可再生能源配额制下售电公司多市场交易决策

doi:10.12204/j.issn.1000-7229.2023.07.001

电力建设 ›› 2023, Vol. 44 ›› Issue (7): 1-10.doi: 10.12204/j.issn.1000-7229.2023.07.001

• 双碳目标驱动下的能源电力经济与市场机制·栏目主持文福拴教授、刘敦楠教授· • 上一篇下一篇

可再生能源配额制下售电公司多市场交易决策

吴玲¹^,²^,³(), 刘浩⁴, 刘秋华³, 郑亚先⁵

1.自然资源部碳中和与国土空间优化重点实验室南京工程学院研究中心,南京市 211167
2.江苏省绿色低碳发展国际合作联合实验室,南京市 211167
3.南京工程学院经济与管理学院,南京市 211167
4.国网江苏泰州供电公司,江苏省泰州市 225310
5.中国电力科学研究院有限公司,南京市 210003

收稿日期:2022-08-10 出版日期:2023-07-01 发布日期:2023-06-21
通讯作者: 吴玲 E-mail:64254212@qq.com
作者简介:刘浩(1995),男,硕士,主要研究方向为电力市场;
刘秋华(1963),女,博士,教授,主要研究方向为能源技术经济;
郑亚先(1982),男,硕士,研究员级高级工程师,主要研究方向为电力市场。
基金资助:
国家自然科学基金青年科学基金项目(52107098);南京工程学院校级科研基金项目(CKJB201907);自然资源部碳中和与国土空间优化重点实验室南京工程学院研究中心开放基金项目(CNT202201)

Research on the Multi-Market Decisions of Electricity Retailers Under Renewable Portfolio Standards

WU Ling¹^,²^,³(), LIU Hao⁴, LIU Qiuhua³, ZHENG Yaxian⁵

1. NJIT Research Center,The Key Laboratory of Carbon Neutrality and Territory Optimization, Ministry of Natural Resources, Nanjing 211167, China
2. International Joint Laboratory of Green & Low Carbon Development, Jiangsu Province, Nanjing 211167, China
3. School of Economy and Management, Nanjing Institute of Technology, Nanjing 211167, China
4. State Grid Jiangsu Taizhou Power Supply Company, Taizhou 225310, Jiangsu Province, China
5. China Electric Power Research Institute, Nanjing 210003, China

Received:2022-08-10 Online:2023-07-01 Published:2023-06-21
Contact: WU Ling E-mail:64254212@qq.com
Supported by:
National Natural Science Foundation of China(52107098);Scientific Research Fund Project of Nanjing Institute of Technology(CKJB201907);Open Research Fund of NJIT Research Center, The Key Laboratory of Carbon Neutrality and Territory Optimization, Ministry of Natural Resources(CNT202201)

摘要/Abstract

摘要：

可再生能源配额制实施后,售电公司面临着电力交易市场和绿证市场的多市场组合交易决策问题。基于配额制下售电公司市场交易框架及模式,考虑售电公司多种购电渠道的购电成本、柔性合约成本、绿证交易成本及售电收入,以条件风险价值法度量相关不确定因素带来的风险值,构建多市场组合交易决策模型。运用多场景法对风电出力、集中竞价市场出清价格、绿证价格等不确定因素生成典型场景集,以售电公司收益最大、市场交易风险最低为决策目标,采用GAMS软件对决策模型进行编程求解。算例仿真分析了风险规避系数、风电出力不确定性、可再生能源配额比例等因素变化对售电公司收益的影响,对模型的有效性进行了验证,为配额制下售电公司参与多市场交易决策提供理论指导。

关键词: 售电公司, 可再生能源配额制, 风险度量, 组合交易策略

Abstract:

With the implementation of renewable energy quota systems, electricity-selling companies are obligated to consume renewable energy. To study the impact of renewable energy quota systems on the revenue of electricity companies, the market transaction framework and model of electricity companies under such quota systems were analyzed, and a multi-market portfolio transaction model was established. The electricity-selling company considered in the model had different market power purchase costs, flexible contract costs, and electricity-selling incomes. Moreover, it used the method of multiple scenarios for renewable energy power-generation unit output, centralized price bidding in uncertain factors such as market clearing price per month, and the method of conditional value at risk, the relevant risk measurement uncertainty. The model was designed to maximize the profit of the electricity sales company and minimize the market transaction risk. GAMS software was used to solve the model. A simulation analysis of the risk avoidance coefficient, renewable energy unit output uncertainty, renewable energy quota ratio, and other factors affecting the revenue of electricity companies verified the effectiveness of the model, providing theoretical guidance for electricity companies to better participate in market competition under quota systems.

Key words: electricity retailer, renewable portfolio standards, risk measurement, portfolio-trading strategy

中图分类号:

TM76
F407.6

吴玲, 刘浩, 刘秋华, 郑亚先. 可再生能源配额制下售电公司多市场交易决策[J]. 电力建设, 2023, 44(7): 1-10.

WU Ling, LIU Hao, LIU Qiuhua, ZHENG Yaxian. Research on the Multi-Market Decisions of Electricity Retailers Under Renewable Portfolio Standards[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(7): 1-10.

图/表 17

图1 配额制下售电公司的市场交易框架

Fig.1 Market transaction framework of electricity companies under quota system

图2 用户柔性负荷响应形式

Fig.2 User flexible load response form

图3 用户柔性负荷响应能力曲线

Fig.3 User flexible load response capability curve

图4 用户侧负荷需求量

Fig.4 User side load demand

图5 不同风险规避系数下售电公司在各市场购电量

Fig.5 Electricity purchased in each market under different risk aversion coefficients of electricity selling companies

图6 不同风险规避系数下售电公司期望收益和风险损失情况

Fig.6 Expected returns and risk losses of electricity sales companies under different risk aversion coefficients

图7 风电机组出力不确定下售电公司风电及绿证购买量

Fig.7 Purchase quantity of wind power and green certificates of electricity sales companies under the uncertainty of output of different wind turbines

图8 风电机组出力不确定下售电公司售电期望收益

Fig.8 Expected revenue of electricity sales of electricity selling companies under different wind turbine output uncertainties

图9 不同配额比例下售电公司在各市场购电量

Fig.9 Electricity purchased in each market under different quota ratios

图10 不同配额比例下售电公司期望收益与风险损失

Fig.10 Expected profit and risk loss of electricity selling company

图A1 集中竞价市场各场景每月出清价格集合

Fig.A1 Collection of monthly clearing prices in various scenarios of centralized bidding market

表A1 集中竞价市场各场景出现相应概率

Table A1 The probability of occurrence of each scenario in the centralized bidding market

图A2 15%不确定性情况下单位风电机组各场景出力集合

Fig.A2 Output set of each scenario of unit wind turbine under 15% uncertainty

图A3 20%不确定性情况下单位风电机组各场景出力集合

Fig.A3 Output set of each scenario of unit wind turbine under 20% uncertainty

图A4 25%不确定性情况下单位风电机组各场景出力集合

Fig.A4 Output set of each scenario of unit wind turbine under 25% uncertainty

表A2 不同单位风电机组出力不确定性场景概率

Table A2 Scenario probability of output uncertainty of different units of wind turbines

表A3 风电绿证各场景价格及概率

Table A3 Price and probability of each scenario of wind power green certificate

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可再生能源配额制下售电公司多市场交易决策

Research on the Multi-Market Decisions of Electricity Retailers Under Renewable Portfolio Standards

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