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  • 學位論文

MPEC模式於電力市場需量反應之分析

MPEC Analysis of Demand Response in Electricity Markets

指導教授 : 胡明哲

摘要


近年來,為了讓人民能自由選擇電力來源以及減輕台灣在用電高峰時發電機組的負載,政府開始推動電力市場自由化,希望更多公司提供新的電力來源。最近,需量反應也被認為是提供電力的新方式,因此需量反應將會是本研究主要的研究目標。然而,電力市場自由化後,成效還不顯著可歸咎於鮮少有對於未來台灣電力市場中競爭的分析及模擬,以至於潛在參與者對於市場的不確定性感到不安。因此,本研究提出將電力自由化後的台灣電力市場模擬成mathematical program with equilibrium constraints(MPEC) 問題。模式中包含利用stochastic programming以及Nash-Cournot equilibrium找出最佳的電力抑低量以及台電的需量反應獎勵金額。要解MPEC問題不是很容易,因此本研究使用GAMS中nlpec的solver,將MPEC reformulation,再找出最佳解。目前在台灣尚未有學者將台灣電力市場模擬成MPEC,而我們認為此模式可以精確的模擬台灣電力市場競爭狀況,並給政府或是想進入市場的玩家有擬訂政策或是策略的依據。

並列摘要


In recent years, in order to allow people to freely choose power sources and reduce the load on generators during peak hours in Taiwan, the government has begun to promote the liberalization of the electricity market, hoping that more companies will provide new sources of electricity. Besides, the demand response has also been considered as a new way to provide electricity, so the demand response will be the main research target of this study. However, after the liberalization of the electricity market, the results are not significant, which can attribute to the lack of analysis and simulation of competition in the future Taiwan electricity market and the potential players are concerned about the uncertainty of the market. Therefore, this study proposes to simulate the Taiwanese electricity market after power liberalization as a mathematical program with equilibrium constraints (MPEC). The model includes the use of stochastic programming and Nash-Cournot equilibrium to find the optimal amount of power reduction and the amount of demand response rewards for Taipower. To solve the MPEC problem is not very easy, so this study uses nlpec solver in GAMS, reformulate this MPEC problem, and then find the best solution. At present, no scholars in Taiwan have simulated the Taiwan power market as MPEC, and we believe that this model can accurately simulate the competition in the Taiwan power market and provide a basis for policy or strategy for the government or players who want to enter the market.

參考文獻


Aalami, H., Moghaddam, M. P., & Yousefi, G. J. A. E. (2010). Demand response modeling considering interruptible/curtailable loads and capacity market programs. 87(1), 243-250.
Abrate, G., Bompard, E., Napoli, R., & Wan, B. (2006). Multi-agent models for consumer choice and retailer strategies in the competitive electricity market. Retrieved from
Barbarosoǧlu, G., & Arda, Y. J. J. o. t. o. r. s. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. 55(1), 43-53.
Birge, J. R., & Louveaux, F. (2011). Introduction to stochastic programming: Springer Science & Business Media.
Cappers, P., Goldman, C., & Kathan, D. J. E. (2010). Demand response in US electricity markets: Empirical evidence. 35(4), 1526-1535.

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