本論文提出了一種基於多目標優化演算法的方法，以改進分散式發電的電壓控制策略。該方法考慮到實際負載的每日變化，涉及設定變壓器有載分接頭切換器、切換式電容器和智慧型變流器之電壓-無效功率控制的閾值。使用多目標粒子群優化演算法與柏拉圖前緣優化目標函數，包括電壓偏差、系統功耗損失以及變壓器有載分接頭切換器和切換式電容器的變動次數，通過最小化這些目標函數，可以獲得一組最佳控制點。最後在IEEE 33-bus測試系統對多種負載模式的操作情景進行模擬，以驗證所提方法的有效性。模擬結果顯示，所提出的方法有效地優化了電壓控制問題，從而提高了配電系統的電壓穩定性和可靠性。

This thesis proposes a method based on a multi-objective optimization algorithm for enhancing the voltage control strategy for distributed generation by considering the daily variations of actual loads. The proposed method involves setting the voltage control thresholds of the on-load tap changer, switched capacitor, and voltage–reactive power control of smart inverters. A multi-objective particle swarm optimization algorithm is used with Pareto fronts to optimize the objective functions, which include voltage deviation,system power losses, and the number of changes in the on-load tap changer and switched capacitor. By minimizing these objective functions, a set of optimal control setpoints can be obtained. Several operating scenarios with varying
daily load patterns were simulated using the IEEE 33-bus test system to validate the effectiveness of the proposed methodology. The simulation results showed that the proposed approach effectively optimizes the voltage control problem, thereby improving the voltage stability and reliability of a distribution system.

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