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Muhammed F. Alwaeli
University of Kufa
Computer Science & IT

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A Time-Domain Power Flow and Genetic Algorithm Approach to Optimal PV and Battery Storage Siting for Grid Resilience Muhammed F. Alwaeli
Journal of Technology and System Information Vol. 3 No. 3 (2026): July
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jtsi.v3i3.6341

Abstract

Higher ambient temperature can adversely affect conductor operating conditions and distribution-network losses, while comparatively less attention has been given to their mitigation through coordinated PV/BESS optimization. This study develops a climate-aware framework for the IEEE 33-bus distribution system using a temperature-dependent conductor resistance model under climate-stress conditions with 24-hour time-domain power flow and Genetic Algorithm optimization of PV/BESS sizing and placement. The reconstructed network reproduced the reported base-case loss of 202.7 kW. Under a severe climate-stress scenario of 50°C and 55% RH, daily losses increased from 2845.4 to 3158.0 kWh (+11.0%), while daily efficiency decreased from 95.76% to 95.30%. The optimized configuration, consisting of 1794.1 kW PV and a 448 kW/1760.4 kWh battery at bus 14, reduced daily losses to 2431.5 kWh, corresponding to reductions of 23.0% relative to the climate-stress case and 14.6% relative to the reference case. The minimum voltage during the critical operating period increased from 0.9063 to 0.9240 pu, and the number of hours within the specified voltage range increased by two. A Particle Swarm Optimization benchmark and sensitivity analysis further evaluated the robustness of the proposed configuration across the tested optimization methods and climate scenarios, with the optimal installation location varying under different capacity constraints.
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