Electricity generation has significant environmental impacts, including on regional air quality, greenhouse gas emissions, and water availability. Modeling the overall environmental impact of electricity generation requires linked simulations of power generation, air pollution physics and chemistry, greenhouse gas emissions, and water use. Tools for performing these analyses in an integrated manner are just beginning to emerge. This work expands on the development of linked models for electricity generation, air quality, and water use that have provided single-day snapshots of these environmental impacts. The original model used a non-linear optimization model for power generation, a regional photochemical model for air quality impacts, and self-contained modules for greenhouse gas emissions and water usage at power plants in Texas. The new model includes life cycle scenarios for the power sector (including changes in both the fuel production and electricity generation stages) and expands the temporal scale of the modeling framework to include impacts on monthly, seasonal, and annual time scales instead of on single days. In addition, the air quality framework has been expanded to include atmospheric particulate matter as an air quality impact. This modeling framework will be used to assess the air quality impacts of new natural gas developments in the Barnett and Eagle Ford shale regions in Texas, the consumptive water impact of new natural gas development in Texas, the impact of seasonal versus ozone forecast-based pricing for power plant NOx emissions in the state of Texas, and the potential cost and air quality impacts of drought-based operation of the power grid in Texas. / text

Electric power generation using wind turbines is on the rise in not only the United States but the entire globe. While the benefits from such methods of generation include clean and renewable energy, wind turbines may pose a potential risk to the stability of grid operation. Wind turbine generators are similar to conventional generators; however, the manner with which the wind turbine is coupled to the grid may reduce system inertia and increase the magnitude of transient stability problems. This study empirically examines the effect of wind generation on ERCOT system response characteristics following unit trips such as frequency drop, and phasor oscillation frequency and damping. It is shown with a high degree of certainty that an increase in wind generation is leading to a greater phasor oscillation frequency and lesser system inertia. Wind generation may also be leading to less system damping and smaller power frequency drops. / text

The wind energy industry in the U.S. has seen robust growth within the last two decades. The amount of renewable resources available throughout the U.S. is substantial, and as renewable energy penetration approaches a significant proportion of total electricity generation, grid operators and utilities will be presented with a myriad of challenges. Such is the case in wind’ rich Texas, where the rate of wind installations surpasses every other state and rivals that of China. By the end of 2009, the ERCOT region of Texas had approximately 9000 MW installed, serving 6.5% of the annual electricity load . The intermittent nature of wind energy can place a burden on existing generators as they are increasingly relied on to provide regulation of power, frequency control and back-up energy services when wind production is low. Exacerbating the difficulty of integrating wind energy is the mismatch of wind generation and electricity demand. Although Texas is blessed with plentiful wind resources, the majority of energy produced typically occurs at night when electricity demands are low. The result is transmission congestion that prevents cost effective generators from serving load. Despite these integration difficulties, ERCOT is paving the way forward with transformative infrastructure plans and proactive rulemaking. This report provides a background on the state of the wind energy industry in the U.S., with a review of power system operation strategies and wind integration best practices. With that context, this study concludes that ERCOT’s electricity market operations, transmission plans, and Texas’ renewable energy policies will act to reasonably and reliably accommodate wind generation capacity that serves over 15% of annual load by 2030. / text

Carbon dioxide (CO₂) capture and sequestration (CCS) at fossil-fueled power plants is a critical technology for CO₂ emissions mitigation during the transition to a sustainable energy system. Post-combustion amine scrubbing is a relatively mature CO₂ capture technology, but barriers to implementation include high capital costs and energy requirements that reduce net power output by 20-30%. Capture energy requirements are typically assumed constant, but work investigates whether flexibly operating amine scrubbing systems in response to electricity market conditions can add value to CO₂ capture facilities while maintaining environmental benefits. Two versatile optimization models have been created to study the electricity system implications of flexible CO₂ capture. One model assesses the value of flexible capture at a single facility in response to volatile electricity prices, while the other represents a full electricity system to study the ability of flexible capture to meet electricity demand and reliability (ancillary) service requirements. Price-responsive flexible CO₂ capture has limited value at market conditions that justify CO₂ capture investments. Solvent storage can add value for price arbitrage by allowing flexible operation without additional CO₂ emissions, but only with favorable capital costs. The primary advantage of flexible CO₂ capture is an increased ability to provide grid reliability services and improve grid resiliency at minimum and maximum electricity demand. Flexibility mitigates capacity shortages because capture energy requirements need not be replaced, and variable capture at low demand helps respond to intermittent renewable generation. / text

Large-scale electrochemical energy storage is a technology that is uniquely suited to integrate intermittent renewable energy sources with the electric grid on a large scale. Grid-based energy storage also has the potential to reduce costs associated with periods of peak electric demand. For these reasons, this work describes the potential applications for grid-based energy storage, and then reviews large-scale energy storage technology innovations since the development of the lead-acid battery. The potential value of grid-based battery energy storage is discussed in the context of restructured electricity markets; then, a dynamic model-based economic optimization routine is developed to gauge the potential value of a vanadium redox flow battery (VRFB) operating for wholesale energy arbitrage and frequency regulation in Texas. Based on this analysis, the relative value of a VRFB in various regions of Texas for energy arbitrage and frequency regulation is examined. It is shown that frequency regulation is an appealing application for a grid-based VRFB, with a VRFB utilized for frequency regulation service in Texas potentially worth approximately $1500/kW. Finally, the effect of a VRFB’s characteristics on its value for frequency regulation and energy arbitrage are compared, and the operational insight developed in this work is used to glean how policies to integrate a large-scale energy storage with the electricity market might be crafted. / text

As more renewable resources are added into the grid and environmental regulations are imposed to reduce emissions, there will be dramatic changes in the generation portfolio. Assessing the impact of these changes is important for policy makers, market participants, and general public to understand trends in the electricity market. This paper addresses this issue by analyzing how the ERCOT market is affected by CO2 penalty and wind penetration. In order to assess the future power system, the study model should represent the long term dynamics of various factors to find out how investment decisions are made economically in a competitive market with appropriate assumptions. Another important aspect is the short term market dynamics from real operation of power system. For this study, AURORAxmp, a commercially available market simulator, is utilized to capture both long term and short term dynamics. This study runs 5 different scenarios: two base cases with and without CO2 price, 20%, 27%, and 33% wind penetration level. The result shows that, increasing wind penetration reduces production and capacity of both coal and gas units, electricity market prices, and amount of emissions. However, increasing wind penetration has greater impacts on a decrease in generation from thermal units than reduction in thermal capacity, resulting in 11.4% capacity value of wind power. The study also confirms that CO2 price impacts capacity and generation of coal (negatively) and gas (positively) units in opposite ways, and reduces emission, but increases power prices and generation cost. Especially, the impact on retirement of coal units is noticeable. Almost half of the current coal capacity (19 GW), 9,390 MW, is retired by 2040 in this study. / text

In the Electric Reliability Council of Texas (ERCOT) compressed air energy storage (CAES) is currently viewed as the most promising energy storage technology due to Texas having suitable geology for CAES and few locations suitable for pumped-hydro storage. CAES is a proven technology but the economics for new facilities are uncertain. This work quantified the economic prospects for CAES in ERCOT as a function of installed wind capacity, natural gas price, and CAES capital cost. Two types of models were developed and used in this work. The first type of model was a CAES dispatch optimization model, which determined the maximum operating profits a CAES facility could earn given a set of electricity and ancillary services market prices. These models were used to examine several separate research questions relating to the maximum potential for CAES and the impact of uncertainty and other real-world complications. The models determined that the maximum operating profit from 2002-2010 varied widely from year to year and averaged $120-140/kW-year, which is likely below the operating profits required to justify investing in CAES. The models also determined that current price forecasting methods are sufficient to earn approximately 95% of the operating profits achievable with perfect knowledge of all prices in the year. The second type of model was a unit commitment model of ERCOT, which determined the least-cost operation of all the generators in the generation fleet to meet given load. The unit commitment model was used to determine electricity and ancillary service market prices under different assumptions about natural gas price, installed wind capacity, and installed CAES capacity. The CAES dispatch optimization model was then used to determine the operating profits of a CAES facility under these scenarios. CAES operating profits were found to increase with increasing natural gas price and installed wind capacity and to decrease with increasing installed CAES capacity. CAES operating profits were estimated to support installed CAES capacities from zero to more than 6 GW, depending on the natural gas price, installed wind capacity, installed CAES capacity, and the CAES capital costs. The strongest determinant of the maximum CAES capacity that would be profitable is the natural gas price, followed by the CAES capital costs. / text

Wind energy has dramatically changed the energy portfolio of Texas and more specifically, a region covering 75% of the state designated as ERCOT (Electric Reliability Council of Texas). Hardly existent at all ten years ago, the amount of capacity the wind farms provide is over 9000MW and accounts for 10% of the total generation. Due to the intermittent nature of wind and limitations of transmission lines, short and long term storage of this energy would benefit wind farms and the grid as a whole. This paper studies the relationship between wind, storage and real time electricity prices by analyzing prices and simulating a wind farm with different wind storage strategies over the course of a year. Based on these simulations, it is found that an ideal storage medium with no losses could be in the money for $17.50/kW for long term storage and $1,998/kW for short term storage for prices similar to 2009-2010. / text

This dissertation contains two essays on the analysis of market imperfections. In the first essay, I empirically test whether in a three-level hierarchy with asymmetries of information, more competition among intermediaries leads to more deception against the principal. In this setting, intermediaries supervise agents by delegation of the principal, and compete among themselves to provide supervision services to the agents. They cannot be perfectly monitored, therefore allowing them to manipulate supervision results in favor of the agents, and potentially leading to less than optimal outcomes for the principal. Using inspection-level data from the vehicular inspection program in Atlanta, I test for the existence of inspection deception (false positives), and whether this incidence is a function of the number of local competitors by station. I estimate the incidence of the most common form of false positives (clean piping) to be 9% of the passing inspections during the sample period. Moreover, the incidence of clean piping -- passing results of a different vehicle fraudulently applied to a failing vehicle -- per station increases by 0.7% with one more competitor within a 0.5 mile radius. These results are consistent with the presence of more competitors exacerbating the perverse incentives introduced by competition under this setting. In the second essay, we test whether electricity consumption by industrial and commercial customers responds to real-time prices after these firms sign-up for prices linked to the electricity wholesale market price. In principle, time-varying prices (TVP) can mitigate market power in wholesale markets and promote the integration of intermittent generation sources such as wind and solar power. However, little is known about the prevalence of TVP, especially in deregulated retail markets where customers can choose whether to adopt TVP, and how these firms change their consumption after signing up for this type of tariff. We study firm-level data on commercial and industrial customers in Texas, and estimate the magnitude of demand responsiveness using demand equations that consider the restrictions imposed by the microeconomic theory. We find a meaningful level of take-up of TVP ? in some sectors more than one-quarter of customers signed up for TVP. Nevertheless, the estimated price responsiveness of consumption is still small. Estimations by size and by type of industry show that own price elasticities are in most cases below 0.01 in absolute value. In the only cases that own price elasticities reach 0.02 in absolute value, the magnitude of demand response compared to the aggregate demand is negligible.

The Texas ERCOT market is one of the most open, deregulated electricity markets in the world. This open market brought electricity costs down for Texas residents and businesses, creating a much more competitive economic climate. However, these low prices currently generate insufficient revenue for generators to finance construction of new or replacement generation assets. In the instance of combined cycle advanced natural gas, the Independent Market Monitor 2012 annual report estimated that a plant needed to generate 2.5 times as much as revenue it did in 2012 to incent new generation. This author argues that while the gap is still significant, the continuous changes to the ERCOT market since its inception make an historical examination like that used by the IMM less accurate. New market rules such as price caps or changes in fuel markets through new technologies like hydraulic fracturing create a very different valuation gap than a model based on historical activity alone. This analysis attempts to get a more accurate approximation of the gap through the use of publicly traded futures contracts for natural gas and electricity. Electricity futures reflect market expectations of revenue based on current and future market rules. Gas futures reflect price expectations in light of market changes like fracturing, potential LNG exports, and other changes. Financial positions can be maintained in both markets to give a fixed rate of return. Using this method, one can create a very conservative valuation model that still more accurately reflects market sentiment. This thesis starts with a brief history of ERCOT deregulation from the early 2000s to present in order to clarify for the reader the changes that have taken place in the market. It then demonstrates the futures-valuation model using an advanced combined cycle power plant as an example. / text