Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization

Abstract

Nowadays, Renewable Energy System (RES) like Photovoltaic (PV) widely used to increase energy generation. Solar PV installation as a Distributed Generation (DG) on the utility scale is commercially feasible, particularly for residential applications. This energy available abundantly and considered clean energy that harnessed and transformed the radiant light energy generated by the sun into electric current. However, the best use of solar energy has been prevented by nature or weather mismatches between. the maximum of solar PV generation and usual residential load. In residential, the PV output is not fully utilized when the load is at the minimum (off-peak load). The wastage of power occurs due to PV excess generation during off peak load and causes an increase in the cost of electricity consumption. To optimize load demands and power flow in the connected grid, RES need to be scheduled. The Battery Energy Storage System (BESS) stores the excess power generated in peak hours and returns it to the system when there is not enough PV. While the energy management system (EMS) is required in operating renewable energy sources connected to a grid to ensure the renewable energy power is fully utilized. Therefore, this project to design the EMS strategy for the network that cooperating PV and BESS. This focused on PV modelling for improved EMS and the designation of storage devices. Optimize the PV size as well to reduce power consumption from the main grid. In this project, MATLAB Software was used to implement the Particle Swarm Optimization (PSO) technique. BESS capacity and PV size are acquired in accordance with the energy dispatch stored in the BESS. This strategy can reduce grid power generation by implementing EMS in the operation of existing residential PV with BESS.