Abstract—This paper proposes a comprehensive two-stage optimization framework for the optimal allocation and operation of hybrid Photovoltaic-Battery Energy Storage Systems (PV-BESS) in distribution networks, taking into account critical/sensitive loads. In the first stage, a Genetic Algorithm (GA) integrated with Time-Domain Power Flow (TDPF) is employed to determine the optimal sizing and placement of PV and BESS units, aiming to minimize active/reactive power losses and voltage deviations. In the second stage, a 24-hour Optimal Power Dispatch (OPD) model is utilized, formulated as a nonlinear programming problem, to minimize total daily operating costs, including grid exchange, losses, battery degradation, and the high penalty Cost of Unserved Energy (COUE) for critical loads. Unlike previous studies, the incorporation of a high COUE penalty ensures zero unserved critical energy by strategically utilizing BESS during peak demand or low-PV periods, even when grid power is more economical. To assess the efficiency of the proposed method, the IEEE 33-bus system and a real network in Mazar-e-Sharif, Afghanistan, are used. Results demonstrate about 33.37% annual reduction in active power loss, stable voltage at critical buses, and a daily operating cost of 494,168 AFN (Afghan Afghani, the currency of Afghanistan) with full reliability. Additionally, the findings confirm that the proposed method is highly suitable for import-dependent, high-insolation distribution networks in developing regions with critical infrastructure.

Keywords—battery energy storage system, critical loads, distribution network, optimal allocation, Photovoltaic (PV) system, Mazar-e-Sharif

Cite: Abdul Farooq Bikzada, Saeid Esmaeili, Sina Shakeri, Mohammad Jawad Rasa, "Two-Stage Optimal Allocation and Operation of Hybrid PV-BESS Systems Considering Critical/Sensitive Loads in Distribution Networks: A Case Study on the 117-Bus Mazar-e-Sharif Network, Afghanistan," International Journal of Smart Grid and Clean Energy, Vol. 15, No. 1, pp. 1-14, 2026. doi: 10.12720/sgce.15.1.1-14

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