本研究提出增強型企業職級演算法應用於配電系統負載削減及負載轉移排程規劃，研究目標乃在於藉由負載削減及負載轉移，有效改善配電系統供電品質問題，同時兼具提昇經濟效益。本文首先建立負載削減及負載轉移之數學模型，並將最大電壓不平衡率及規劃成本共同整合為一多目標函數，然後輔以增強型企業職級演算法進行負載削減及負載轉移之排程擬定。本文所研發之增強型企業職級演算法係由企業上下級關係及員工工作方式啟發，並加以推導建立為尋優機制，有助於求解最佳化問題。而為驗證本文所提方法之可行性，本文透過IEEE測試系統及一實際配電系統進行模擬測試，並建立三種測試情境加以探討。由模擬結果可知，本文所提方法於求解負載削減及負載轉移排程規劃問題，確實優質可行，研究成果可提供電力規劃及調度施行參考。

This study applies the enhanced heap-based optimization algorithm to load-curtailment and load-shifting scheduling of distribution systems, aiming at using load-curtailment and load-shifting to improve the power quality of distribution systems while economic efficiency is also concerned. The thesis starts with the formulation of mathematical models of load-curtailment and load-shifting, in which maximum voltage unbalance ratio and planning cost are included as multi-objective function while those constraints of distribution systems are taken into consideration as well. Following the formulation of the problem to solve, an enhanced heap-based optimization algorithm is developed to perform the work of load- curtailment and load-shifting scheduling of distribution systems. The enhanced heap-based optimization algorithm is developed based on mimicking the corporate ranking and the achievements of employees, by which it is modeled as an optimization method for solving problems. To verify the effectiveness of the method, this study applies the approach on an IEEE test system and a real distribution system under three different scenarios. Test results indicate the superiority and feasibility of the proposed method. The outcome gained from this study serves as beneficial references for power system planning and operation.

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