Browsing by Subject "economic dispatch"
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Item A Framework for Analyzing the Impact of Data Integrity/Quality on Electricity Market Operations(2014-02-21) Choi, DaeThis dissertation examines the impact of data integrity/quality in the supervisory control and data acquisition (SCADA) system on real-time locational marginal price (LMP) in electricity market operations. Measurement noise and/or manipulated sensor errors in a SCADA system may mislead system operators about real- time conditions in a power system, which, in turn, may impact the price signals in real-time power markets. This dissertation serves as a first attempt to analytically investigate the impact of bad/malicious data on electric power market operations. In future power system operations, which will probably involve many more sensors, the impact of sensor data integrity/quality on grid operations will become increasingly important. The first part of this dissertation studies from a market participant?s perspective a new class of malicious data attacks on state estimation, which subsequently influences the result of the newly emerging look-ahead dispatch models in the real-time power market. In comparison with prior work of cyber-attack on static dispatch where no inter-temporal ramping constraint is considered, we propose a novel attack strategy, named ramp-induced data (RID) attack, with which the attacker can manipulate the limits of ramp constraints of generators in look-ahead dispatch. It is demonstrated that the proposed attack can lead to financial profits via malicious capacity withholding of selected generators, while being undetected by the existing bad data detection algorithm embedded in today?s state estimation software. In the second part, we investigate from a system operator?s perspective the sensitivity of locational marginal price (LMP) with respect to data corruption-induced state estimation error in real-time power market. Two data corruption scenarios are considered, in which corrupted continuous data (e.g., the power injection/flow and voltage magnitude) falsify power flow estimate whereas corrupted discrete data (e.g., the on/off status of a circuit breaker) do network topology estimate, thus leading to the distortion of LMP. We present an analytical framework to quantify real-time LMP sensitivity subject to continuous and discrete data corruption via state estimation. The proposed framework offers system operators an analytical tool to identify economically sensitive buses and transmission lines to data corruption as well as find sensors that impact LMP changes significantly. This dissertation serves as a first step towards rigorous understanding of the fundamental coupling among cyber, physical and economical layers of operations in future smart grid.Item Decomposition algorithms for multi-area power system analysis(Texas A&M University, 2007-09-17) Min, LiangA power system with multiple interconnected areas needs to be operated coordinately for the purposes of the system reliability and economic operation, although each area has its own ISO under the market environment. In consolidation of different areas under a common grid coordinator, analysis of a power system becomes more computationally demanding. Furthermore, the analysis becomes more challenging because each area cannot obtain the network operating or economic data of other areas. This dissertation investigates decomposition algorithms for multi-area power system transfer capability analysis and economic dispatch analysis. All of the proposed algorithms assume that areas do not share their network operating and economic information among themselves, while they are willing to cooperate via a central coordinator for system wide analyses. The first proposed algorithm is based on power transfer distribution factors (PTDFs). A quadratic approximation, developed for the nonlinear PTDFs, is used to update tie-line power flows calculated by Repeated Power Flow (RPF). These tie-line power flows are then treated as injections in the TTC calculation of each area, as the central entity coordinates these results to determine the final system-wide TTC value. The second proposed algorithm is based on REI-type network equivalents. It uses the Continuation Power Flow (CPF) as the computational tool and, thus, the problem of voltage stability is considered in TTC studies. Each area uses REI equivalents of external areas to compute its TTC via the CPF. The choice and updating procedure for the continuation parameter employed by the CPF is implemented in a distributed but coordinated manner. The third proposed algorithm is based on inexact penalty functions. The traditional OPF is treated as the optimization problems with global variables. Quadratic penalty functions are used to relax the compatible constraints between the global variables and the local variables. The solution is proposed to be implemented by using a two-level computational architecture. All of the proposed algorithms are verified by numerical comparisons between the integrated and proposed decomposition algorithms. The proposed algorithms lead to potential gains in the computational efficiency with limited data exchanges among areas.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.