需求响应下计及电碳市场耦合的多元主体成本效益分析

doi:10.12204/j.issn.1000-7229.2023.02.005

电力建设 ›› 2023, Vol. 44 ›› Issue (2): 50-60.doi: 10.12204/j.issn.1000-7229.2023.02.005

• 面向新型电力系统的灵活性资源发展关键技术及应用·栏目主持鞠立伟副教授、谭忠富教授· • 上一篇下一篇

需求响应下计及电碳市场耦合的多元主体成本效益分析

靳冰洁¹, 李家兴²(), 彭虹桥¹, 罗澍忻¹, 卢治霖³, 冷媛³, 董萍², 梁梓杨³

1.广东电网有限责任公司电网规划研究中心,广州市 510080
2.华南理工大学电力学院,广州市 510641
3.南方电网能源发展研究院有限责任公司,广州市 510663

收稿日期:2022-07-22 出版日期:2023-02-01 发布日期:2023-01-30
通讯作者: 李家兴(1999),男,硕士研究生,主要研究方向为电力市场需求响应、电力系统优化与控制,E-mail:499061976@qq.com。
作者简介:靳冰洁(1989),女,硕士,工程师,主要研究方向为电力系统运行与规划;
彭虹桥(1993),男,硕士,助理工程师,主要研究方向为负荷预测、电力系统规划;
罗澍忻(1987),男,博士,高级工程师,主要研究方向为电力系统规划;
卢治霖(1994),男,硕士,工程师,主要研究方向为电力系统优化运行与控制、电力市场;
冷媛(1986),女,硕士,高级经济师,主要研究方向为电力体制改革、电力市场、电力价格;
董萍(1978),女,博士,副教授,主要研究方向为电力市场需求响应、柔性交流输电系统技术及电力系统控制等;
梁梓杨(1998),男,硕士,助理工程师,主要研究方向为综合能源市场、电力市场。
基金资助:
中国南方电网有限责任公司电力规划专题研究项目(031000QQ00210011)

Cost-Benefit Analysis of Multiple Entities Under the Coupling of Electricity and Carbon Trading Market Considering Demand Response

JIN Bingjie¹, LI Jiaxing²(), PENG Hongqiao¹, LUO Shuxin¹, LU Zhilin³, LENG Yuan³, DONG Ping², LIANG Ziyang³

1. Grid Planning & Research Center, Guangdong Power Grid Co., Ltd., CSG, Guangzhou 510080, China
2. School of Electric Power, South China University of Technology, Guangzhou 510641, China
3. China Southern Power Grid Energy Development Research Institute Co., Ltd., Guangzhou 510663, China

Received:2022-07-22 Online:2023-02-01 Published:2023-01-30
Supported by:
Electric Power Planning Research Program of China Southern Power Grid Co., Ltd.(031000QQ00210011)

摘要/Abstract

摘要：

成本效益研究有助于了解各市场主体的效益情况和交易意愿,从而指导市场制定更加合理的交易机制。文章提出了一种需求响应(demand response,DR)下计及电碳交易市场耦合的多个市场主体的成本效益分析方法。首先将碳交易中的单位碳排放成本计入各发电机组的报价函数中进行统一出清,体现碳交易与现货市场运营的耦合;其次,考虑了需求响应下电碳耦合市场中各个主体的交易机制,提出了发电侧、用户侧、负荷聚合商、储能运营商及电网侧的成本效益分析模型。最后,对中国某省电网某实际运行日进行了算例分析,结果表明,碳排放权交易市场运作将抬高电力市场出清价格,影响相关主体的成本与效益。

关键词: 现货市场, 碳排放权交易市场, 需求响应(DR), 成本效益分析

Abstract:

Cost-benefit research helps to understand the benefits and willingness to trade of various market players, so as to guide the market to formulate a more reasonable trading mechanism. This paper proposes a cost-benefit analysis method for multiple market players considering the coupling of electricity and carbon trading markets under demand response (DR). First, the unit carbon emission cost in carbon trading is included in the quotation function of each generating unit for unified clearing, which reflects the coupling of carbon trading and spot market operations. Secondly, the transactions of various entities in the electricity-carbon coupling market under demand response are considered. A cost-benefit analysis model for the generation side, the user side, the load aggregator, the energy storage operator and the grid side is proposed. Finally, an example analysis is carried out on an actual operation day of a certain provincial power grid in China. The results show that the operation of the carbon emission trading market will raise the clearing price of the electricity market and affect the cost and benefit of the relevant entities.

Key words: spot market, carbon trading market, demand response (DR), cost-benefit analysis

中图分类号:

TM73

靳冰洁, 李家兴, 彭虹桥, 罗澍忻, 卢治霖, 冷媛, 董萍, 梁梓杨. 需求响应下计及电碳市场耦合的多元主体成本效益分析[J]. 电力建设, 2023, 44(2): 50-60.

JIN Bingjie, LI Jiaxing, PENG Hongqiao, LUO Shuxin, LU Zhilin, LENG Yuan, DONG Ping, LIANG Ziyang. Cost-Benefit Analysis of Multiple Entities Under the Coupling of Electricity and Carbon Trading Market Considering Demand Response[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(2): 50-60.

图/表 25

图1 广东电力市场框架

Fig.1 Framework of Guangdong electricity market

图2 电力市场出清框架

Fig.2 Framework of electricity market clearing

表1 各类别机组碳排放基准值

Table 1 Carbon emission baseline of various units

图3 总体分析框架

Fig.3 Overall analysis framework

图4 发电侧成本与效益分析框架

Fig.4 Framework of generating-side cost and benefit analysis

图5 用户侧成本与效益分析框架

Fig.5 Framework of user-side cost and benefit analysis

图6 负荷聚合商成本与效益分析框架

Fig.6 Cost and benefit analysis framework for load aggregators

图7 储能运营商成本与效益分析框架

Fig.7 Cost and benefit analysis framework for energy storage operators

图8 电网侧成本与效益分析框架

Fig.8 Framework of grid-side cost and benefit analysis

图9 负荷电量及需求响应场景示意

Fig.9 Schematic diagram of load and demand response scenarios

图10 日前市场及实时市场出清电价曲线

Fig.10 Curves of day-ahead and real-time electricity market clearing prices

表2 仿真参数

Table 2 Simulation parameters

图11 发电侧各时段结算结果

Fig.11 Generation-side results for each time period

图12 用户侧各时段结算结果

Fig.12 User-side results for each time period

图13 负荷聚合商各时段结算结果

Fig.13 Results of load aggregators for each time period

图14 储能运营商各时段结算结果

Fig.14 Results of energy storage operators for each time period

图15 电网侧各时段结算结果

Fig.15 Grid-side results for each time period

表3 运行日各市场主体总效益

Table 3 Total benefit of each market entity on operation day

图16 出清电价对比

Fig.16 Comparison of clear electricity prices

表4 两种模式出清结果的对比

Table 4 Comparison of the clearing results of the two modes

图17 2种模式下运行日各主体的总效益变化

Fig.17 The change of the total benefit of each entity in the two operating days

图18 用户需求响应占比对各主体效益的影响

Fig.18 The influence of user demand-response ratio on the benefit of each entity

图19 用户需求响应占比对社会总效益的影响

Fig.19 The influence of user demand-response ratio on total social benefit

图20 总需求响应比例对各主体效益的影响

Fig.20 The influence of total demand-response ratio on the benefit of each entity

图21 总需求响应比例对社会总效益的影响

Fig.21 The influence of total demand-response ratio on total social benefit

参考文献 20

[1]	关于征求《南方(以广东起步)电力现货市场实施方案(稿)》意见的函[EB/OL]. (2018-08-31) [2022-07-10]. http://power.in-en.com/html/power-2295719.shtml.
[2]	关于征求南方(以广东起步)电力现货市场系列规则意见的通知[EB/OL]. (2018-08-31) [2022-07-10]. http://nfj.nea.gov.cn/adminContent/initViewContent.do?pk=402881e56579be6301658d7123c2001a.
[3]	全国碳排放权交易市场上线交易正式启动[EB/OL]. (2021-07-17) [2022-07-10]. http://www.gov.cn/xinwen/2021-07/17/content_5625625.htm#1.
[4]	李姚旺, 张宁, 杜尔顺, 等. 基于碳排放流的电力系统低碳需求响应机制研究及效益分析[J]. 中国电机工程学报, 2022, 42(8): 2830-2842.
	LI Yaowang, ZHANG Ning, DU Ershun, et al. Mechanism study and benefit analysis on power system low carbon demand response based on carbon emission flow[J]. Proceedings of the CSEE, 2022, 42(8): 2830-2842.
[5]	吴鸿亮, 刘羽霄, 张宁, 等. 南方电网西电东送中的碳交易模型及其效益分析[J]. 电网技术, 2017, 41(3): 745-751.
	WU Hongliang, LIU Yuxiao, ZHANG Ning, et al. Carbon trading models and benefit analysis in CSG west-to-east power transmission[J]. Power System Technology, 2017, 41(3): 745-751.
[6]	马辉, 陈雨果, 陈晔, 等. 南方(以广东起步)电力现货市场机制设计[J]. 南方电网技术, 2018, 12(12): 42-48.
	MA Hui, CHEN Yuguo, CHEN Ye, et al. Mechanism design of Southern China (starting from Guangdong Province) electric spot market[J]. Southern Power System Technology, 2018, 12(12): 42-48.
[7]	代贤忠, 韩新阳, 靳晓凌. 需求响应参与电力平衡的成本效益评估方法[J]. 中国电力, 2022, 55(10): 170-177.
	DAI Xianzhong, HAN Xinyang, JIN Xiaoling. Cost-benefit assessment method for demand response participating in power balance[J]. Electric Power, 2022, 55(10): 170-177.
[8]	张静页, 王磊, 刘顺桂. 负荷聚合商参与可中断负荷项目的成本效益分析[J]. 南方电网技术, 2016, 10(8): 74-81.
	ZHANG Jingye, WANG Lei, LIU Shungui. Cost-benefit analysis of load aggregator participating in interruptible load program[J]. Southern Power System Technology, 2016, 10(8): 74-81.
[9]	刘坚, 熊英, 金亨美, 等. 电动汽车参与电力需求响应的成本效益分析: 以上海市为例[J]. 全球能源互联网, 2021, 4(1): 86-94.
	LIU Jian, XIONG Ying, KIM Hyoung Mi, et al. Economic assessment of demand response delivered by electric vehicles in Shanghai[J]. Journal of Global Energy Interconnection, 2021, 4(1): 86-94.
[10]	LI X Z. A cost-benefit analysis of V2G electric vehicles supporting peak shaving in Shanghai[J]. Electric Power Systems Research, 2020, 179: 106058. doi: 10.1016/j.epsr.2019.106058 URL
[11]	陈启鑫, 周天睿, 康重庆, 等. 节能发电调度的低碳化效益评估模型及其应用[J]. 电力系统自动化, 2009, 33(16): 24-29.
	CHEN Qixin, ZHOU Tianrui, KANG Chongqing, et al. An assessment model of low-carbon effect and its application to energy saving based generation dispatching[J]. Automation of Electric Power Systems, 2009, 33(16): 24-29.
[12]	ELDALI F, HARDY T, CORBIN C, et al. Cost-benefit analysis of demand response programs incorporated in open modeling framework[C]// 2016 IEEE Power and Energy Society General Meeting. IEEE, 2016: 1-5.
[13]	庄晓丹, 刘卫东, 黄为群, 等. 浙江电力现货市场环境下储能的市场交易机制与效益分析[J]. 中国电力, 2022, 55(6): 80-85.
	ZHUANG Xiaodan, LIU Weidong, HUANG Weiqun, et al. Energy storage market trading mechanism and benefit analysis of Zhejiang power spot market[J]. Electric Power, 2022, 55(6): 80-85.
[14]	张高, 薛松, 范孟华, 等. 面向我国电力市场的需求响应市场化交易机制设计[J]. 电力建设, 2021, 42(4): 132-140. doi: 10.12204/j.issn.1000-7229.2021.04.015
	ZHANG Gao, XUE Song, FAN Menghua, et al. Design of demand-response market mechanism in accordance with China power market[J]. Electric Power Construction, 2021, 42(4): 132-140. doi: 10.12204/j.issn.1000-7229.2021.04.015
[15]	冯天天. 绿证交易及碳交易对电力市场的耦合效应分析模型研究[D]. 北京: 华北电力大学, 2016.
	FENG Tiantian. Coupling induction analysis model of tradable green certificates and carbon emission trading acting on electricity market in China[D]. Beijing: North China Electric Power University, 2016.
[16]	卢治霖, 刘明波, 尚楠, 等. 考虑碳排放权交易市场影响的日前电力市场两阶段出清模型[J]. 电力系统自动化, 2022, 46(10): 159-170.
	LU Zhilin, LIU Mingbo, SHANG Nan, et al. Two-stage clearing model for day-ahead electricity market considering impact of carbon emissions trading market[J]. Automation of Electric Power Systems, 2022, 46(10): 159-170.
[17]	赵晨晨. 低碳背景下电力需求响应效益评估研究[D]. 北京: 华北电力大学, 2015.
	ZHAO Chenchen. Research on benefits assessment of power demand response in the context of low carbon economy[D]. Beijing: North China Electric Power University, 2015.
[18]	彭晓洁, 钟永馨. 碳排放权交易价格的影响因素及策略研究[J]. 价格月刊, 2021(12): 25-31.
	PENG Xiaojie, ZHONG Yongxin. Research on influencing factors and strategies of carbon emission trading price[J]. Prices Monthly, 2021(12): 25-31.
[19]	HUANG J, XUE Y S, JIANG C, et al. An experimental study on emission trading behaviors of generation companies[J]. IEEE Transactions on Power Systems, 2015, 30(2): 1076-1083. doi: 10.1109/TPWRS.2014.2366767 URL
[20]	广东电力市场现货电能量交易实施细则(2022 年试行版)(南方监能市场[2022]1号))[EB/OL].(2022-01-07)[2022-07-10]. http://nfj.nea.gov.cn/adminContent/initViewContent.do?pk=4028811c7d55f39b017e329a8df400a3.

需求响应下计及电碳市场耦合的多元主体成本效益分析

Cost-Benefit Analysis of Multiple Entities Under the Coupling of Electricity and Carbon Trading Market Considering Demand Response

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 25

参考文献 20

相关文章 15

编辑推荐

Metrics

本文评价

[1]	时维帅, 孙欣, 谢敬东, 严佳嘉, 张誉匀. “双碳”目标下风氢联合系统参与现货市场的优化运行与效益分析[J]. 电力建设, 2022, 43(7): 1-12.
[2]	丁曦, 姜威, 郭创新, 奚增辉, 高洁. 考虑需求响应的电/热/气云储能优化配置策略[J]. 电力建设, 2022, 43(3): 83-99.
[3]	李磊, 王朝亮, 郝一浩, 李彬, 祁兵, 陈宋宋. 面向需求响应业务的灵活弹性传输策略[J]. 电力建设, 2022, 43(2): 10-17.
[4]	梁政, 魏震波, 孙舟倍, 马志程, 周强, 邵冲. 光热发电商参与下的电力现货市场均衡分析[J]. 电力建设, 2022, 43(1): 122-131.
[5]	段秦刚, 陈永椿, 王一, 吴明兴, 别佩, 董萍. 电力现货市场下激励型需求响应交易机制及出清模型[J]. 电力建设, 2021, 42(6): 145-156.
[6]	魏震波, 田轲, 罗筱均, 方涛. 电动汽车聚合商参与下的主辅联合市场均衡分析[J]. 电力建设, 2021, 42(2): 50-57.
[7]	刘政, 雷少锋, 王清亮, 李云达, 任惠, 卢锦玲. 考虑备用共享的区域电力现货市场出清模型[J]. 电力建设, 2021, 42(11): 63-71.
[8]	郝旭东, 孙伟, 程定一, 张国强, 匡洪辉. 基于Q强化学习的综合能源服务商现货市场申报策略研究[J]. 电力建设, 2020, 41(9): 132-138.
[9]	赵洱岽, 王浩, 林弘杨. 现货市场中基于演化博弈的火电企业阶梯报价策略[J]. 电力建设, 2020, 41(8): 68-71.
[10]	刘自发，王新月，于寒霄，高建宇，吴刚. 微电网与配电网的成本效益关系及交互电量定价方法[J]. 电力建设, 2020, 41(3): 39-46.
[11]	陆承宇, 江婷, 邓晖, 房乐, 王旭, 蒋传文. 基于合作博弈的含清洁能源发电商参与现货市场竞价策略及收益分配[J]. 电力建设, 2020, 41(12): 152-160.
[12]	袁桂丽，董金凤，魏更，贾新潮. 基于需求响应和多能互补的冷热电联产微网优化调度[J]. 电力建设, 2019, 40(9): 64-72.
[13]	高瑞，郭红霞，杨苹，郭敏铧，任智君. 基于用户侧可调节资源的售电公司实时市场偏差电量管控策略[J]. 电力建设, 2019, 40(6): 114-122.
[14]	宋杰，陈振宇，杨阳，张凯恒，张卫国，朱庆，徐青山. 考虑资源相关性和不确定性的负荷需求响应决策研究[J]. 电力建设, 2019, 40(6): 132-138.
[15]	马佳乐,谭忠富，喻小宝，谭清坤，德格吉日夫，赵蕊. 计及实时电量交易的售电公司日偏差电量考核优化模型[J]. 电力建设, 2019, 40(2): 11-19.