Multiyear transmission expansion planning using discrete evolutionary particle swarm optimization

Abstract

The objective of Transmission Expansion Planning (TEP) is to obtain a plan to expand or reinforce a transmission network that minimizes construction and operational costs while satisfying the requirement of delivering electricity safely and reliably to load centres along the planning horizon. This definition is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. The objective of this paper is the introduction of a new discrete approach to solve dynamic TEP, based on an improved version of the Evolutionary Particle Swarm Optimization (EPSO) meta-heuristic algorithm. The paper includes sections describing the Discrete EPSO (DEPSO), an enhanced approach of EPSO, the mathematical formulation of the problem, including the objective function and constraints, and the application of DEPSO to this problem. Finally, the use of the developed approach is illustrated using Case Studies based on the Garver network and on the IEEE 24 bus / 38 branch test system.