本文選題：電力市場(chǎng) + 售電公司�。� 參考：《華北電力大學(xué)(北京)》2017年碩士論文

【摘要】：1985年,我國(guó)開始實(shí)行集資辦電政策,正式拉開了電力工業(yè)改革的序幕。2015年,我國(guó)下發(fā)《關(guān)于進(jìn)一步深化電力體制改革的若干意見》,鼓勵(lì)組建6類售電主體,有序向社會(huì)資本放開售電業(yè)務(wù),進(jìn)一步推進(jìn)了電力零售市場(chǎng)的改革進(jìn)程。售電公司作為零售市場(chǎng)的主體擔(dān)任著從批發(fā)市場(chǎng)和平衡市場(chǎng)購(gòu)買電能,并出售給用戶的中間商角色。同時(shí)在電力交易過程中,售電公司也面臨著市場(chǎng)價(jià)格和用戶側(cè)負(fù)荷雙重波動(dòng)的風(fēng)險(xiǎn)。因而,深入研究購(gòu)售電合同類型及其風(fēng)險(xiǎn)規(guī)避特征,制定合理組合購(gòu)售電策略及售電價(jià)格,是售電公司面臨的關(guān)鍵問題。本文圍繞售電公司在批發(fā)市場(chǎng)和平衡市場(chǎng)計(jì)及風(fēng)險(xiǎn)規(guī)避的交易策略問題展開研究。在批發(fā)市場(chǎng)中,研究包括中遠(yuǎn)期雙邊合同、期權(quán)合同、可中斷合同、現(xiàn)貨市場(chǎng)交易四種購(gòu)電方式,以及固定分時(shí)電價(jià)合同、實(shí)時(shí)電價(jià)合同兩種售電方式的組合交易策略;采用條件風(fēng)險(xiǎn)價(jià)值法(Conditional Value at Risk,CVa R)度量交易策略預(yù)期風(fēng)險(xiǎn)損失,并建立混合整數(shù)非線性規(guī)劃數(shù)學(xué)模型;以售電公司組合交易策略收益最優(yōu)和預(yù)期風(fēng)險(xiǎn)損失最小為目標(biāo),采用BONMIN進(jìn)行優(yōu)化求解。在平衡市場(chǎng)中,引入用戶側(cè)負(fù)荷作為平衡資源,提出包含可中斷負(fù)荷/電量收購(gòu)和關(guān)鍵負(fù)荷電價(jià)兩類需求響應(yīng)項(xiàng)目參與的平衡市場(chǎng)優(yōu)化交易策略;采用CVa R度量交易策略預(yù)期風(fēng)險(xiǎn)損失,并建立了基于隨機(jī)規(guī)劃的非線性數(shù)學(xué)模型。利用雙層規(guī)劃思想,以售電公司收益最大、預(yù)期風(fēng)險(xiǎn)損失最小為上層目標(biāo),以用戶滿意度最大為下層,采用自適應(yīng)遺傳算法和二代非劣排序遺傳算法進(jìn)行模型求解。算例結(jié)果證明了模型的有效性和合理性。第一個(gè)算例表明,不同類型的購(gòu)電合同和售電合同具有不同的收益特點(diǎn)和風(fēng)險(xiǎn)規(guī)避特征,售電公司可根據(jù)自身風(fēng)險(xiǎn)偏好制定合理的購(gòu)售電組合交易策略和售電電價(jià)。第二個(gè)算例表明,風(fēng)險(xiǎn)偏好和市場(chǎng)電價(jià)波動(dòng)程度對(duì)售電公司收益和預(yù)期風(fēng)險(xiǎn)損失有顯著影響,本文提出的引入需求響應(yīng)項(xiàng)目的平衡市場(chǎng)交易策略可顯著優(yōu)化售電公司收益并降低風(fēng)險(xiǎn)損失,實(shí)現(xiàn)售電公司和用戶的雙贏。
[Abstract]:In 1985, China began to implement the policy of raising funds to run electricity, which officially kicked off the reform of the electric power industry. In 2015, China issued "some opinions on further deepening the Reform of the Power system" to encourage the formation of six types of power sales agents. The orderly opening of electricity sales to social capital has further promoted the reform process of the electricity retail market. As the main body of the retail market, the power sale company acts as a middleman who buys electricity from the wholesale market and balances the market and sells it to the user. At the same time, in the process of electricity trading, the company faces the risk of double fluctuation of market price and customer side load. Therefore, it is a key problem for power sale companies to study the types of power purchase contracts and their risk aversion characteristics, and to formulate reasonable combination of purchase and sale strategies and selling prices. This paper focuses on the trading strategy of power sale companies in wholesale market and balanced market and risk aversion. In the wholesale market, the research includes four ways of purchasing electricity, including bilateral contract, option contract, interruptible contract, spot market transaction, and the combination trading strategy of two kinds of electricity sale modes: fixed time-sharing electricity price contract and real-time electricity price contract. The conditional value at Riskat CVa R is used to measure the expected risk loss of the trading strategy, and a mixed integer nonlinear programming mathematical model is established, in which the optimal return of the portfolio trading strategy and the minimum expected risk loss are taken as the goal. BONMIN is used to optimize the solution. In the equilibrium market, the user side load is introduced as the balanced resource, and the optimal trading strategy is put forward, which includes two types of demand response items: interruptible load / electricity quantity acquisition and critical load electricity price. CVaR is used to measure expected risk loss of trading strategy, and a nonlinear mathematical model based on stochastic programming is established. Based on the idea of bilevel programming, the model is solved by using adaptive genetic algorithm and second-generation non-inferior sorting genetic algorithm, aiming at the maximum profit and minimum expected risk loss of the power sale company, and taking the maximum customer satisfaction as the lower level. The results show that the model is effective and reasonable. The first example shows that different types of power purchase contracts and power sales contracts have different characteristics of revenue and risk aversion. The companies can make reasonable purchase and sale combination trading strategy and electricity price according to their own risk preference. The second example shows that risk preference and the fluctuation of electricity price have significant influence on the profit and expected risk loss of the company. In this paper, the balanced market trading strategy with demand response project can significantly optimize the revenue and reduce the risk loss of the power sale company, and realize the win-win situation between the power sale company and the user.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F426.61

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