Enhancing Power Distribution Efficiency in Nigeria: Optimal Placement and Sizing of Solar Photovoltaics
Abstract
Nigeria’s power sector is plagued by chronic electricity shortages, high transmission losses, and an overdependence on fossil fuels, all of which hamper socio-economic development. With abundant solar irradiance across its regions, solar photovoltaic (PV) integration presents a viable alternative to improve power reliability and sustainability. However, improper placement and sizing of distributed solar units within distribution networks can result in voltage instability, reverse power flows, and inefficient system performance. This study investigates the optimal placement and sizing of solar PV units in Nigerian distribution systems to minimise power losses and improve voltage profiles. Using a selected radial distribution network representative of Nigeria’s 33 kV feeders, the study employs a load flow analysis coupled with a Particle Swarm Optimisation (PSO) algorithm to determine ideal locations and capacity ratings for PV units. The analysis considers practical constraints including voltage limits, load demands, and generation capacity bounds. Results indicate that strategic integration of solar PV at optimally identified buses significantly reduces total active power losses and improves voltage stability across the network. Specifically, losses were reduced by over 40% in the test scenario, while voltage deviations were maintained within acceptable limits. The findings further suggest that even modest penetration of solar PV can enhance distribution efficiency when correctly deployed. The study underscores the technical and economic viability of decentralised solar deployment in addressing Nigeria’s persistent electricity challenges. It recommends the incorporation of optimisation models in national energy planning and calls for regulatory support to facilitate distributed generation. Future research may extend the model to include energy storage systems and time-varying load dynamics for more robust planning. This re
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