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研究生: 陳彥竹
Chen, Yen-Chu
論文名稱: 建構在不確定環境下混合再生能源系統之最佳電力供給與傳輸模式
Modeling and Optimization of Power Management of Hybrid Renewable Energy Systems in Uncertain Environment
指導教授: 張國浩
Chang, Kuo-Hao
口試委員: 楊朝龍
Yang, Chao-Lung
馮文昕
Feng, Wen-Xin
學位類別: 碩士
Master
系所名稱: 工學院 - 工業工程與工程管理學系
Department of Industrial Engineering and Engineering Management
論文出版年: 2013
畢業學年度: 101
語文別: 中文
論文頁數: 42
中文關鍵詞: 混合再生能源系統隨機最佳化分散式發電系統微電網兩階段隨機規劃模型
外文關鍵詞: Hybrid renewable energy system, stochastic optimization, distributed generation, micro grid, two-stage stochastic programming model
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  • 混合再生能源系統 (hybrid renewable energy system, HRES)為一個使用多種能源的供電系統,其中能源包含再生能源和備用能源,如太陽能發電、風力發電和傳統柴油發電等等...,但由於在真實世界中,再生能源發電與用電需求皆具不確定性,每天每小時皆會改變,想要利用再生能源來滿足需求顯得有一定的困難度。本論文目的為針對用電需求與再生能源供給皆為不確定的情況下,以分散式發電系統 (Distributed Generation, DG)所構成的微電網為架構,建立一個混合再生能源管理模型,包含管理電力供給與傳輸,並發展一套有效率的最佳化演算法來達到以最小化的發電成本來供給多個區域下的需求,最後將模型與演算法建構成一個決策支援系統,以方便使用者使用此系統,做為能源決策的參考。


    A hybrid renewable energy system (HRES) is the energy system which combines several renewable energy sources and conventional generators such as solar photovoltaic, wind energy and conventional diesel generator for back up. The matching of electrical generation with power consumption in HRES is a challenging problem due to the intermittent and highly variable characteristics of renewable energies and unknown demand. In this paper, we optimize the number of renewable energy generators in each station so as to result in minimized total generation cost, while satisfying demand of each area. Further, we propose a new methodology to handle the problem. Numerical experiments show that the proposed method can work well in real settings. Finally, we create a decision support system (DSS) that enables power management in real time.

    目錄 摘要 ii ABSTRACT iii 目錄 v 圖目錄 vii 表目錄 viii 一、 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 3 1.3 論文架構 4 二、 文獻探討 7 2.1 混合再生能源系統 7 2.2 分散式發電系統 9 2.2.1 太陽能發電 12 2.2.2 風力發電 13 三、 問題定義 16 四、 發展演算法 21 五、 數值實驗 25 六、 決策支援系統 30 6.1 參數設定 31 6.2 結果輸出 32 6.3 敏感度分析 33 6.4 電力傳輸與補足 34 七、 結論與未來研究 38 7.1 結論 38 7.2 未來研究 39

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