Optimal Sizing and Economical Analysis of PV-Wind Hybrid Power System for Water Irrigation using Genetic Algorithm

In the present study three renewable power systems are proposed to select the most optimum one for powering an irrigation pumping system and a farmer’s house in two different locations in Sinai, Egypt. Abu-Rudies in south Sinai and El-Arish in north Sinai are the two selected locations. The three suggested power systems are; standalone photovoltaic (PV) system, standalone wind system and standalone PV-wind hybrid system. HOGA (Hybrid Optimization by Genetic Algorithms) simulation software tool based on genetic algorithm (GA) is used for sizing, optimization and economical evaluation of three suggested renewable power systems. Optimization of the powersystem is based on the components sizing and the operational strategy.  The calculated maximum amount of water required for irrigating ten acres of olive per day is 170 m3. In terms of cost effectiveness, the optimal configurations are the hybrid PV-wind system and the standalone PV system for Abu-Rudies and El-Arish locations respectively. These systems are the most suitable than the others for the selected sites metrological data and the suggested electrical loa

Comparison between P&O and SSO techniques based MPPT algorithm for photovoltaic systems

Solar photovoltaic (SPV) systems are a renewable source of energy that are environmentally friendly and recyclable nature. When the solar panel is connected directly to the load, the power delivered to the load is not the optimal power. It is therefore important to obtain maximum power from SPV systems for enhancing efficiency. Various maximum power point tracking (MPPT) techniques of SPV systems were proposed. Traditional MPPT techniques are commonly limited to uniform weather conditions. This paper presents a study of MPPT for photovoltaic (PV) systems. The study includes a discussion of different MPPT techniques and performs comparison for the performance of the two MPPT techniques, the P&O algorithm, and salp swarm optimization (SSO) algorithm. MATLAB simulations are performed under step changes in irradiation. The results of SSO show that the search time of maximum power point (MPP) is significantly decreased and the MPP is obtained in the shortest time with high accuracy and minimum oscillations in the generated power when compared with P&O