Optimization and Cost Analysis of an Off-Grid Hybrid Power System for Rural Electrification: A Case Study of Pawi District, Ethiopia

Abstract

Hybrid power systems have become one of the most fascinating and exciting fields in the research industry due to the reliability and efficiency of power systems. Off-grid and grid connected hybrid power system optimizations are designed for the electrification of rural areas. The main objectives of this study are designing and optimizing of an off-grid hybrid power system rural electrification for Ketena 1 Mender 127, which is located in Ethiopia. In the study, Four combinations of hybrid energy systems are performed and designed. To meet the region’s load demand, the study includes a photovoltaic system (PV), wind turbines (WT), diesel generators (DG) and battery energy storage systems (BESS). For the optimization of hybrid renewable energy system (HRES), HOMER software and Genetic Algorithm (GA) approaches are proposed and based on their cost expense and unmet load, the comparison tests are conducted. The optimal size of the hybrid power system is determined through minimization of the cost of energy (COE), total net present cost (NPC) while satisfying constraints. According to the results, the proposed GA outperforms higher efficiency, lower COE, NPC and unmet load than HOMER software.

Keywords

• Optimal size
• HOMER software
• Hybrid energy system
• Genetic algorithm

References

1. [1] B. Debebe, F. Senbeta, D. Diriba, E. Teferi, and D. Teketay, “Determinants of household energy choice for domestic chores : Evidence from the Semien Mountains National Park and Adjacent Districts , Northwest Ethiopia,” Clean. Energy Syst., vol. 4, no. March, p. 100063, 2023, doi: 10.1016/j.cles.2023.100063.
2. [2] A. Hossain and C. Ringler, “Optimization and cost-bene fi t assessment of hybrid power systems for off-grid rural electri fi cation in Ethiopia,” vol. 177, pp. 234–246, 2019, doi: 10.1016/j.energy.2019.04.095.
3. [3] A. Terefe, H. Long, and J. Li, “Electrifying rural Ethiopia : Boosting nonfarm enterprises and income through household electricity access,” Energy Policy, vol. 209, no. PB, p. 114992, 2026, doi: 10.1016/j.enpol.2025.114992.
4. [4] S. Yadav, P. Kumar, and A. Kumar, “Hybrid renewable energy systems design and techno-economic analysis for isolated rural microgrid using HOMER,” Energy, vol. 327, no. May, p. 136442, 2025, doi: 10.1016/j.energy.2025.136442.
5. [5] B. Te, B. Assefa, and G. Assefa, “Assessing the life cycle environmental impacts of hydroelectric generation in,” vol. 41, no. February, 2020, doi: 10.1016/j.seta.2020.100795.
6. [6] M. Kamal, I. Asharaf, and E. Fernandez, “Optimal renewable integrated rural energy planning for sustainable energy development,” Sustain. Energy Technol. Assessments, vol. 53, no. PB, p. 102581, 2022, doi: 10.1016/j.seta.2022.102581.
7. [7] H. Laryea and A. Schiffauerova, “A novel standalone hybrid renewable energy systems onboard conventional and autonomous tugboats,” Energy, vol. 303, no. December 2023, p. 131948, 2024, doi: 10.1016/j.energy.2024.131948.
8. [8] B. Modu, P. Abdullah, A. Lawan, and M. Fatihu, “Energy management and capacity planning of photovoltaic-wind-biomass energy system considering hydrogen-battery storage,” J. Energy Storage, vol. 73, no. PD, p. 109294, 2023, doi: 10.1016/j.est.2023.109294.

9. [9] V. Suresh, M. Muralidhar, and R. Kiranmayi, “Modelling and optimization of an off-grid hybrid renewable energy system for electrification in a rural areas,” Energy Reports, vol. 6, pp. 594–604, 2020, doi: 10.1016/j.egyr.2020.01.013.
10. [10] O. Arouna et al., “Technical-ecological optimization of the operation of a multi-source electrical system injecting into a distribution network using HOMER software and genetic algorithms,” 2020 IEEE PES/IAS PowerAfrica, PowerAfrica 2020, 2020, doi: 10.1109/PowerAfrica49420.2020.9219833.
11. [11] M. R. Islam, M. M. Uddin, M. F. Hassen Bablo, and M. A. Uddin, “Optimization of aRE-based Microgrid using Genetic Algorithm in the perspective of Bangladesh,” Proc. 6th Int. Conf. Commun. Electron. Syst. ICCES 2021, no. 2, pp. 283–288, 2021, doi: 10.1109/ICCES51350.2021.9489107.
12. [12] A. J. De Kock and A. J. Rix, “Optimal Sizing of Hybrid Utility-Scale Photovoltaics and Pumped Hydro Storage Plants,” Int. Conf. Electr. Comput. Commun. Mechatronics Eng. ICECCME 2022, no. November, pp. 1–6, 2022, doi: 10.1109/ICECCME55909.2022.9988537.
13. [13] T. A. Boghdady, S. R. Bakhoum, and M. M. Sayed, “Microgrid Optimal Sizing and Economic Operation for Rural Area in Assiut (Egypt) Using Meta-Heuristic Optimization Techniques,” Int. Telecommun. Conf. ITC-Egypt 2022 - Proc., pp. 1–7, 2022, doi: 10.1109/ITC-Egypt55520.2022.9855733.
14. [14] A. Nyandwi, A. Gupta, D. Kumar, and A. Ved, “Design Optimization Analysis Based on Demand Side Management of a Stand-alone Hybrid Power System Using Genetic Algorithm for Remote Rural Electrification,” 3rd Int. Conf. Energy, Power Environ. Towar. Clean Energy Technol. ICEPE 2020, no. Icepe 2020, 2021, doi: 10.1109/ICEPE50861.2021.9404489.
15. [15] Y. T. Wassie and E. O. Ahlgren, “Understanding the load profiles and electricity consumption patterns of PV mini-grid customers in rural off-grid east africa : A data-driven study,” Energy Policy, vol. 185, no. December 2023, p. 113969, 2024, doi: 10.1016/j.enpol.2023.113969.
16. [16] S. M. M. Tafreshi, H. A. Zamani, S. M. Ezzati, M. Baghdadi, and H. Vahedi, “Optimal unit sizing of distributed energy resources in microgrid using genetic algorithm,” Proc. - 2010 18th Iran. Conf. Electr. Eng. ICEE 2010, pp. 836–841, 2010, doi: 10.1109/IRANIANCEE.2010.5506961.
17. [17] C. E. Lin and B. C. Phan, “Optimal hybrid energy solution for island micro-grid,” Proc. - 2016 IEEE Int. Conf. Big Data Cloud Comput. BDCloud 2016, Soc. Comput. Networking, Soc. 2016 Sustain. Comput. Commun. Sustain. 2016, pp. 461–468, 2016, doi: 10.1109/BDCloud-SocialCom-SustainCom.2016.74.
18. [18] D. A. Kawadgave and M. G. Unde, “Design and Optimization of Renewable Hybrid Energy System for Rural India - Feasibility Study,” Int. Conf. Electr. Comput. Commun. Mechatronics Eng. ICECCME 2022, no. November, pp. 1–6, 2022, doi: 10.1109/ICECCME55909.2022.9988469.
19. [19] A. M. Abdelshafy, H. Hassan, A. M. Mohamed, G. El-Saady, and S. Ookawara, “Optimal grid connected hybrid energy system for Egyptian residential area,” Proceeding - ICSEEA 2017 Int. Conf. Sustain. Energy Eng. Appl. "Continuous Improv. Sustain. Energy Eco-Mobility", vol. 2018-Janua, pp. 52–60, 2017, doi: 10.1109/ICSEEA.2017.8267687.
20. [20] S. L. Arun, S. Kumaravel, and M. P. Selvan, “Unit size optimization of Hybrid Energy System,” 2014 IEEE Innov. Smart Grid Technol. - Asia, ISGT ASIA 2014, pp. 79–83, 2014, doi: 10.1109/ISGT-Asia.2014.6873768.
21. [21] S. Rajanna and R. P. Saini, “Optimal modeling of an integrated renewable energy system with battery storage for off grid electrification of remote rural area,” 1st IEEE Int. Conf. Power Electron. Intell. Control Energy Syst. ICPEICES 2016, 2017, doi: 10.1109/ICPEICES.2016.7853114.
22. [22] S. Rajanna and R. P. Saini, “Selection of suitable strategy with peak load shifting based DSM strategy of standalone integrated renewable energy system for a remote rural area,” 1st IEEE Int. Conf. Power Electron. Intell. Control Energy Syst. ICPEICES 2016, pp. 1–6, 2017, doi: 10.1109/ICPEICES.2016.7853645.
23. [23] C. Altin, “Artificial Bee Colony Algorithm Based Very Fast Renewable Energy System Optimization Tool Design,” Proc. 2023 27th Int. Conf. Electron. Electron. 2023, pp. 1–6, 2023, doi: 10.1109/IEEECONF58372.2023.10177657.