A Decentralized Optimization for Risk Based Regional Congestion Management

Fu Rong, Ge Zhao-qiang, Li Yang, Tang Guo-qing


A new decentralized risk-based congestion management method is proposed, in which theobject function is represented by utility value in electricity market. Centralized optimizationapproaches are primarily employed in congestion management study , however, decentralizedoptimizations are used to make decisions in real regional markets. In this paper, participants indifferent regions are allowed to pursue their own profits and utility functions are defined to synthesizethe profit and the congestion risk. The system operator with more priority coordinates the relationsbetween the decentralized schemes. It is evident that the decentralized scheme is more realistic inregional market management. Congestion management with thermal rating risk assessment willcoordinate the security and efficiency of transmission network and obey the rules of market operation.The utility function is based on Optimal Power Flow (OPF) coupled with short-term transmissionline thermal overload r1isk assessment. Simulation tests on IEEE 30-bus system demonstrate thatthe predicted risk of thermal overload is useful for online decision making and the decentralizedrisk based congestion management approach is transparent and efficient to the market participants.

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