电力市场下计及风险规避的售电公司购售电策略研究

发布时间：2018-06-22 04:44

本文选题：电力市场 + 售电公司　；参考：《华北电力大学(北京)》2017年硕士论文

【摘要】：1985年,我国开始实行集资办电政策,正式拉开了电力工业改革的序幕。2015年,我国下发《关于进一步深化电力体制改革的若干意见》,鼓励组建6类售电主体,有序向社会资本放开售电业务,进一步推进了电力零售市场的改革进程。售电公司作为零售市场的主体担任着从批发市场和平衡市场购买电能,并出售给用户的中间商角色。同时在电力交易过程中,售电公司也面临着市场价格和用户侧负荷双重波动的风险。因而,深入研究购售电合同类型及其风险规避特征,制定合理组合购售电策略及售电价格,是售电公司面临的关键问题。本文围绕售电公司在批发市场和平衡市场计及风险规避的交易策略问题展开研究。在批发市场中,研究包括中远期双边合同、期权合同、可中断合同、现货市场交易四种购电方式,以及固定分时电价合同、实时电价合同两种售电方式的组合交易策略;采用条件风险价值法(Conditional Value at Risk,CVa R)度量交易策略预期风险损失,并建立混合整数非线性规划数学模型;以售电公司组合交易策略收益最优和预期风险损失最小为目标,采用BONMIN进行优化求解。在平衡市场中,引入用户侧负荷作为平衡资源,提出包含可中断负荷/电量收购和关键负荷电价两类需求响应项目参与的平衡市场优化交易策略;采用CVa R度量交易策略预期风险损失,并建立了基于随机规划的非线性数学模型。利用双层规划思想,以售电公司收益最大、预期风险损失最小为上层目标,以用户满意度最大为下层,采用自适应遗传算法和二代非劣排序遗传算法进行模型求解。算例结果证明了模型的有效性和合理性。第一个算例表明,不同类型的购电合同和售电合同具有不同的收益特点和风险规避特征,售电公司可根据自身风险偏好制定合理的购售电组合交易策略和售电电价。第二个算例表明,风险偏好和市场电价波动程度对售电公司收益和预期风险损失有显著影响,本文提出的引入需求响应项目的平衡市场交易策略可显著优化售电公司收益并降低风险损失,实现售电公司和用户的双赢。
[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.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F426.61

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