發(fā)布時間：2018-10-25 19:08

【摘要】：風能作為可再生能源的后起之秀,蘊藏著巨大的經(jīng)濟效益,但其隨機性與間歇性已然成為大規(guī)模風電并網(wǎng)的瓶頸,增加了電力系統(tǒng)動態(tài)經(jīng)濟調(diào)度的技術(shù)難度,也影響了發(fā)電公司的收益。 本文遵循現(xiàn)代電力市場競爭調(diào)度原則,提出一種考慮利益重配機制的風水火二階段隨機動態(tài)經(jīng)濟調(diào)度策略,旨在實現(xiàn)能源互補、利益共贏。策略以發(fā)電公司總收益最優(yōu)為導向,借水電、火電常規(guī)電源穩(wěn)定可靠的發(fā)電能力輔助消除風電功率間歇變化對電力系統(tǒng)產(chǎn)生的沖擊,利于處理風電隨機擾動影響決策執(zhí)行的問題。 模型構(gòu)建需要場景樹理論作為支撐,將分類電價與風電功率的隨機性問題轉(zhuǎn)化成確定性問題。建模中,第一階段尋求給定條件下日前市場最具經(jīng)濟效益的出力方式,稱為計劃出力；第二階段引入不平衡電價評估風電實際調(diào)度不滿足計劃出力的懲罰,并借助水火電穩(wěn)定調(diào)節(jié)能力對不平衡量進行補償,完成實時市場細化時間區(qū)間內(nèi)的反饋修正。統(tǒng)籌兩階段問題解算出最優(yōu)收益,依據(jù)均衡解法利益重配與風險評估指標確定風水火各自最終收益。本策略能將系統(tǒng)重新分配的收益與風險維持在預期水平,增加發(fā)電公司在調(diào)度中的主動性,通過調(diào)用GAMS軟件的DICOPT求解器解決了高維、非線性、多約束的混合整數(shù)規(guī)劃問題,結(jié)合不同算例驗證了所述方法與模型的可行性。 負荷水平一致時,對比是否考慮隨機場景下風水火系統(tǒng)收益的多個算例,表明引入隨機場景后,所提策略可行且提高了發(fā)電公司的總收益。在均衡解法下優(yōu)化了水火電源收益,驗證了合理構(gòu)建多源共濟動態(tài)經(jīng)濟調(diào)度策略對創(chuàng)造共贏格局的重要性。不平衡電價取值較高時,總收益下降并趨于恒定值,此時發(fā)電公司可以通過實際收益期望選擇是否接納風電并網(wǎng)調(diào)度,提高發(fā)電主動性和預見性。
[Abstract]:As the rising star of renewable energy, wind energy has great economic benefits, but its randomness and intermittency have become the bottleneck of large-scale wind power grid connection, which increases the technical difficulty of dynamic economic dispatch of power system. Also affected the power generation company's income. Following the principle of competitive dispatch in modern electric power market, this paper presents a two-stage stochastic dynamic economic scheduling strategy for feng shui fire considering the mechanism of benefit redistribution, which aims at realizing energy complementarity and win-win benefits. The strategy is based on the optimal total income of the power generation company. By means of hydropower, the stable and reliable generating capacity of conventional thermal power supply helps to eliminate the impact of intermittent variation of wind power on the power system. It is propitious to deal with the problem that random disturbance of wind power affects decision execution. The model construction needs scene tree theory to transform the stochastic problem of classified electricity price and wind power into deterministic problem. In modeling, the first stage is to seek the most economical way for the pre-day market under given conditions, which is called "planning force". In the second stage, the penalty of unbalance electricity price is introduced to evaluate the actual dispatch of wind power, and the feedback correction in the time range of real-time market refinement is completed with the help of the ability of hydro-thermal power stability regulation to compensate the unbalanced amount. The optimal income is calculated by solving the two-stage problem as a whole, and the final income of feng shui fire is determined according to the equilibrium solution and the risk evaluation index. This strategy can maintain the income and risk of system redistribution at the expected level, increase the initiative of power generation companies in scheduling, and solve the high dimensional, nonlinear, multi-constraint mixed integer programming problem by calling the DICOPT solver of GAMS software. The feasibility of the method and model is verified by different examples. When the load level is the same, a number of examples of wind and water heating system under random scenarios are compared, which shows that the proposed strategy is feasible and improves the total revenue of power generation companies after introducing the random scenario. Based on the equilibrium solution, the benefits of water and fire power are optimized, and the importance of constructing multi-source dynamic economic scheduling strategy for win-win situation is verified. When the value of unbalanced electricity price is higher, the total income decreases and tends to a constant value. In this case, the power generation company can choose whether to accept wind power grid scheduling or not through the actual income expectation, so as to improve the initiative and predictability of power generation.
【學位授予單位】：廣西大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM73

【參考文獻】

相關(guān)期刊論文 前10條

1 王素霞;;國內(nèi)外風力發(fā)電的情況及發(fā)展趨勢[J];電力技術(shù)經(jīng)濟;2007年01期

2 李衛(wèi)東,吳海波,武亞光,張銳,金鐘鶴;電力市場下AGC機組調(diào)配的遺傳算法[J];電力系統(tǒng)自動化;2003年15期

3 李端超,江山立,陳家庚,李東明;AGC機組調(diào)節(jié)效能定量評估與補償方式研究[J];電網(wǎng)技術(shù);2001年08期

4 吳至復;曾鳴;劉寶華;袁德;路燁;林俊;;電力市場中的水火電優(yōu)化調(diào)度模型及其應(yīng)用[J];電網(wǎng)技術(shù);2006年15期

5 林伯強;電力消費與中國經(jīng)濟增長:基于生產(chǎn)函數(shù)的研究[J];管理世界;2003年11期

6 韋增欣,莫降濤;補償隨機規(guī)劃的一種新數(shù)值方法[J];數(shù)學年刊A輯(中文版);2002年05期

7 李曉玲;GAMS系統(tǒng)中的數(shù)據(jù)庫設(shè)計[J];西北大學學報(自然科學版);1999年01期

8 韋化,李濱,杭乃善,劉東平,文杰,佐佐木博司;大規(guī)模水火電力系統(tǒng)最優(yōu)潮流的現(xiàn)代內(nèi)點理論分析[J];中國電機工程學報;2003年04期

9 白曉清;韋化;Katsuki Fujisawa;;求解最優(yōu)潮流問題的內(nèi)點半定規(guī)劃法[J];中國電機工程學報;2008年19期

10 孫元章;吳俊;李國杰;何劍;;基于風速預測和隨機規(guī)劃的含風電場電力系統(tǒng)動態(tài)經(jīng)濟調(diào)度[J];中國電機工程學報;2009年04期

相關(guān)博士學位論文 前1條

1 李雪峰;互聯(lián)電力系統(tǒng)的AGC容量需求和控制策略研究[D];大連理工大學;2010年

，

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