assistant Professor
Ivan Head South/North Research Chair
Liu Institute for Global Issues
University of British Columbia
6476 NW Marine Dr.
Vancouver BC V6T 1Z2
Canada
hzerriffi@exchange.ubc.ca

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