Firefly Algorithm for Optimal Allocation of Photovoltaic Systems to Enhance the Resiliency of Radial Distribution Networks: An Iraqi Case Study

Abstract

This paper presents an intelligent optimization approach to enhance voltage stability and resilience in radial distribution systems in Iraq through the strategic integration of photovoltaic (PV) units. A modified IEEE 35-bus radial feeder, reflecting the actual characteristics of Iraqi power grids, was used to simulate various operational scenarios, including base load, single and multiple PV placements, varying load levels, and fault conditions. To determine the optimal placement and sizing of PV units, a nature-inspired metaheuristic — the Firefly Algorithm (FA) — was employed. The FA effectively addresses nonlinear, multi-objective optimization challenges in practical power distribution planning, especially under fault-prone conditions. System performance was assessed using voltage deviation, total power loss, and energy not supplied (ENS) as evaluation metrics. The results demonstrate that improper PV placement can worsen voltage instability; however, this issue is effectively mitigated through FA-based optimization. The FA achieved a minimum bus voltage of 0.9508 p.u., outperforming the Genetic Algorithm and conventional methods. Multi-run simulations further validated the robustness and consistency of the FA under varying load and fault scenarios. The proposed intelligent PV planning framework offers a scalable, adaptable solution for enhancing resilience and enabling renewable energy integration in Iraq and other developing nations with radial distribution networks and high solar potential .