Energy Flow Management and Size Optimization for Photo-Voltaic and Wind Renewable Sources Integrated with Vehicle-to-Grid Technology

Abstract

The energy management process can increase the reliability of the energy flow to cover the load in a Hybrid Renewable Energy System (HRES), especially in light of the development of new technologies such as Vehicle-to-Grid (V2G) technology that helps the grid handle with peak load coverage. This paper deals with a connected hybrid system With the grid is used to operate a residential building in the Sabha region in southern Libya, as it consists of photovoltaic (PV) with a capacity of (112.8) KW, wind turbines (WT) generating (24) KW, batteries (BT) up to (63) KW, and electric vehicles (67) KW, with an investment of (513,432) thousand dollars. The proposed system generates (2338) Mw/h/year, which is sufficient to meet (54.76) % of the demand for electricity from renewable energy sources. It also generates surplus energy at a value of (0.91) Mw/h/year, meaning that the deficit in meeting energy demand is negligible. The system is designed to reduce the Levelized Cost of Energy (LCOE) and Loss of Power Supply Probability (LPSP) while increasing the Renewable Energy Fraction (REF) by implementing an energy management optimization strategy through search algorithms such as the Cuckoo search algorithm (CSA) and Particle swarm optimization (PSO) for component size. Hybrid renewable energy system, taking into account climatic data as well as objective functions and Constraints. The energy balance between system components is analyzed to obtain the best performance at the lowest operating cost. The system was set up using MATLAB codes in different configurations, and the obtained results show better performance values such as (0.0340) $/KWh, (0.0769)%, and (0.5476)% for COE, LPSP, and REF, respectively.