應用模糊馬可夫決策發展自由化電業市場多狀態競價策略

近年解制及自由化的風潮在世界各地展開，不論在電信、運輸或電力產業均已見其成效，而電力產業在邁向自由化後，市場買賣的行為變成一種透過競標方式的商業交易。本文觀察了各國電業市場之競爭發展概況，以及瞭解為因應新環境而建立的新機構，如獨立系統操作員(ISO)及電力交易所(PX)。在此市場中，每一家發電公司皆在公平的制度下，自由參與投標發電，系統操作員於每一交易時段會考慮網路相關限制式與每一家發電公司之競標價，然後依負載需求來調度發電公司發電。本文主要是以發電公司的觀點來探討如何在競標過程中決定競標策略，發電公司決策單位利用系統的狀態來訂定競標策略。本文假設市場在每一競標過程之交易時段結束後，系統會公佈節點價格(Nodal Price)之資訊給所有市場參與者，且利用模擬軟體Power World V. 7.0來得到節點價格，並由已知的節點價格資訊及各時段系統負載量利用模糊C分割(Fuzzy-C-Means, FCM)的方法，對已知狀態做模糊分類。在求解最佳決策方面，本文採用馬可夫決策過程(Markov Decision Process, MDP)以線性規劃法(LP)來對已知之模糊狀態與決策進行最佳化演算，以求得最佳的競標策略。在模擬測試上，我們利用一30匯流排及IEEE 118匯流排系統來進行模擬，並比較模糊與非模糊之馬可夫決策過程的結果差異。由模擬結果顯示本文之方法具有可行性。

關鍵字

競標策略；馬可夫決策過程；節點價錢；模糊分類

並列摘要

Recently, deregulation has had a great impact on the telecommunication, transportation and electric power industry in various countries. Bidding competition is one of the main transaction approaches after deregulation. This thesis analyzes the recent development of deregulated electric power markets and figures out the new organizations like Independent System Operator (ISO) and Power Exchange (PX). In this market, each genco offers a bid price and the ISO takes the all bidding prices with network constraints into account to determine the generation scheduling. In this thesis, bidding strategies are developed for a genco in a competitive market with the states of the power systems. The information of the nodal prices is assumed to be available in the competitive market for the participants in the thesis. We use the software package, Power World V. 7.0 to obtain the nodal price. Fuzzy-C-Means (FCM) algorithm is employed to cluster load levels and nodal prices. In this thesis, Markov Decision Process (MDP) which uses the Linear Programming (LP) algorithm is used to obtain the best policy for the states of the genco. A 30-bus system and the IEEE 118-bus are used to be examples for generating scheduling data. The results of the fuzzy and non-fuzzy MDP are finally compared. It is shown that the proposed method is applicable on the basis of the simulation results.

並列關鍵字

nodal price ； Markov Decision Process ； Fuzzy-C-Means ； bidding strategy

參考文獻

[2] 張簡志年，「解制市場之壅塞管理」，中原大學電機工程學系碩士論文，民國90年6月。

[38] 韓夢麟，「服務復原策略效益評估模式建立之研究-以馬可夫鏈為分析工具」，中原大學企業管理研究所碩士論文，民國90年6月。

[6] 「台灣電業自由化下發電市場競爭機制之研究」，台灣經濟研究院，民國89年3月。

[7] C.W. Richter, Jr. and G.B. Sheble, “Genetic Algorithm Evolution of Utility Bidding Strategies for the Competitive Marketplace,” IEEE Trans. on Power Systems, Vol. 13, No. 1, Feb. 1998, pp. 256-261.

[9] Y. Y. Hong and M. T. Weng,“Investigation of Nodal Prices in Deregulated Competitive Market –Case Studies,”International Conference on PowerTech, Budapest, Aug. 29-Sep. 2, 1999, pp. 161.

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應用模糊馬可夫決策發展自由化電業市場多狀態競價策略

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