A Bi-Level Evolutionary Optimization for Coordinated Transmission Expansion Planning

Abstract

In this paper, a real-life application of bi-level evolutionary optimization is proposed to optimize the electricity industry infrastructure. It offers a coordinated generation and transmission expansion planning (CGTEP) from the perspective of an independent system operator (ISO). The main objective of the proposed study is to show the effect of optimizing the generators concerning capacity and location both to reduce the transmission investment and increasing the reliability of the network. The proposed framework of bi-level optimization contributes to utilize global evolutionary optimization method GA in its hybrid form in level-I to select the location of lines and energy generators. The respective capacities of the corresponding selected lines and generators are optimized in the level-II by RW. In conflicting objectives of minimizing the investment for capacity addition in the network and maximizing the reliability, a Pareto-optimal solution is achieved by using the theory of marginal value (TMV). To satisfy TMV, the total cost is minimized, which comprises the cost of investment in building new transmission and generation capacities, cost of not-served expected energy, cost of unutilized expected generation, and cost of unserved energy due to the constrained network. Proposed methodology on IEEE 24-bus power system is presented encountering the combination of N-1 and probable N-2 contingency security criteria. The comparison results show that bi-level GA-RW optimization minimizes the investment with increasing power system reliability.