Sizing of a standalone photovoltaic water pumping system using a multi-objective evolutionary algorithm

In this paper, a differential evolution based multi-objective optimization algorithm is proposed to optimally size a photovoltaic water pumping system (PVPS). Non-dominated sorting and crowding distance concepts are used to increase the elitism and diversity of the proposed algorithm. The proposed objective function is composed of technical and economic objectives. Loss of load probability is used as a technical objective, whereas life cycle cost is considered as an economic objective. The proposed PVPS is designed to provide a daily water demand of 30 m3 with a 20 m static head and a drawdown level. The optimal configuration of the system is selected from an optimal Pareto set of configurations to achieve balance between reliability, cost, and excess water of the system. The performance of the system is tested using hourly metorological data for one year time. Results show that the loss of load probability of the proposed system is around 0.5%. The life cycle cost, water deficit, and cost of water unit of the system are 9910 USD, 55 m3, and 0.045 USD/m3, respectively.