考虑碳排放需求响应及碳交易的电力系统双层优化调度

doi:10.12204/j.issn.1000-7229.2024.05.010

电力建设 ›› 2024, Vol. 45 ›› Issue (5): 94-104.doi: 10.12204/j.issn.1000-7229.2024.05.010

考虑碳排放需求响应及碳交易的电力系统双层优化调度

张妍¹(), 冷媛¹(), 尚楠¹(), 梁梓杨¹(), 石昊²(), 罗钢²()

1.南方电网能源发展研究院有限责任公司,广州市 510663
2.北京清能互联科技有限公司,北京市 100084

收稿日期:2023-09-25 出版日期:2024-05-01 发布日期:2024-04-29
通讯作者: 石昊(1995),男,硕士,助理工程师,研究方向为电力市场、电力系统调度优化运行等,Email:shihao@tsintergy.com。
作者简介:张妍(1996),女,硕士,工程师,研究方向为电力市场等,Email:zhangyanthu0731@163.com;
冷媛(1986),女,硕士,高级经济师,研究方向为电力市场、电力价格等,Email:mucunleng@sina.com;
尚楠(1993),女,硕士,中级经济师,研究方向为电力市场建模分析等,Email: shangnan@csg.cn;
梁梓杨(1998),男,硕士,工程师,研究方向为电力市场等,Email: liangzy2@csg.cn;
罗钢(1987),男,博士,高级工程师,研究方向为电力市场、电力系统运行分析与控制等,Email:luogang@tsintergy.com。
基金资助:
国家重点研发计划项目(2022YFB2403100);中国南方电网有限责任公司科技项目(ZBKJXM20220010);南网能源院电碳耦合系统研究平台V1.0建设项目(2800002022030102DGO0005)

Bi-Level Optimal Scheduling of Power System Considering Carbon Demand Response and Carbon Trading

ZHANG Yan¹(), LENG Yuan¹(), SHANG Nan¹(), LIANG Ziyang¹(), SHI Hao²(), LUO Gang²()

1. China Southern Power Grid Energy Development Research Institute Ltd., Guangzhou 510663, China
2. Beijing Tsintergy Technology Co., Ltd., Beijing 100084, China

Received:2023-09-25 Published:2024-05-01 Online:2024-04-29
Supported by:
National Key Research and Development Program of China(2022YFB2403100);Science and Technology Project of China Southern Power Grid Co., Ltd.(ZBKJXM20220010);V1.0 Construction Project of Electric Carbon Coupling System Research Platform of Southern Grid Energy Institute(2800002022030102DGO0005)

摘要/Abstract

摘要：

发展低碳发电技术及有效参与碳配额市场交易是促进电力低碳转型的关键,借助储能和需求响应等灵活资源,产消者在电能生产和消费上具有更强的平衡能力。基于碳排放流理论提出了一种考虑碳排放需求响应及碳交易的电力系统双层优化调度模型。以配电网的节点碳势作为产消者需求响应的价格因素之一,通过上层配电网与下层产消者之间供/用能信息及电价、碳价信息的交互传递实现配电网优化运行。下层的产消者之间基于运行计划进行碳配额交易,并通过纳什议价方式完成收益确定。算例分析验证了所提模型在控制系统碳排放、促进需求响应积极性等方面的有效性。

关键词: 碳排放需求响应, 碳交易, 产消者, 双层优化

Abstract:

The development of low-carbon power generation technologies and effective participation in carbon quota market trading are the keys to promoting low-carbon transformation of electric power, and with the help of flexible resources such as energy storage and demand response, the prosumers have stronger balancing capabilities in electric energy production and consumption. A two-layer optimal scheduling model of the power system considering carbon demand response and carbon trading is proposed based on the carbon flow theory. The node carbon potential of the distribution network is used as one of the price factors for the demand response of producers and consumers, and the optimal operation of the distribution network is realized through the interactive transmission of supply/consumption information as well as electricity price and carbon price information between the upper distribution network and the lower producers and consumers. The lower tier producers and consumers trade carbon allowances based on the operation plan and determine the revenue through the Nash bargaining method. Case simulations verify the effectiveness of the model proposed in this paper in controlling the carbon emissions of the system and promoting the enthusiasm of demand response.

Key words: carbon demand response, carbon trading, prosumer, bi-level optimization

中图分类号:

TM73

张妍, 冷媛, 尚楠, 梁梓杨, 石昊, 罗钢. 考虑碳排放需求响应及碳交易的电力系统双层优化调度[J]. 电力建设, 2024, 45(5): 94-104.

ZHANG Yan, LENG Yuan, SHANG Nan, LIANG Ziyang, SHI Hao, LUO Gang. Bi-Level Optimal Scheduling of Power System Considering Carbon Demand Response and Carbon Trading[J]. ELECTRIC POWER CONSTRUCTION, 2024, 45(5): 94-104.

图/表 15

图1 双层调度框架

Fig.1 Bi-level scheduling framework

图2 模型求解流程

Fig.2 Model solving process

图3 改进的IEEE 33节点系统

Fig.3 Modified IEEE 33 bus system

表1 产消者资源设置

Table 1 Resource settings of prosumers

图4 负荷及可再生能源出力预测值

Fig.4 Forecast value of load and renewable energy output

图5 主网分时电价

Fig.5 Main grid time-of-day electricity price

表2 仿真参数

Table 2 Simulation parameters

表3 调度仿真结果美元

Table 3 Results of scheduling

图6 储能运行状态

Fig.6 Energy storage operational status

表4 产消者间碳配额交易量

Table 4 Volume of carbon allowances traded between prosumers

图7 系统09:00及12:00节点碳势

Fig.7 Nodal carbon potential of the system at 09:00 and 12:00

图8 场景1负荷响应情况

Fig.8 DR status in scenario 1

图9 场景4负荷响应情况

Fig.9 DR status in scenario 4

图10 基于动态碳势的需求响应价格

Fig.10 Price of DR based on dynamic carbon intensity

图11 系统总运行成本

Fig.11 Total operation costs of the system

参考文献 34

[1]	黄守军, 杨俊. 发电成本垂直差异电力市场概率发电: 基于大用户电量偏好视角[J]. 管理科学学报, 2020, 23(6): 18-43.
	HUANG Shoujun, YANG Jun. Probabilistic generating in the vertical generation cost-differentiated electricity market: a perspective from the large user’s generation capacity preference[J]. Journal of Management Sciences in China, 2020, 23(6): 18-43.
[2]	ZHANG Z, ZHOU M, YUAN B, et al. Multipath retrofit planning approach for coal-fired power plants in low-carbon power system transitions: Shanxi province case in China[J]. Energy, 2023, 275: 127502. doi: 10.1016/j.energy.2023.127502 URL
[3]	刘鹏, 崔雪. 双碳背景下考虑市场份额偏好的发电侧市场均衡分析[J]. 电力科学与技术学报, 2023, 38(2): 9-17, 39.
	LIU Peng, CUI Xue. Equilibrium analysis of power generation market considering market share preference un-der carbon-neutral goal[J]. Journal of Electric Power Science and Technology, 2023, 38(2): 9-17, 39.
[4]	李汪繁, 吴何来. 双碳目标下我国碳市场发展分析及建议[J]. 南方能源建设, 2022, 9(4): 118-126.
	LI Wangfan, WU Helai. Analysis and suggestions for the development of carbon emissions trading markets in China under carbon peak and neutrality goals[J]. Southern Energy Construction, 2022, 9(4): 118-126.
[5]	MA G L, LI J N, ZHANG X P. A review on optimal energy management of multimicrogrid system considering uncertainties[J]. IEEE Access, 2022, 10: 77081-77098. doi: 10.1109/ACCESS.2022.3192638 URL
[6]	HAMID K, SHAHRAM J. Multi-layer energy management of smart integrated-energy microgrid systems considering generation and demand-side flexibility[J]. Applied Energy, 2023, 339: 120984. doi: 10.1016/j.apenergy.2023.120984 URL
[7]	邵建林, 郑明辉, 郭宬昊, 等. 双碳目标下燃煤热电联产机组储能技术应用分析[J]. 南方能源建设, 2022, 9(3): 102-110.
	SHAO Jianlin, ZHENG Minghui, GUO Chenghao, et al. Application analysis of energy storage technology for coal-fired combined heat and power generation under carbon peak and neutrality goal[J]. Southern Energy Construction, 2022, 9(3): 102-110.
[8]	杨秀, 胡晓龙, 孙改平, 等. 考虑电能共享的楼宇虚拟电厂协调优化调度[J]. 电力科学与技术学报, 2022, 37(1): 96-105.
	YANG Xiu, HU Xiaolong, SUN Gaiping, et al. Coordinated optimization scheduling of building virtual power plant considering power sharing[J]. Journal of Electric Power Science and Technology, 2022, 37(1): 96-105.
[9]	胡静哲. 低碳背景下考虑主动配电网响应的电力系统协调调度研究[D]. 上海: 上海交通大学, 2019.
	HU Jingzhe. Research on coordinate optimal operation of power system considering active distribution network response under low-carbon environment[D]. Shanghai: Shanghai Jiao Tong University, 2019.
[10]	韩海腾, 魏恬恬, 周亦洲, 等. 考虑碳排放的含产消者多主体博弈协同调度策略研究[J]. 电网技术, 2022, 46(11): 4238-4248.
	HAN Haiteng, WEI Tiantian, ZHOU Yizhou, et al. Cooperative dispatch strategy of multi-agent gaming including prosumers considering carbon emission[J]. Power System Technology, 2022, 46(11): 4238-4248.
[11]	WANG R T, WEN X Y, WANG X Y, et al. Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading[J]. Applied Energy, 2022, 311: 118664. doi: 10.1016/j.apenergy.2022.118664 URL
[12]	AKULKER H, AYDIN E. Optimal design and operation of a multi-energy microgrid using mixed-integer nonlinear programming: impact of carbon cap and trade system and taxing on equipment selections[J]. Applied Energy, 2023, 330: 120313. doi: 10.1016/j.apenergy.2022.120313 URL
[13]	LI Z H, ZHAO B, CHEN Z, et al. Low-carbon operation method of microgrid considering carbon emission quota trading[J]. Energy Reports, 2023, 9: 379-387.
[14]	WOO C, CHEN Y, ZARNIKAU J, et al. Carbon trading’s impact on California’s real-time electricity market prices[J]. Energy, 2018, 159:579-587. doi: 10.1016/j.energy.2018.06.188 URL
[15]	CHEN X Q, DONG W, YANG L F, et al. Scenario-based robust capacity planning of regional integrated energy systems considering carbon emissions[J]. Renewable Energy, 2023, 207: 359-375. doi: 10.1016/j.renene.2023.03.030 URL
[16]	WANG Z, WANG C. How carbon offsetting scheme impacts the duopoly output in production and abatement: analysis in the context of carbon cap-and-trade[J]. Journal of Cleaner Production, 2015, 103:715-723. doi: 10.1016/j.jclepro.2014.04.069 URL
[17]	FRANTIŠEK Z, MARTIN Š, VÁCLAV K. Multi-stage stochastic optimization of carbon risk management[J]. Expert Systems With Applications, 2022, 201: 117021.1-117021.12.
[18]	陈厚合, 茅文玲, 张儒峰, 等. 基于碳排放流理论的电力系统源-荷协调低碳优化调度[J]. 电力系统保护与控制, 2021, 49(10): 1-11.
	CHEN Houhe, MAO Wenling, ZHANG Rufeng, et al. Low-carbon optimal scheduling of a power system source-load considering coordination based on carbon emission flow theory[J]. Power System Protection and Control, 2021, 49(10): 1-11.
[19]	YANG C, LIU J J, LIAO H X, et al. An improved carbon emission flow method for the power grid with prosumers[J]. Energy Reports, 2023, 9:114-121.
[20]	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.
[21]	WANG H X, CAI X Y, LU X Y, et al. A novel load-side settlement mechanism based on carbon emission flow in electricity spot market[J]. Energy Reports, 2023, 9: 1057-1065. doi: 10.1016/j.egyr.2023.04.064 URL
[22]	陈修鹏, 李庚银, 夏勇. 基于主从博弈的新型城镇配电系统产消者竞价策略[J]. 电力系统自动化, 2019, 43(14): 97-104.
	CHEN Xiupeng, LI Gengyin, XIA Yong. Stackelberg game based bidding strategy for prosumers in new urban distribution system[J]. Automation of Electric Power Systems, 2019, 43(14): 97-104.
[23]	HEO K, KONG J, OH S, et al. Development of operator-oriented peer-to-peer energy trading model for integration into the existing distribution system[J]. International Journal of Electrical Power & Energy Systems, 2021, 125: 106488. doi: 10.1016/j.ijepes.2020.106488 URL
[24]	崇志强, 陈培育, 李树青, 等. 基于合作博弈论的P2P电力交易方法[J]. 电力系统及其自动化学报, 2021, 33(12): 87-92, 100.
	CHONG Zhiqiang, CHEN Peiyu, LI Shuqing, et al. P2P energy trading method based on cooperative game theory[J]. Proceedings of the CSU-EPSA, 2021, 33(12): 87-92, 100.
[25]	高赐威, 曹家诚, 吕冉, 等. 基于主从博弈的虚拟电厂内部购售电价格制定方法[J]. 电力需求侧管理, 2021, 23(6): 8-14.
	GAO Ciwei, CAO Jiacheng, LYU Ran, et al. Method for determining the internal price of virtual power plant based on stackelberg game theory[J]. Power Demand Side Management, 2021, 23(6): 8-14.
[26]	顾欣, 王琦, 胡云龙, 等. 基于纳什议价的多微网综合能源系统分布式低碳优化运行策略[J]. 电网技术, 2022, 46(4): 1464-1482.
	GU Xin, WANG Qi, HU Yunlong, et al. Distributed low-carbon optimal operation strategy of multi-microgrids integrated energy system based on Nash bargaining[J]. Power System Technology, 2022, 46(4): 1464-1482.
[27]	梁宁, 方茜, 徐慧慧, 等. 基于节点碳势需求响应的电力系统双层优化调度[J/OL]. 电力系统自动化, 2023:1-21.(2023-05-25)[2023-09-12]. https://kns.cnki.net/kcms2/detail/32.1180.TP.20230522.1927.002.html.
	LIANG Ning, FANG Qian, XU Huihui, et al. Bi-level optimal dispatch of power system based on demand response considering nodal carbon intensity[J/OL]. Automation of Electric Power Systems, 2023:1-21. (2023-05-25)[2023-09-12]. https://kns.cnki.net/kcms2/detail/32.1180.TP.20230522.1927.002.html.
[28]	宋泽淏, 冯华, 陈晓刚, 等. 基于节点碳势的配电网分布式资源低碳调度策略[J]. 高电压技术, 2023, 49(6): 2320-2332.
	SONG Zehao, FENG Hua, CHEN Xiaogang, et al. Low-carbon scheduling strategy of distributed energy resources based on node carbon intensity for distribution networks[J]. High Voltage Engineering, 2023, 49(6): 2320-2332.
[29]	詹博淳, 冯昌森, 王晓晖, 等. 基于碳排放流模型的分布式产消者P2P电-碳交易机制[J/OL]. 上海交通大学学报, 2023: 1-21. (2023-07-27)[2023-09-12].https://doi.org/10.16183/j.cnki.jsjtu.2023.139.
	ZHAN Bochun, FENG Changsen, WANG Xiaohui, et al. A P2P electricity-carbon trading mechanism for distributed prosumers based on carbon emission flow model[J/OL]. Journal of Shanghai Jiaotong University, 2023:1-21. (2023-07-27)[2023-09-12]. https://doi.org/10.16183/j.cnki.jsjtu.2023.139.
[30]	芮涛, 李国丽, 王群京, 等. 配电侧多微电网日前电能交易纳什议价方法[J]. 电网技术, 2019, 43(7): 2576-2585.
	RUI Tao, LI Guoli, WANG Qunjing, et al. Nash bargaining method for multi-microgrid energy trading in distribution network[J]. Power System Technology, 2019, 43(7): 2576-2585.
[31]	曹茜琳. 基于纳什议价博弈的用户侧共享储能优化配置研究[D]. 武汉: 中国地质大学, 2022.
	CAO Xilin. Research on Optimal Configuration of User-side Shared Energy Storage based on Nash Bargaining Game[D]. Wuhan: China University of Geosciences, 2022.
[32]	吴锦领, 楼平, 管敏渊, 等. 基于非对称纳什谈判的多微网电能共享运行优化策略[J]. 电网技术, 2022, 46(7): 2711-2723.
	WU Jinling, LOU Ping, GUAN Minyuan, et al. Operation optimization strategy of multi-microgrids energy sharing based on asymmetric Nash bargaining[J]. Power System Technology, 2022, 46(7): 2711-2723.
[33]	WANG Y Q, QIU J, TAO Y C, et al. Carbon-oriented operational planning in coupled electricity and emission trading markets[J]. IEEE Transactions on Power Systems, 2020, 35(4): 3145-3157. doi: 10.1109/TPWRS.59 URL
[34]	张菁, 林毓军, 齐晓光, 等. 考虑碳税与碳交易替代效应的电力系统低碳经济调度方法[J]. 电力建设, 2022, 43(6): 1-11. doi: 10.12204/j.issn.1000-7229.2022.06.001
	ZHANG Jing, LIN Yujun, QI Xiaoguang, et al. Low-carbon economic dispatching method for power system considering the substitution effect of carbon tax and carbon trading[J]. Electric Power Construction, 2022, 43(6): 1-11. doi: 10.12204/j.issn.1000-7229.2022.06.001

考虑碳排放需求响应及碳交易的电力系统双层优化调度

Bi-Level Optimal Scheduling of Power System Considering Carbon Demand Response and Carbon Trading

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