Energy management of the hybrid power system based on improved intelligent Perturb and Observe control using battery storage systems

Abstract

With the increase in demand for electrical energy, renewable energy systems have become unable to meet this demand, especially in difficult weather conditions, so hybrid energy systems (HESs) have been resorted to as a suitable solution. These HESs require special control to manage energy. In this work, an HES consisting of a diesel generator system, an energy storage system, and a photovoltaic (PV) system will be implemented to solve the problem of the inability to provide electrical energy in special weather conditions. The proposed system is of great importance in the industrial and economic field because it provides a suitable solution to compensate for excess demand with the possibility of storing excess energy and using it at critical times. In this work, an efficient energy management algorithm (EMA) is designed for this HES to obtain significant energy from the sun, protect the battery, store excess energy, prevent power shortages in the grid, and use the diesel generator at critical times. The first contribution of this paper lies in improving the effectiveness of the Perturb and Observe (P&O) for maximum power point tracking using fuzzy logic control (FLC), as the proposed strategy contributes significantly to obtaining the maximum energy from the PV system and greatly increasing its durability. The energy stored in the batteries is harnessed to extend the diesel “off” time to avoid any possible problems. The proposed EMA is effective in organizing work between the various parts of the proposed HES. The latter was implemented in the Matlab environment with the completion of a comparative study between the classical P&O technique and P&O based on FLC technique, as these suggested solutions proved their effectiveness and significantly improved the reliability of the system in the face of climate change and increased load demand.