A decentralized optimization for risk based regional congestion management

A new decentralized risk-based congestion management method is proposed, in which the object function is represented by utility value in electricity market. Centralized optimization approaches are primarily employed in congestion management study, however, decentralized optimizations are used to make decisions in real regional markets. In this paper, participants in different regions are allowed to pursue their own profits and utility functions are defined to synthesize the profit and the congestion risk. The system operator with more priority coordinates the relations between the decentralized schemes. It is evident that the decentralized scheme is more realistic in regional market management. Congestion management with thermal rating risk assessment will coordinate 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 transmission line thermal overload risk assessment. Simulation tests on IEEE 30-bus system demonstrate that the predicted risk of thermal overload is useful for online decision making and the decentralized risk based congestion management approach is transparent and efficient to the market participants.