Optimal transmission expansion planning using Mean-Variance Mapping Optimization

Abstract

The optimization problem in transmission system expansion planning (TSEP) is a mixed-integer nonlinear programming problem of combinatorial nature that leads to an extremely large number of alternative solutions for medium and large size electric power systems. Due to its complex characteristics, heuristic optimization has become an effective solver. In this paper, a novel heuristic optimization algorithm, namely the Mean-Variance Mapping Optimization (MVMO), is adapted to handle the TSEP. Additionally, a variant of MVMO termed as collaborative MVMO (CMVMO) is introduced. CMVMO exploits multicore technology of modern computers as well as distributed computing to enhance the performance of the former MVMO. Several tests were performed on three benchmark systems with different mesh complexity in their topologies in order to compare the performance of both, MVMO and CMVMO, with other evolutionary algorithms. Simulation results show that CMVMO constitutes a powerful algorithm and should earn more attention.