本文選題：售電公司 + 購電決策��； 參考：《華北電力大學(xué)(北京)》2017年碩士論文

【摘要】：隨著2015年“電改9號文”的下發(fā),正式啟動了我國售電側(cè)市場改革,大量售電公司在全國各地迅速成立。作為售電側(cè)市場的新型市場主體,售電公司具有代理用戶從多個電力交易市場上購售電的優(yōu)勢,因此如何合理的規(guī)劃購電比例及售電方案成為其運營的核心問題。此外,針對不斷增強(qiáng)的用戶需求響應(yīng)意識和激勵信息,用戶能夠主動調(diào)整其用電方式配合市場運營,從而降低自身的用電花銷,新的市場規(guī)則賦予了用戶直接參與市場交易的權(quán)利,用戶的用電行為將直接影響售電公司的購售電決策。針對這一新的需求,本文首先對售電公司在多個購電及售電市場面臨的不確定性進(jìn)行了分析和建模,為售電公司的購售電決策建立了模型基礎(chǔ)。隨后參照新的市場規(guī)則,為售電公司設(shè)計了購電與售電統(tǒng)一的購售電模型,并將用戶的用電行為聯(lián)動考慮,建立了考慮用戶需求響應(yīng)的售電公司購售電決策雙層模型,上層模型以售電公司利潤最大化為目標(biāo),下層模型以用戶用電效用最大化為目標(biāo)。綜合考慮了雙邊合同違約懲罰機(jī)制,對具有需求響應(yīng)能力的用戶用電負(fù)荷進(jìn)行建模,采取了售電公司代理用戶需求響應(yīng)資源參與實時市場的互動機(jī)制。此外,由于售電公司購售電決策中面臨的風(fēng)險將直接影響售電公司的決策,因此針對售電公司在進(jìn)行購售電決策時不同市場帶來的風(fēng)險,引入金融領(lǐng)域常用的風(fēng)險評估方法——條件風(fēng)險價值(CVaR),并結(jié)合風(fēng)險偏好系數(shù),建立了售電公司購售電效用決策模型,更準(zhǔn)確地反映了售電公司在進(jìn)行購售電決策中的行為選擇。最后,為驗證所提出的考慮用戶需求響應(yīng)的購售電決策模型和購售電效用決策模型,選用美國PJM市場一周的數(shù)據(jù)對模型進(jìn)行了驗證。結(jié)果表明考慮用戶需求響應(yīng)能夠給出更優(yōu)的售電公司購電決策方案,且考慮風(fēng)險的效用模型能更準(zhǔn)確地反映售電公司在進(jìn)行購售電決策時的風(fēng)險偏好程度及決策行為。論文研究工作瞄準(zhǔn)了售電市場改革新需求,為新的市場環(huán)境下售電公司的購售電決策提供了方法指導(dǎo)。
[Abstract]:With the launch of "Power Reform 9" in 2015, the reform of China's power sale market has been officially launched, and a large number of power sale companies have been set up rapidly throughout the country. As a new type of market subject in the power sale market, the power sale company has the advantage of purchasing and selling electricity from multiple electricity trading markets. Therefore, how to plan the proportion of electricity purchase and the scheme of electricity sale becomes the core problem in its operation. In addition, in response to the increasing awareness of user demand response and incentive information, users can actively adjust their electricity use mode to match the market operation, thereby reducing their own consumption. The new market rules give users the right to participate in market transactions directly. In view of this new demand, this paper first analyzes and models the uncertainty faced by the power sale companies in many power purchasing and selling markets, and establishes the model foundation for the purchasing and selling decisions of the power sale companies. Then, referring to the new market rules, a unified model of purchasing and selling electricity is designed for the power sale company. Considering the user's electricity consumption behavior, a two-layer model of purchasing and selling decision is established, which takes into account the response of the user's demand. The upper model aims at maximizing the profit of the power sale company, and the lower model aims at maximizing the utility of the consumers. Taking into account the penalty mechanism of bilateral contract breach, the model of customer power load with demand response ability is built, and the interactive mechanism of acting user demand response resource to participate in real-time market is adopted. In addition, because the risks faced by the power sale companies in their purchasing and selling decisions will directly affect the decisions of the power sale companies, the risks arising from different markets when the power sale companies make the purchase and sale decisions are addressed. This paper introduces the risk assessment method commonly used in financial field, conditional risk value (RV), and combines with risk preference coefficient, establishes the utility decision model of power purchase and sale for power sale companies, which reflects more accurately the behavior choice of power sale companies in the decision-making of purchasing and selling electricity. Finally, in order to verify the proposed decision model of purchasing and selling electricity and the utility decision model of purchasing and selling electricity taking into account the response of user demand, the model is verified by the one-week data of American PJM market. The results show that considering the customer demand response, a more optimal power purchase decision scheme can be obtained, and the utility model considering the risk can more accurately reflect the degree of risk preference and decision behavior of the power sale company. This paper aims at the new demand of the electricity market reform, and provides the method guidance for the purchasing and selling decision of the power sale company under the new market environment.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F426.61

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳政;王麗華;曾鳴;宋藝航;;國內(nèi)外售電側(cè)改革背景下的電力需求側(cè)管理[J];電力需求側(cè)管理;2016年03期

2 張曉萱;薛松;楊素;屠俊明;魏哲;馬莉;;售電側(cè)市場放開國際經(jīng)驗及其啟示[J];電力系統(tǒng)自動化;2016年09期

3 楊旭英;周明;李庚銀;;智能電網(wǎng)下需求響應(yīng)機(jī)理分析與建模綜述[J];電網(wǎng)技術(shù);2016年01期

4 羅琴;宋依群;;售電市場環(huán)境下計及可中斷負(fù)荷的營銷策略[J];電力系統(tǒng)自動化;2015年17期

5 羅琴;宋依群;徐劍;陳飛杰;薛瓊;;基于AHP-Logit模型的競爭性售電公司決策研究[J];華東電力;2013年11期

6 郭興磊;張宗益;亢婭麗;汪鋒;;基于CVaR模型的大用戶直購電決策分析[J];電力系統(tǒng)保護(hù)與控制;2011年18期

7 宋藝航;譚忠富;于超;姜海洋;;需求側(cè)峰谷分時電價對供電公司購售電風(fēng)險影響分析模型[J];電工技術(shù)學(xué)報;2010年11期

8 鄭雅楠;李庚銀;周明;;大用戶模糊優(yōu)化購電組合策略的研究[J];中國電機(jī)工程學(xué)報;2010年10期

9 張欽;王錫凡;王建學(xué);;需求側(cè)實時電價下供電商購售電風(fēng)險決策[J];電力系統(tǒng)自動化;2010年03期

10 曾鳴;王冬容;陳貞;;需求側(cè)響應(yīng)在電力零售市場中的應(yīng)用[J];電力需求側(cè)管理;2009年02期

，

本文編號：2030678