隨著全球能源轉型的加速，微電網作為一種靈活性高的小型分散式電力系統，其在促進能源效率與穩定電力供應的潛力正逐步被發掘。本研究為發展一套具備電動車雙向充放電應用的家庭微電網系統，並著重於考量外在環境影響如溫度或雨量所產生的車輛運行能耗與微電網當前電力狀態之電能管理控制策略，旨在提出一種高效率與可持續性的電能管理系統(Energy Management System, EMS)控制架構，以支持電動車和微電網之間的能量協調。本研究中所建立的微電網系統包含電動車系統、太陽能發電系統、儲能系統、市電與家庭負載，並搭配多種控制策略包含本研究提出之階層式交互式粒子群模糊控制，針對不同的情境能更適應性的實現電能管理的效果，藉以達到最佳化用電之目標。
本研究以Matlab/Simulink軟體實現，實驗平台包含直流-直流轉換器、三相變流器、Y-Y三相變壓器、電子負載、可程控電源供應器、搭載鋰電池模組之儲能系統與PC控制器，透過PC控制器進行實虛功率控制以及電能管理控制。觀察非夏季實驗結果，在用電量方面相較於階層式模糊基本規則庫控制策略，階層式粒子群模糊控制策略可改善5.5%；階層式交互式粒子群模糊控制策略可改善11.2%，從而驗證本研究提出之階層式交互式粒子群模糊控制策略能有效應用於微電網電能管理系統。

As the global energy transition accelerates, microgrids, as flexible and decentralized power systems, are increasingly recognized for their potential to enhance energy efficiency and ensure stable power supply. This study aims to develop a home microgrid system incorporating bidirectional charging and discharging applications for electric vehicles. It focuses on considering external environmental factors, such as temperature and rainfall, which affect vehicle energy consumption, and the current power state of the microgrid to design an energy management control strategy. The goal is to propose an efficient and sustainable energy management system (EMS) control framework that coordinates energy flow between electric vehicles and the microgrid.
The microgrid system developed in this study includes an electric vehicle system, a solar power generation system, a battery storage system, the utility grid, and household loads. The system is designed to work with various control strategies, including the proposed hierarchical interactive particle swarm fuzzy control method, which adapts to different scenarios to achieve optimal energy management.
The system is implemented using MATLAB/Simulink, and the experimental platform includes a DC-DC converter, a three-phase inverter, a Y-Y three-phase transformer, an electronic load, a programmable power supply, an energy storage system equipped with lithium battery modules, and a PC controller. The PC controller handles real and reactive power control as well as energy management control. Experimental results conducted outside the summer season show that, in terms of power consumption, compared to the hierarchical fuzzy rule-based control strategy, the hierarchical particle swarm fuzzy control strategy improves by 5.5%, and the hierarchical interactive particle swarm fuzzy control strategy improves by 11.2%. This verifies that the proposed hierarchical interactive particle swarm fuzzy control strategy is effectively applicable to energy management systems in microgrids.

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