本論文應用慣性權重粒子群演算法於微型電網之電力調度。首先，鑑於微型電網中之風力發電與太陽能發電系統，其發電量分別受風速與日照影響，具相當之不穩定性，本文採用商用軟體Solar Pro來建立太陽能發電系統模型，並模擬其發電量；風力發電系統部分則採韋伯機率密度分佈及實際日風速變化資料來模擬及計算其發電量。其次，本文以國內某研究單位所建構之微型電網示範系統為範例系統，以電力潮流解析法為基礎，建構微型電網之最適電力調度法則。除此之外，本論文尚利用MATLAB模擬軟體，開發出一套最佳化粒子群演算法，可在滿足負載需求與各項運轉限制條件下，充分有效利用風力發電及太陽能發電系統之發電量，最適化微型渦輪機與儲能設備之運轉調度。所開發之電力調度程式適用於併網及孤島兩種運轉模式，而利用粒子群演算法可求解出最佳市電購售電及電池充放電等各調度情況，使得微型電網之電力調度更富彈性。模擬結果顯示，本文所提出之方法確實可行，可提供為微型電網系統即時控制與調度之參考。

This thesis applies inertia weight particle swarm optimization (PSO) algorithm to microgrid power dispatch. First of all, the power generation of wind turbine and solar photovoltaic (PV) system depend on the wind speed and sunlight, respectively, having considerable instability. In this study, a commercial software Solar Pro is used to create a solar PV system model and to simulate their power generation. The Weibull probability density distribution and actual daily wind speed data are used to create a wind speed model and calculate its power generation. Secondly, a microgrid pilot demonstration system constructed by a research institute of Taiwan was selected as a sample system and microgrid optimal power dispatch rules based on power flow analysis was proposed. In addition, this paper uses the MATLAB simulation software to develop a set of optimized particle swarm algorithm that can meet the load demand and the operating restrictions. The operation scheduling optimization of micro-turbines and energy storage equipment can be achieved with the full and effective use of wind power and Solar photovoltaic system. Power dispatch program developed can be applied to the grid-connected and the islands modes, and the use of the particle swarm algorithm can solve the optimal power dispatch problems considering the power purchase and battery management. Simulation results show that the proposed method is feasible and may provide a valuable reference for real-time control and dispatch of a micro-grid system.

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