Multi-Objective Genetic Algorithm Optimal Planning and Scheduling of Hybrid Energy System Connected to the Egyptian Grid

The stricter environmental regulation and fossil-fuel shortage, result in growing interest in using renewable energy as alternative sources of energy. These alternative sources are environmentally friendly. However, its capital investments are normally high. Furthermore, due to the intermittent of these sources by natural, reliability issues should be addressed when integrating different power sources. In this article, the author has presented, a grid-connected hybrid energy system (HES) comprising photovoltaic module (PV), wind turbine (WT), fuel cell (FC), electrolyzer, diesel generator (DG), hydrogen tank (HT) and battery system. Considering the complexity of this HES a multi-objective genetic algorithm (MOGA) is applied to solve the optimal planning and scheduling of hybrid energy system components taking into consideration the load requirements in a reliable manner and selling the excess energy to the main grid. The main objective of the optimal planning process is to minimize the cost of electricity (COE) and CO2 emission simultaneously with zero load rejection. A case study proposed hybrid energy system loads are some residential buildings (one block) in New Assiut City, Egypt with a peak value of 160.2 kW and yearly energy of 430 MWh. A simulation code of the planning and scheduling problem is developed using MATLAB software package to solve the optimization problem. An optimal planning is obtained with a lifetime of 20 years. A comparison between different configuration of HES is done. Results indicated that incorporating diesel generator with HES increase system reliability and provide a further reduction in COE. The grid-connected HES is highly beneficial for the block since it reduces long term cost of electricity generation ($/kWh) while at the same time it is supporting their energy consumption with cleaner, renewable energy sources. The results also showed that HES comprising PV/WT/battery/diesel choice is more feasible economically and less CO2 emission than other configurations. Further, it is contributing to reduce the load size of the utility grid.