Pareto optimality-based multi-objective transmission planning considering transmission congestion

In the deregulated environment, transmission congestion is one major problem that needs to be handled in power system operation and network expansion planning. This paper aims to enhance the transmission system capability and have the congestion alleviated using the multi-objective transmission expansion planning (MOTEP) approach. A system congestion index called the congestion surplus is presented to measure the congestion degree of the transmission system. The proposed MOTEP approach optimizes three objectives simultaneously, namely the congestion surplus, investment cost and power outage cost. An improved strength Pareto evolutionary algorithm (SPEA) is adopted to solve the proposed model. A ranking method based on Euclidean distance is presented for decision-making in the Pareto-optimal set. The effectiveness of both the improved SPEA and the proposed multi-objective planning approach has been tested and proven on the 18-bus system and the 77-bus system, respectively.