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研究生: 蔡逸哲
Tsai, Yi-Je
論文名稱: Finding Optimal Dispatch Schedule of Power Generation Using Locational Marginal Pricing in a Dynamic Market
在動態市場中使用區域邊際叫價方法尋找最佳發電分配計畫
指導教授: 蘇豐文
Soo, Von-Wun
口試委員:
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2010
畢業學年度: 99
語文別: 英文
論文頁數: 47
中文關鍵詞: 動態電力市場供應函數均衡區域邊際價格代理人基底模型
外文關鍵詞: Dynamic electricity market, Supply function equilibrium, Locational marginal price, Agent-based model
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  • 近年來,傳統所使用的電力批發市場逐漸的被零售的電力市場架構所取代,在許多國家當中,各項針對市場設計的問題正激烈被討論中,比如如何避免市場壟斷,如何正確實做出電力零售市場,以及如何增加市場整體的利潤。本文的重點是在於開發一個模型,用以模擬電力市場的競價過程,以及研究電力損失對試場均衡所造成的影響。我們使用多代理人系統與供應函數均衡模型(SFE model)模擬市場參與者之間的策略性互動行為,並利用損失因子來當作系統電力損失的計算考量。為了分析考量系統電力損失的競價方式,會對電力使用的效率造成多大的影響,我們以IEEE 30-匯流排系統為依據,對不同的電力需求分佈實例做實驗,並將數據結果列在論文當中。我們的系統為了能夠及時修正任何突發狀況,有別於一般採用的Day-ahead市場架構,我們以動態(Dynamic)競價市場架構當作系統的主體,並實驗若當系統當中,電力供給或電力需求的條件改變時,系統是否能夠及時反應。最後針對兩個在動態競價市場架構當中,對市場達到供需平衡所需的時間有所影響的兩個系統參數(市場初始價格以及市場價格調節因子)做探討,試著找出一個最有效率的競價系統。


    During these years, the regulatory framework for the wholesale sector of the electricity industry has been replaced by market competition in many countries. There are many ongoing debates over market design issues such as how to avoid market oligopoly problem, how to properly implement a retail electricity market and how to increase profits of market players. This thesis focuses on the development of a model and the simulation of electricity market and studies the impacts of power losses on electricity market equilibrium states in order to find an optimal dispatch schedule of distributed power supplies to power demand in the power delivery networks. To simulate the interaction among strategic behaviors of market players, we generalize a multi-agent system with the supply function equilibrium (SFE) model and take power losses into consideration. We conduct the experiments on IEEE 30-bus systems to illustrate the performance of the proposed method and present some numerical results that are effective in showing various economic impacts of power losses including system benefits and changes in the system marginal price. And we also investigate the influence of market operator variables such as market initial price and price adjust factor on convergence rate in terms of curves of market bidding history.

    中文摘要 i Abstract ii Acknowledgement iv Table of figures v Table of Tables vi Table of contents vii 1 Introduction 1 2 Market architecture 5 2.1 SFE approach for electricity market modeling 5 2.1.1 Overview 5 2.1.2 Supplier agents 5 2.1.3 Market operator 6 2.2 Locational marginal price 8 2.2.1 Overview 8 2.2.2 Power losses calculation 9 2.2.3 Penalty loss factor 9 3 System design 12 3.1 Market structure 12 3.2 Dynamic LMP bidding algorithm 13 4 Numerical results 17 4.1 Experiments of dynamic LMP bidding algorithm 18 4.1.1 Simple test 18 4.1.2 Randomly generated cases 21 4.2 Reactions for the changes in generation conditions 26 4.3 Influence of market operator variables 29 4.3.1 Initial price 29 4.3.2 Price adjustor factor 33 5 Conclusion and future work 37 Reference 39 Appendix 43

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