碳—绿色证书交易机制下考虑回收P2G余热和需求响应的PIES优化调度

doi:10.12204/j.issn.1000-7229.2023.03.003

电力建设 ›› 2023, Vol. 44 ›› Issue (3): 25-35.doi: 10.12204/j.issn.1000-7229.2023.03.003

• 综合多元能源及信息技术的能源互联网规划与运行·栏目主持刘洋副教授、韩富佳博士· • 上一篇下一篇

碳—绿色证书交易机制下考虑回收P2G余热和需求响应的PIES优化调度

原希尧¹(), 王关涛¹(), 朱若源¹(), 白星振¹(), 葛磊蛟²(), 李顾辉¹()

1.山东科技大学电气与自动化工程学院, 山东省青岛市 266590
2.智能电网教育部重点实验室(天津大学), 天津市 300072

收稿日期:2022-11-23 出版日期:2023-03-01 发布日期:2023-03-02
作者简介:原希尧(1998),男,硕士研究生,主要研究方向为综合能源系统的规划和运行,E-mail:Whitaker012@163.com
王关涛(1998),男,硕士研究生,主要研究方向为区域综合能源系统运行优化,E-mail:1539372350@qq.com
朱若源(1997),男,硕士研究生,主要研究方向为综合能源系统的优化和运行,E-mail:982827570@qq.com
白星振(1977),男,博士,副教授,主要研究方向为智能电网状态估计、综合能源系统优化运行,E-mail:xzbai@163.com
葛磊蛟(1984),男,博士,副教授,主要从事智能配电网态势感知、云计算和大数据方面的研究工作,E-mail: legendglj99@tju.edu.cn
李顾辉(1998),男,硕士研究生,主要研究方向为配电网状态估计,E-mail:lgh_sdust@163.com
基金资助:
国家自然科学基金资助项目(52277118);电网安全与节能国家重点实验室开放基金资助项目(YDB51202201356)

Optimal Scheduling of Park Integrated Energy System with P2G Waste Heat Recovery and Demand Response under Carbon-Green Certificate Trading Mechanism

YUAN Xiyao¹(), WANG Guantao¹(), ZHU Ruoyuan¹(), BAI Xingzhen¹(), GE Leijiao²(), LI Guhui¹()

1. School of Electrical and Automation Engineering, Shandong University of Science and Technology, Qingdao 266590, Shandong Province, China
2. Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China

Received:2022-11-23 Online:2023-03-01 Published:2023-03-02
Supported by:
National Natural Science Foundation of China(52277118);State Key Laboratory of Grid Security and Energy Conservation(YDB51202201356)

摘要/Abstract

摘要：

为进一步促进园区级综合能源系统(park integrated energy system,PIES)的可再生能源消纳和碳减排,优化园区级综合能源系统的运行总成本,提出一种碳-绿色证书交易机制下考虑回收电转气(power to gas,P2G)余热和需求响应的园区级综合能源系统优化调度模型。首先,考虑阶梯式碳交易机制和绿色证书交易制度,以促进可再生能源的消纳和碳减排。其次,引入回收余热的电转气设备,优化电-热-气耦合关系来提高系统消纳可再生能源和碳减排水平。然后,建立含可削减、转移、替代负荷的需求侧响应模型,指导用户的用能方式由高能耗、高污染向低碳、可持续转变。最后,以购能成本、弃风惩罚成本、需求响应补偿成本、阶梯式碳交易成本、绿色证书交易收益之和最小为目标,构建PIES优化调度模型。算例结果表明,该模型可以有效促进可再生能源消纳和碳减排并降低系统运行成本。

关键词: 园区级综合能源系统(PIES), 电转气(P2G), 需求响应, 碳交易, 绿色证书交易

Abstract:

In order to further promote the renewable energy consumption and carbon emission reduction of the park integrated energy system (PIES), and optimize the total operation cost of the PIES, this paper proposes a PIES optimization scheduling model considering the recovery of waste heat from power to gas (P2G) and demand response under the carbon-green certificate trading mechanism. Firstly, the stepwise carbon trading mechanism and green certificate trading system are considered to promote the consumption of renewable energy and carbon emission reduction. Secondly, the P2G equipment to recover waste heat is introduced, and the electric-heat-gas coupling relationship is optimized to improve the system's renewable energy consumption and carbon emission reduction level. Then, a demand-side response model including reduced, transferred and substituted loads is established to guide users to change their energy use mode from high energy consumption and high pollution to low-carbon and sustainable. Finally, the PIES optimization scheduling model is constructed to minimize the sum of energy purchase cost, wind curtailment penalty cost, demand response compensation cost, stepped carbon trading cost and green certificate trading revenue. The simulation results show that the model can effectively promote the renewable energy consumption and carbon emission reduction and reduce the system operation cost.

Key words: park integrated energy system (PIES), power to gas (P2G), demand response, carbon trading, green certificate trading

中图分类号:

TM73

原希尧, 王关涛, 朱若源, 白星振, 葛磊蛟, 李顾辉. 碳—绿色证书交易机制下考虑回收P2G余热和需求响应的PIES优化调度[J]. 电力建设, 2023, 44(3): 25-35.

YUAN Xiyao, WANG Guantao, ZHU Ruoyuan, BAI Xingzhen, GE Leijiao, LI Guhui. Optimal Scheduling of Park Integrated Energy System with P2G Waste Heat Recovery and Demand Response under Carbon-Green Certificate Trading Mechanism[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(3): 25-35.

图/表 13

图1 园区级综合能源系统结构示意图

Fig.1 Structure diagram of a PIES

图2 回收P2G余热促进风电消纳机理

Fig.2 Mechanism of recovering P2G waste heat to promote wind power consumption

图3 PIES风电出力和多元负荷预测

Fig.3 PIES wind power output and multiple load forecasting

表1 分时电价、天然气价格

Table 1 Time-of-use electricity price and natural gas price

表2 设备参数

Table 2 Equipment parameters

表3 储能参数

Table 3 Parameters of energy storage devices

表4 实际碳排放参数

Table 4 Actual carbon emission parameters

表5 Results of scheduling in 8 scenarios 元

Table 5

图4 场景4电、热功率调度结果

Fig.4 Result of electrical and thermal power scheduling in Scenario 4

图5 场景5电、热功率调度结果

Fig.5 Result of electrical and thermal power scheduling in Scenario 5

图6 场景6需求响应调度结果

Fig.6 Result of demand response scheduling in Scenario 6

图7 场景7需求响应调度结果

Fig.7 Result of demand response scheduling in Scenario 7

图8 场景8需求响应调度结果

Fig.8 Result of demand response scheduling in Scenario 8

参考文献 21

[1]	马迪, 高红均, 张江林, 等. 考虑风电不确定性的电-气综合能源系统协调优化[J]. 智慧电力, 2022, 50(11):33-40.
	MA Di, GAO Hongjun, ZHANG Jianglin, et al. Coordinated optimization of power-gas integrated energy system considering wind power uncertainty[J]. Smart Power, 2022, 50(11):33-40.
[2]	骆钊, 卢涛, 马瑞, 等. 可再生能源配额制下多园区综合能源系统优化调度[J]. 电力自动化设备, 2021, 41(4): 8-14.
	LUO Zhao, LU Tao, MA Rui, et al. Optimal scheduling of multipark integrated energy system under renewable portfolio standard[J]. Electric Power Automation Equipment, 2021, 41(4): 8-14.
[3]	陈锦鹏, 胡志坚, 陈嘉滨, 等. 考虑阶梯式碳交易与供需灵活双响应的综合能源系统优化调度[J]. 高电压技术, 2021, 47(09): 3094-3106.
	CHEN Jinpeng, HU Zhijian, Chen Jiabin, et al. Optimal dispatch of integrated energy system considering tiered carbon trading and flexible dual response of supply and demand[J]. High Voltage Engineering, 2021, 47(09): 3094-3106.
[4]	杨智麟, 张英敏, 何川. 基于风功率间歇性的多区域综合能源系统两阶段分布鲁棒协同优化调度的研究[J]. 智慧电力, 2021, 49(10):59-67.
	YANG Zhilin, ZHANG Yingmin, HE Chuan. Two-stage distributed robust coordinated optimal dispatch for multi-regional integrated energy system considering intermittent wind power[J]. Smart Power, 2021, 49(10):59-67.
[5]	张明光, 王文婷, 陈大为. 基于合作博弈的多区域综合能源系统优化调度[J]. 智慧电力, 2022, 50(10):102-108.
	ZHANG Mingguan, WANG Wenting, CHEN Dawei. Optimal dispatching of multi-regional integrated energy system based on cooperative game[J]. Smart Power, 2022, 50(10):102-108.
[6]	魏震波, 马新如, 郭毅, 等. 碳交易机制下考虑需求响应的综合能源系统优化运行[J]. 电力建设, 2022, 43(1): 1-9. doi: 10.12204/j.issn.1000-7229.2022.01.001
	WEI Zhenbo, MA Xinru, GUO Yi, et al. Optimized operation of integrated energy system considering demand response under carbon trading mechanism[J]. Electric Power Construction, 2022, 43(1): 1-9. doi: 10.12204/j.issn.1000-7229.2022.01.001
[7]	胡静哲, 王旭, 蒋传文, 等. 考虑区域碳排放均衡性的电力系统最优阶梯碳价[J]. 电力系统自动化, 2020, 44(6): 98-105.
	HU Jingzhe, WANG Xu, JIANG Chuanwen, et al. Optimal tiered carbon price of power system considering equilibrium of regional carbon emission[J]. Automation of Electric Power Systems, 2020, 44(6): 98-105.
[8]	卢志刚, 郭凯, 闫桂红, 等. 考虑需求响应虚拟机组和碳交易的含风电电力系统优化调度[J]. 电力系统自动化, 2017, 41(15): 58-65.
	LU Zhigang, GUO Kai, YAN Guihong et al. Optimal dispatch of power system integrated with wind power considering virtual generator units of demand response and carbon trading[J]. Automation of Electric Power Systems, 2017, 41(15): 58-65.
[9]	秦婷, 刘怀东, 王锦桥, 等. 基于碳交易的电-热-气综合能源系统低碳经济调度[J]. 电力系统自动化, 2018, 42(14): 8-13,22.
	QIN Ting, LIU Huaidong, WANG Jinqiao, et al. Carbon trading based low-carbon economic dispatch for integrated electricity-heat-gas energy system[J]. Automation of Electric Power Systems, 2018, 42(14): 8-13,22.
[10]	陈锦鹏, 胡志坚, 陈颖光, 等. 考虑阶梯式碳交易机制与电制氢的综合能源系统热电优化[J]. 电力自动化设备, 2021, 41(9): 48-55.
	CHEN Jinpeng, HU Zhijian, CHEN Yingguang, et al. Thermoelectric optimization of integrated energy system considering ladder-type carbon trading mechanism and electric hydrogen production[J]. Electric Power Automation Equipment. 2021, 41(9):48-55.
[11]	CHEN C, ZHU Y, ZENG X T, et al. Analyzing the carbon mitigation potential of tradable g-reen certificates based on a TGC-FFSRO model:a case study in the Beijing-Tianjin-Hebei region,China[J]. Science of the Total Environment, 2018, 630: 469-486. doi: 10.1016/j.scitotenv.2018.02.103 URL
[12]	董帅, 王成福, 梁军, 等. 计及电转气运行成本的综合能源系统多目标日前优化调度[J]. 电力系统自动化, 2018, 42(11): 8-15.
	DONG Shuai, WANG Chengfu, LIANG Jun, et al. Multi-objective optimal day-ahead dispatch of integrated energy system considering power-to-gas operation cost[J]. Automation of Electric Po-wer Systems, 2018, 42(11): 8-15.
[13]	凌梓, 杨秀, 李莉华, 等. 含电转气多能系统的协调控制与优化调度[J]. 太阳能学报, 2020, 41(12): 9-17.
	LING Zi, YANG Xiu, LI Lihua, et al. Coordinated control and optimal scheduling of multi energy systems with power-to-gas devices[J]. Acta Energiae Solaris Sinica, 2020, 41(12): 9-17.
[14]	李东东, 张凯, 姚寅, 等. 基于信息间隙决策理论的电动汽车聚合商日前需求响应调度策略[J]. 电力系统保护与控制, 2022, 50(24):101-111.
	LI Dongdong, ZHANG Kai, YAO Yin, et al. Day-ahead demand response scheduling strategy of an electric vehicle aggregator based on information gap decision theory[J]. Power System Protection and Control, 2022, 50(24):101-111.
[15]	贠保记, 张恩硕, 张国, 等. 考虑综合需求响应与“双碳”机制的综合能源系统优化运行[J]. 电力系统保护与控制, 2022, 50(22):11-19.
	YUN Baoji, ZHANG Enshuo, ZHANG Guo, et al. Optimal operation of an integrated energy system considering integrated demand response and a "dual carbon "mechanism[J]. Power System Protection and Control, 2022, 50(22):11-19.
[16]	LIU C, LI Y, WANG Q S, et al. Optimal configuration of park-level integrated energy system considering integrated demand response and construction time sequence[J]. Energy Reports, 2022, 8(5): 1174-1180.
[17]	LV G Y, CAO B, LI J, et al. Optimal scheduling of integrated energy system under the background of carbon neutrality[J]. Energy Reports, 2022, 8(5): 1236-1248.
[18]	LI Y Q, ZHANG J, MA Z J, et al. An energy management optimization method for community integrated energy system based on user dominated demand side response[J]. Energies, 2021, 14: 4398. doi: 10.3390/en14154398 URL
[19]	LIU X R, SUN S L, Sun Q Y, et al. Time scale economic dispatch of electricity-heat integrated system based on users’ thermal comfort[J]. Energies, 2020, 13: 5505. doi: 10.3390/en13205505 URL
[20]	HE L C, LU Z G, GENG L J, et al. Environmental economic dispatch of integrated regional energy system considering integrated demand response[J]. International Journal of Electrical Power & Energy Systems, 2020, 116: 105525. doi: 10.1016/j.ijepes.2019.105525 URL
[21]	崔杨, 郭福音, 付小标, 等. 供用能转换促进风电消纳的综合能源系统源荷协调优化调度[J]. 电网技术, 2022, 46(4): 1437-1447.
	CUI Yang, GUO Fuyin, FU Xiaobiao, et al. Source-load coordinated optimal dispatch of integrated energy system based on conversion of energy supply and use to promote wind power accommodation[J]. Power System Technology, 2022, 46(4): 1437-1447.

碳—绿色证书交易机制下考虑回收P2G余热和需求响应的PIES优化调度

Optimal Scheduling of Park Integrated Energy System with P2G Waste Heat Recovery and Demand Response under Carbon-Green Certificate Trading Mechanism

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 13

参考文献 21

相关文章 15

编辑推荐

Metrics

本文评价

[1]	姚寅, 朱烨冬, 李东东, 周波, 林顺富. 基于决策实验室算法-对抗解释结构模型的电动汽车多场景需求响应策略分析[J]. 电力建设, 2023, 44(3): 93-104.
[2]	樊伟, 李旭东, 王尧, 李祥光, 王玉洁, 谭忠富, 鞠立伟. 新型电力系统灵活性资源聚合两阶段调度优化模型[J]. 电力建设, 2023, 44(2): 25-37.
[3]	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.
[4]	于昊正, 赵寒杰, 李科, 朱星旭, 皇甫霄文, 樊江川, 李翠萍, 李军徽. 计及需求响应的分布式光伏集群承载能力评估[J]. 电力建设, 2023, 44(2): 122-130.
[5]	余彬, 翁利国, 练德强, 王思斌, 黄媛, 姚昊天. 计及价格引导机制的含分布式资源园区协调运行策略[J]. 电力建设, 2023, 44(2): 145-154.
[6]	张尧翔, 刘文颖, 庞清仑, 李亚楼, 安宁, 李芳. 计及综合需求响应参与消纳受阻新能源的多时间尺度优化调度策略[J]. 电力建设, 2023, 44(1): 1-11.
[7]	温钱惠, 魏震波, 张勇林, 梁政, 何永祥. 考虑保险机制与用户需求响应的售电公司优化运营[J]. 电力建设, 2023, 44(1): 47-54.
[8]	刘至纯, 李华强, 王俊翔, 陆杨, 游祥, 何永祥. 基于多时间尺度综合需求响应策略的综合能源系统优化运行[J]. 电力建设, 2022, 43(9): 54-65.
[9]	杨志豪, 刘沆, 文明, 赵海彭, 廖菁, 苗世洪. 考虑综合需求响应混合不确定性的综合能源系统优化调度策略[J]. 电力建设, 2022, 43(9): 66-76.
[10]	范辉, 罗蓬, 王弘利, 梁纪峰, 李乾, 杨军, 吴赋章. 基于社交网上演化博弈的光伏台区用户需求响应特性研究[J]. 电力建设, 2022, 43(8): 150-158.
[11]	李鹏, 余晓鹏, 张艺涵, 周青青, 田春筝, 乔慧婷. 计及碳捕集和电转气的农村虚拟电厂多目标随机调度优化模型[J]. 电力建设, 2022, 43(7): 24-36.
[12]	张菁, 林毓军, 齐晓光, 苗世洪, 张倩茅, 董家盛, 陈宇. 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.
[13]	张菁, 林毓军, 齐晓光, 苗世洪, 张倩茅, 董家盛, 陈宇. 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.
[14]	杨雪, 金孝俊, 王海洋, 魏翼飞. 基于区块链的绿证和碳交易市场联合激励机制[J]. 电力建设, 2022, 43(6): 24-33.
[15]	刁利, 李光, 宋雪莹, 德格吉日夫, 谭忠富. 新能源分比例渗透下基于博弈的多主体效益综合评估方法[J]. 电力建设, 2022, 43(6): 43-55.