Optimal Sizing and Techno-Economic Feasibility of A Hybrid Energy System for Rural Electrification in Nakwamoru Village, Kenya

¹ Pan African University-Institute of Water and Energy Sciences –including Climate Change (PAUWES), Tlemcen, Algeria.
² Department of Mechanical Engineering, Covenant University, Ota, Ogun State
³ The Energy and Environment Research Group (TEERG), Mechanical Engineering Department, Covenant University, Ogun State, Nigeria.
⁴ Faculty of Engineering & the Built Environment, University of Johannesburg, South Africa.

Abstract

Integration of renewable energy sources has been found to be the best alternative for rural electrification. Kenya has made significant efforts in the energy sector, having electricity access at 75 % electricity via the grid or off-grid sources. However, it is still evident that citizens mostly depend upon biomass for energy use, especially those living in rural areas that are not grid-connected. With the Rural Electrification and Renewable Energy Corporation (REREC), Kenya's ambition is to increase the rural electrification rate to 40 % by 2024, through rapid deployment of solar PV mini-grid systems. This study optimally sizes and analyses the techno-economic feasibility of various configurations of hybrid systems for Nakwamoru Village comprising 522 households. An energy optimization tool (HOMER Pro) was adopted for the sizing, simulation, optimization, and techno-economic evaluation. The analysis indicates that the most optimal hybrid system configuration consists of 174 kW of PV panels, 314 batteries, and 65 kW of converter, to meet the daily electric load. The solar PV-battery power system will generate annual electricity of 276,142 kWh/yr, and the community AC loads will consume 190,520 kWh/yr of electricity. The optimal hybrid power system has a COE of $ 0.166/kWh and an NPC of $ 474,456. The COE obtained is 17% lower than the current LCOE ($ 0.20/kWh) for residential tariffs in Kenya. Sensitivity analysis was performed to assess the possible solar radiation and inflation rates on the optimal system configurations. The results indicate that an increase in solar radiation will reduce both the COE and NPC, whereas an increase in inflation will increase the NPV while reducing the COE.