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چکیده
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This thesis investigates the active power control of photovoltaic (PV) systems integrated into islanded microgrids, with a focus on enhancing voltage stability, energy management, and resilience in the case of uncertainty. Islanded microgrids face significant challenges due to their dependence on intermittent renewable sources and the absence of main grid support. To address these challenges, a Model Predictive Control (MPC) strategy, a technique-based forecasting for irradiance, temperature, and load demand, is developed. A key contribution of this work is the integration of an adaptive forecast-error correction mechanism, which refines irradiance predictions in real time using PV output feedback. This correction approach ensures that the controller continuously compensates for mismatches between predicted and actual operating conditions, thereby improving voltage regulation and maintaining accurate MPPT operation. The proposed framework also incorporates battery state-of-charge (SoC) management, switching between MPPT and curtailment modes to avoid overcharging and deep discharging. Simulation results of a complete nonlinear state-space model of a standalone PV-battery microgrid demonstrate superior voltage stability, smoother control actions, and extended battery life compared to conventional MPC approaches. This work highlights that embedding adaptive forecast- error compensation into MPC significantly enhances the robustness and efficiency of islanded PV-based microgrids under real-world uncertainties.
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