Planning off-grid rural electrification with MicroGridsPy: The case of Dugub, Nigeria

Rural electrification plays a crucial role in improving the socioeconomic conditions of underserved communities by enabling extended productive hours, enhancing access to education, and empowering women. However, conventional grid extension is often economically unfeasible for remote areas due to challenging terrain, dispersed populations, and low demand. As a result, alternative solutions such as solar photovoltaic (PV) mini-grids are gaining attention. This study investigates the most cost-effective and sustainable approach to off-grid rural electrification using solar PV-based mini-grids in Dugub, a rural farming community in northeastern Nigeria. Specifically, it examines different demand scenarios and system configurations to identify the optimal solution that minimizes costs and greenhouse gas (GHG) emissions. The study utilizes the MicroGridsPy optimization model to simulate and analyze energy usage patterns and mini-grid system performance under constant and evolving demand scenarios. Key parameters such as installed capacity, net present cost (NPC), and the levelized cost of electricity (LCOE) were evaluated across different configurations involving solar PV, batteries, and diesel generators. Results indicate that a hybrid system consisting of solar PV with battery storage and a backup generator, incorporating capacity expansion over time, is the most cost-effective option. The optimal scenario achieved a renewable energy penetration of 94.7 %, with the generator contributing less than 6 % of the total energy supply. The findings demonstrated that solar-based mini-grids offer a viable solution for rural electrification when appropriately sized. The study highlights the importance of supportive policies, capacity planning, and stakeholder engagement in ensuring long-term sustainability and socioeconomic development in rural areas. • Highlights the effectiveness of MicroGridsPy for off-grid rural electrification optimization. • The Comprehensive Energy Solution Planning methodology was employed. • Capacity expansion with evolution of demand provides an optimal mini-grid design. • Data-driven electrification planning is key to mini-grid development in rural areas. • The study highlights the critical role of policy interventions.