Application and Comparison of Metaheuristic Techniques to Generation Expansion Planning Incorporating Both Bilateral and Multilateral Transactions

Abstract

In restructured environment, various transactions such as firm bilateral and multilateral transactions are taking place. An analysis is made on effects of transactions on Generation Expansion Planning (GEP). Some of the metaheuristic techniques such as Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), Evolutionary Strategy (ES), Particle Swarm Optimization (PSO), Tabu Search (TS), Simulated Annealing (SA), and Hybrid Approach (HA) are applied to solve the Transactions-GEP problem with the support of AC-Optimal Power Flow (OPF) for the modified IEEE-30 bus test system with 6-years planning horizon. The original GEP problem is modified using the proposed methods i) Virtual Mapping Procedure (VMP), and ii) Penalty Factor Approach (PFA), to improve the effectiveness of the Metaheuristic techniques. Further, Intelligent Initial Population Generation (IIPG) and 'Store and Retrieve approach' are introduced in the solution techniques to reduce the computational time. PFA is used to convert the constrained problem into an unconstrained one. The results of the metaheuristic techniques are compared and validated with that of Dynamic Programming (DP). The performances of each metaheuristic technique were compared in terms of their Success Rate (SR), Average Number of Generations (ANG), the error percentage and the mean execution time. The effects of various transactions on GEP are also analyzed.