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This article proposes a single-period unit commitment enhancement for specified system load to minimize two separate objective functions of economic operations: fuel cost of thermal power generation units and active power losses of transmission based on Optimal Power Flow (OPF) using a hybrid optimization technique of the Whale Optimization Algo-rithm and Differential Evolution (WOA-DE). The proposed algorithm included the renew-able energy resource of wind turbines, considering the wind speed uncertainty with a Weibull distribution model to estimate wind power output. The wind turbines have been installed based on optimal locations using the WOA-DE technique. The control variables of optimal power flow were initially optimized to minimize two separate objective func-tions of fuel cost and active power losses for each one. These control variables are the gen-erator active power except the slack, the generator voltage magnitude, the transformer tap setting, the shunt compensation reactive power and the locations of renewable energy re-sources. OPF output was accessed during each progressive unit shutdown. Integrating re-newable energy improves the flexibility of the unit commitment schedule by decreasing the number of thermal generating units taken offline without compromising system feasibility. The proposed WOA-DE-based framework can support more economical and reliable oper-ation of the power system by improving unit commitment decisions, increasing the instal-lation of the renewable energy sources, and enabling satisfying the operational constraints of the power system. The novelty of the proposed framework lies in integrating Weibull-based wind recourse characterization, optimal wind turbine placement, single-period unit commitment, and optimal power flow within a hybrid WOA-DE optimization framework to assess power system operation before and after renewable energy integration. The pro-posed technique is implemented on the IEEE 30 bus test system.
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Habeeb et al. (2026) studied this question.
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