隨著電力需求的不斷增長和能源危機的出現，微電網的發展變得更加普遍. 再生能源在微電網中的利用更具優勢. 本研究探討了將分散式發電和太陽能光伏系統整合到微電網中.目標函數的主要目的是最大限度地減少太陽能光電等再生能源發電與微電網系統內的需求之間的功率差異累積.發電或從公用電網接收電力的能力取決於微電網的能源容量.在此背景下，螢火蟲演算法和移動回歸被用作解決討論中的最佳化問題的有效工具. 所提出的方法正在微電網領域應用，並且正在將實施演算法的結果與原始調度方法進行比較.在調度過程中，分配一定電量作為備用電源，以減輕停電影響，並提高微電網整體供電可靠性。 在這項工作中，使用 MATLAB 模擬了所提出的方法在電力調度策略中的可行性。 Modbus通訊協定和演算法的實作通常使用C程式語言進行。 一台支援程式的工業電腦已放置在國立中央大學的微電網一號中，以評估演算法的可行性以及調度方法在系統供電可靠性方面的最佳化結果。 ;With the growing demand for electricity and the emergence of energy crises, the development of microgrids (MGs) has become more common. Renewable energy source utilization in Microgrids is more advantageous. This study examines the integration of Distributed Generation (DG) and Solar Photovoltaic (PV) systems into a Microgrid. The primary aim of the objective function is to minimize accumulation of power differences between the generation from renewable energy sources (RES), such as solar photovoltaic, and the demand within the microgrid system. The ability to produce electricity or receive power from the utility grid (UG) is dependent upon the energy capacity of the Microgrid. In this context, the Firefly Algorithm (FA) and Moving Regression (MR) are employed as effective tools for addressing the optimization problem as discussed. The proposed methodology is being applied in the domain of Microgrid, and the outcomes of implementing the Firefly algorithm are being compared with the original dispatch methods. During the process of dispatching, a certain amount of power is allocated as backup power to mitigate the impact of power outages, hence improving the overall supply reliability of the microgrids. In this work, the viability of the proposed method in power dispatch strategy is simulated using MATLAB. The implementation of the Modbus communication protocol and algorithm is often carried out using the C programming language. A program-enabled industrial computer has been placed in Microgrid 1 at National Central University to assess the viability of the algorithm and the optimization outcome of the scheduling approach in terms of system supply reliability.
