Optimal planning and electricity sharing strategy of hybrid energy system for remote communities in Nigeria

In recent times, renewable energy-based power systems are being used to address energy poverty or shortage that is experienced in developing countries. To improve these systems’ applicability, they are used to design a hybrid energy system. It is against this backdrop that this paper focuses on how hybrid energy systems can be designed optimally to address electricity sharing between domestic and productive use in remote communities. This paper, therefore, proposes a mixed-integer multi-objective optimization model for electricity sharing between domestic and productive use in remote communities. The model considered the number of solar photovoltaic (PV) systems acquisition, the total cost of energy utilized, and the cost of CO2 emissions avoided. A genetic algorithm was used to optimize these decision variables. The proposed model evaluation was carried out using data from three remote communities in South-West Nigeria. The results obtained from the model show that the number of installed solar PV systems in the first, second, and third communities is 74, 76 and 73 solar PV systems, respectively. For 25 years planning period, the first community required 29,554.05 kWh, the second community required 28,280.20 kWh, and the third community required 28,608.70 kWh. The average values for productive use of electricity from the conventional energy sources for the first community was 0.358, for the second community was 0.338, and for the third community was 0.348. In terms of the maximum productive use of electricity from the solar PV system, the first and second communities had the same value (0.39), while the third community's maximum had a value of 0.40. The developed model will be useful for evaluating the expected number of functional solar PV systems required, managing the quantity of electricity supply from the national grid and the generators, and planning electricity sharing for domestic and productive use within the selected communities.