Optimal Sizing of Hybrid Wind/PV/Diesel Generation in a Stand-Alone Power System Using Markov-Based Genetic Algorithm

Abstract

Owing to the Kyoto Protocol and the growing depletion of natural resources, renewable energies have attracted much attention. This paper considers 25-kW wind-turbine generator, 5-kW PV and 30-kW diesel generator as unit sizes for generation planning in a stand-alone power system. The investment cost (installation and unit costs) and fuel cost are minimized while retaining the reliability requirement and CO emission limit. First, the fuzzy-c-means (FCM) is employed to cluster the operation states for system load, wind-turbine generations (WTG), and PV in 8760 h. Then, the Markov models for the system load, WTG, and photovoltaic (PV) are established. The Markov models are embedded into the genetic algorithm to determine the optimal sizes for WTG, PV, and the diesel generator. The simulation results reveal that computation time can be reduced greatly while optimality can be still retained, compared with the traditional method using chronological data.