Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm

The design of energy systems is very important in order to reduce operating costs and guarantee the reliability a system. This paper proposes new algorithm solve problem optimal multi-objective redundancy series-parallel power systems. chosen based on hybridization two metaheuristics, which are bat (BA) generalized evolutionary walk (GEWA), also called BAG (bat with flight). approach combined Ushakov method, universal moment generating function (UMGF), evaluate multi-state aims minimize cost, maximize performance electric generation system from solar gas generators by taking into account indices. Power subsystem devices labeled according their reliabilities, performances. Reliability hangs an operational system, implies likewise satisfying customer demand, so it depends amassed batch curve. Two different allocation problems, commonly found planning, solved show algorithm. first bi-objective formulation that corresponds minimization investment cost maximization availability. In second, seeks availability, capacity