Browsing by Subject "electricity market"
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Item Essays in Competition and Investment in Electricity Market(2014-11-07) Tang, XinMany jurisdiction has opened retail electricity markets to competition. In Texas, retailers offer hundreds of electricity plans with different prices. The first paper uses search cost and product differentiation to explain the price dispersion using only data on price. If search costs are present, the search burden can lead to market inefficiency. If product differentiation is the main cause of price dispersion, the market competition can increases consumer welfare. The model improves the current sequential search model by taking product differentiation into consideration. The results show that both product differentiation and search cost result in price dispersion. Product differentiation explains about 55% of the price dispersion. The magnitude of search costs is large and the counter-factual experiment shows that reduced search cost could reduce both market average price and price dispersion. The second paper uses a dynamic investment model to tackle three critical issues in renewable energy in the electricity industry. First, current renewable energy policies do not differentiate the carbon intensity of nonrenewable resources, which makes them less cost effective in reducing the carbon emission. Second, when making investment decisions, power plants take uncertainties into consideration. Lastly, the electricity generation market is unique that the players in the market not only compete in the hourly spot market but also compete with long-term investment strategies. A dynamic investment model considers all three issues simultaneously by simulating both short term and long term firm behavior under different market design parameter settings.Item Intelligent Economic Alarm Processor (IEAP)(2013-08-06) Guan, YufanThe advent of electricity market deregulation has placed great emphasis on the availability of information, the analysis of this information, and the subsequent decision-making to optimize system operation in a competitive environment. This creates a need for better ways of correlating the market activity with the physical grid operating states in real time and sharing such information among market participants. Choices of command and control actions may result in different financial consequences for market participants and severely impact their profits. This work provides a solution, the Intelligent Economic Alarm Processor to be implemented in a control center to assist the grid operator in rapidly identifying the faulted sections and market operation management. The task of fault section estimation is difficult when multiple faults, failures of protection devices, and false data are involved. A Fuzzy Reasoning Petri-nets approach has been proposed to tackle the complexities. In this approach, the fuzzy reasoning starting from protection system status data and ending with estimation of faulted power system section is formulated by Petri-nets. The reasoning process is implemented by matrix operations. Next, in order to better feed the FRPN model with more accurate inputs, the failure rates of the protections devices are analyzed. A new approach to assess the circuit breaker?s life cycle or deterioration stages using its control circuit data is introduced. Unlike the traditional ?mean time? criteria, the deterioration stages have been mathematically defined by setting up the limits of various performance indices. The model can be automatically updated as the new real-time condition-based data become available to assess the CB?s operation performance using probability distributions. The economic alarm processor module is discussed in the end. This processor firstly analyzes the fault severity based on the information retrieved from the fault section estimation module, and gives the changes in the LMPs, total generation cost, congestion revenue etc. with electricity market schedules and trends. Then some suggested restorative actions are given to optimize the overall system benefit. When market participants receive such information in advance, they make estimation about the system operator's restorative action and their competitors' reaction to it.Item Risk Aware Robust Decision Making in Power Systems with Renewable Resources(2014-10-29) Thatte, Anupam AjitThe increasing penetration of renewable generation poses significant risks to the reliable operation of power systems, mainly due to the variable and uncertain nature of the output of wind and solar resources. This dissertation presents a robust optimization based decision making framework in future power systems with high penetration of variable renewable resources. The first part of this dissertation involves the modeling and analysis of a robust optimization based bidding strategy for the combination of a wind farm and an energy storage device participating in a deregulated electricity market. The selection of the uncertainty set for the robust optimization problem, based on the decision maker?s risk preference, is also discussed. From the market participant?s point of view improved utilization of the renewable resource, through storage enabled energy arbitrage, can lead to better economic performance. The storage device can provide firming power to the output of the wind farm, enabling the renewable resource to participate in the electricity market. The robust optimization based approach is compared to a deterministic optimization based approach through a numerical example. The second part of this dissertation investigates the metric and the dispatch method needed for a more robust real-time market operation. A novel metric for evaluating system-wide ramp flexibility is proposed. A robust framework to ensure the reliable dispatch of generators is presented and analyzed. The robust model is compared to both the conventional economic dispatch as well as a proposed industry approach to managing system flexibility called the look-ahead dispatch. Furthermore, the formulation for a robust multi-zonal dispatch model is presented. The proposed robust model and flexibility index is demonstrated through a numerical on a modified IEEE 24 Bus Reliability Test System.