Enhancing electricity auction mechanism with FACTS devices

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2000
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Wu, Hao
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Sheblé, Gerald B.
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Abstract
In the U.S., the electrical industry has consisted of state-regulated vertically integrated monopolies for a long time. The results of monopolistic operation are high electricity price and low output level, which brings deadweight loss to the social welfare. In order to eliminate the deadweight and achieve high efficiency, the restructuring, i.e., deregulation, is an inevitable trend in the electrical industry. In the deregulated electric power market, auction is demonstrated to be an effective way to achieve the Pareto optimality. The auction scheme in this work is double-sided SPCA (single period commodity auction). The auction problem is formulated in a linear form and can be solved by LP (linear programming). Recent advances in the power electronics field bring the FACTS (flexible AC transmission system) devices and HVDC (high voltage DC) transmission to the power system. These devices are the power electronics based fast switching power flow controller. They have the ability to enhance the system controllability, capacity and stability. This work constructs linearized models for UPFC (unified power flow controller) and two-terminal HVDC link. This model can be easily incorporated into the SPCA formulation without losing much accuracy. The control parameters of FACTS devices and HVDC link are introduced to the formulation as new state variables. The test result shows the power flow solution with UPFC can converge in four to six iterations. The using of UPFC can enhance the trading surplus in the power auction market. This work also introduces a LP algorithm to solve the power auction problem with contingency. The expected remedial action cost (ERAC) for the contingencies cannot be known before getting the result of power auction. Thus, the ERAC cannot be formulated explicitly in the objective function of the power auction problem. The LP algorithm solves an optimal remedial action sub-problem after each LP iteration of the power auction problem. The ERAC is returned from the sub-problem and used to update the reduced cost coefficients (RCCs) in the main problem. The simplex pivot maybe changed after this updating. Thus, the global optimality of the power auction problem with the consideration of contingency can be gotten using this algorithm.
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