Optimal size and cost analysis of stand-alone hybrid wind/photovoltaic power-generation systems

Design of sustainable energy systems for the supply of electricity need correct selection and sizing to reduce investment costs. In this article, a new sizing methodology is developed for stand-alone hybrid wind/photovoltaic (PV) power systems, using multi-objective optimisation algorithms. Multi-objective particle swarm optimisation algorithm and non-dominated sorting genetic algorithm-II are selected related to their match with the nature of renewable energy sizing problem. A match evaluation method is developed based on renewable energy supply/demand match evaluation criteria, to size the proposed system in the lowest cost. As an example of application of this technique, six different wind turbines (WTs) and also six different PV modules have been considered. The sizing methodology determines a multi-objective design, obtaining the best solutions that the applied algorithm has found simultaneously considering three objectives: inequality coefficient, correlation coefficient, and annualised cost of system. The optimal number of WTs, PV modules, and batteries ensuring that the system total cost is minimised while guaranteeing a highly reliable source of load power is obtained. A management strategy has been designed to achieve higher electricity match rate. Based on the proposed technique, the algorithm developed for different cases, using the climatic condition data of the city Zabol, located in south-east of Iran. Additionally, a study of operating hours of diesel generator in optimal configuration is carried out.