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Performance comparison of heuristic optimization methods for optimal dynamic transmission expansion planning

Abstract:

Modern heuristic optimization algorithms have gained considerable attention in different research fields due to their conceptual simplicity and their ability to deal with different complex optimization problems. Motivated by promising results from the application of these emerging tools on other power system optimization problems, this paper presents a comparative study on the capabilities of three heuristic optimization algorithms for solving the problem of optimal dynamic centralized transmission expansion planning (CTEP). Among the studied algorithms are: Evolutionary particle swarm optimization, differential evolution, and a newly developed tool named mean-variance mapping optimization. Considering a predefined indicative generation expansion plan, which is usually contemplated in regulations for the power system planning in most Latin American countries, modified versions of the well-known Garver's system and the IEEE-118 bus multi-area system are used to evaluate the performance of each algorithm for solving the dynamic CTEP with a medium-term planning horizon of 10 years.