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工程科学与技术:2023,55(1):101-109
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基于投资组合理论的风光储场站参与多时间尺度电力现货市场的出力分配优化方法
(新能源电力系统国家重点实验室(华北电力大学),北京 102206)
Output Allocation Optimization Method for the Wind Photovoltaic Energy Storage Power Station in the Multi-time-scale Electricity Spot Market Under Portfolio Theory
(State Key Lab.of Alternate Electrical Power System with Renewable Energy Sources, (North China Electric Power Univ.), Beijing 102206, China)
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投稿时间:2022-07-18    修订日期:2022-12-17
中文摘要: 随着中国电力现货市场的发展及“双碳”目标的提出,风光储场站参与电力现货市场已成为主流趋势。为了考虑市场价格波动与风光出力不确定性对风光储场站出力分配的影响,本文从经济学引入投资组合理论作为收益和风险的权衡工具,提出了风光储场站参与日前、日内、实时市场的出力分配方法,使风光储场站获得最大化收益的同时承担最小的风险。首先,考虑风光出力不确定性,基于日前、日内、实时市场的电价构建了多时间尺度的收益模型。然后,采用历史电价数据的方差与协方差来描述市场风险及其相关性,考虑风光储场站内部能量的协同调控,构建了以场站的收益最大、风险最小为目标函数的出力分配优化模型。最后,通过增广拉格朗日乘子法对问题进行求解,获得了风光储场站参与电力现货市场的最优出力分配。对市场风险、场站最优出力分配、风险规避指数灵敏度与计算效率进行算例分析。结果表明:市场电价与风险之间存在着较强的相关性;使用本文方法后的场站收益比参与单一市场可以提高13.3%,风险可以降低84.1%;随着风险规避程度的增加,场站会降低高风险市场的参与度;本文算法具有较高的计算效率。因此,通过本文的优化方法,风光储场站可以根据不同市场的风险与预期收益有选择性地参与市场,并按照自身风险规避程度实现收益的最大化与风险的最小化。
Abstract:With the development of the electricity spot market and the “double carbon” goal in China, the participation of the wind-photovoltaic-energy storage power station (WPS) has become a mainstream trend. In order to consider the influence of the market price fluctuation and the renewable energy uncertainty on the output allocation of the WPS, a output allocation method of the WPS participating in the day-ahead, day-time and real-time markets was put forward in this paper. The portfolio theory from economics was taken as a trade-off tool for the profit and risk so that the WPS can maximize the benefits while taking the least risks. Firstly, considering the uncertainty of the wind power and photovoltaic output, a multi-time-scale revenue model was constructed based on the electricity price in the day-ahead, day-time and real-time markets. Secondly, the variance and covariance of electricity prices were used to describe the market risk and its correlation. The optimization model of output allocation was then constructed with the maximum profit and minimum risk as the objective function, considering the collaborative regulation of the internal energy of the WPS. Finally, the problem was solved by the augmented Lagrange method to get the optimal output allocation of the WPS in the electricity spot market over daily operation time. The market risk, the optimal output allocation of the WPS, the sensitivity and the calculation efficiency of risk aversion index were analyzed in this paper. The results showed that there is a strong correlation between the electricity price and risk. Compared with participating in a single market, the profit of WPS increased by 13.3% under the proposed method, the risk decreased by 84.1%. With the increase of risk aversion index, the WPS reduced its participation in high-risk markets. Moreover, this algorithm has high computational efficiency. Therefore, through the optimization method, the WPS can selectively participate in the market according to the risks and expected profits of different markets, and realize the maximization of profits and the minimization of risks according to its own risk aversion degree.
文章编号:202200726     中图分类号:TM73    文献标志码:
基金项目:国家重点研发计划项目(2021YFB2400702)
作者简介:第一作者:王凯(1998-),男,硕士生.研究方向:电力市场.E-mail:kyriek1998@163.com;通信作者:延肖何,讲师,E-mail:x.yan@ncepu.edu.cn
引用文本:
王凯,延肖何,刘念.基于投资组合理论的风光储场站参与多时间尺度电力现货市场的出力分配优化方法[J].工程科学与技术,2023,55(1):101-109.
WANG Kai,YAN Xiaohe,LIU Nian.Output Allocation Optimization Method for the Wind Photovoltaic Energy Storage Power Station in the Multi-time-scale Electricity Spot Market Under Portfolio Theory[J].Advanced Engineering Sciences,2023,55(1):101-109.