上海交通大学学报

上海交通大学学报 >

2024 , Vol. 58 >Issue 9: 1297 - 1308

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.494

新型电力系统与综合能源

综合能源系统电气热多能量流建模及优化

  • 李冰洁 ,
  • 袁晓昀 ,
  • 史静 ,
  • 徐华池 ,
  • 罗子萱
展开
  • 1.国网江苏省电力有限公司经济技术研究院,南京 210000
    2.清华四川能源互联网研究院,成都 610042
李冰洁(1990—),硕士,从事能源经济研究.
徐华池,博士,助理研究员,电话(Tel.):028-61956712;E-mail:xuhuachi0307@163.com.

收稿日期: 2022-12-02

  修回日期: 2023-04-24

  录用日期: 2023-05-08

  网络出版日期: 2023-05-15

基金资助

国网江苏省电力有限公司科技项目(J2021079)

收起

Multi-Energy Flow Modeling and Optimization of Electric-Gas-Thermal Integrated Energy System

  • LI Bingjie ,
  • YUAN Xiaoyun ,
  • SHI Jing ,
  • XU Huachi ,
  • LUO Zixuan
Expand
  • 1. Economic Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210000, China
    2. Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610042, China

Received date: 2022-12-02

  Revised date: 2023-04-24

  Accepted date: 2023-05-08

  Online published: 2023-05-15

Fold

摘要

针对区域综合能源系统中电、气、热多种能源形式的转换严重影响系统运行的经济性,建立区域综合能源系统(RIES)能量流数学模型和优化模型,以提升系统的经济性和对可再生能源的消纳.建立系统中各类能源转换设备数学模型,确定电力、燃气、热能3种能源传输网络约束条件;以经济性运行为首要目标,兼顾低碳排放和提高可再生能源消纳率的目标函数,构建RIES多能流优化模型.在大型综合能源系统基础上,引入负荷侧需求响应,建立仿真模型.仿真结果表明,需求响应的引入提高了系统调度灵活性,减少了系统对储能设备的依赖,有效降低了用户的用能成本.

关键词： 区域综合能源系统; 多能流; 线性化; 需求响应

本文引用格式

李冰洁 , 袁晓昀 , 史静 , 徐华池 , 罗子萱 . 综合能源系统电气热多能量流建模及优化[J]. 上海交通大学学报, 2024 , 58(9) : 1297 -1308 . DOI: 10.16183/j.cnki.jsjtu.2022.494

Abstract

In view of the fact that the conversion of various energy forms such as electricity, gas, and heat in the regional integrated energy system (RIES) seriously affects the economy of the system operation, a mathematical model and an optimization model of RIES energy flow are established to improve the economy of the system and the absorption of renewable energy. First, the mathematical models of all kinds of energy conversion equipment in the system are established to determine the constraints of three kinds of energy transmission networks, namely electricity, natural gas, and heat. Then, taking economic operation as the primary objective, and taking into account the objective function of low carbon emissions and increasing the uptake rate of renewable energy, the RIES multi-energy flow optimization model is constructed. Finally, based on the large-scale integrated energy system, the load side demand response is introduced and the simulation model is established. The simulation results show that the introduction of demand response improves the flexibility of system scheduling, reduces the dependence of the system on energy storage equipment, and effectively reduces the energy consumption cost of users.

Key words： regional integrated energy system (RIES); multi-energy flow; linearization; demand response

参考文献

[1] 邱雨微, 郑徐跃, 詹翔燕, 等. 耦合可再生能源的分布式联供系统设计及运行策略优化[J]. 厦门大学学报(自然科学版), 2019, 58(1): 103-110.
  QIU Yuwei, ZHENG Xuyue, ZHAN Xiangyan, et al. The optimal design and operation strategy for combined cooling, heating and power system coupled with renewable energies[J]. Journal of Xiamen University (Natural Science), 2019, 58(1): 103-110.
[2] CHANG H W, DUAN C, XU X X, et al. Technical performance analysis of a micro-combined cooling, heating and power system based on solar energy and high temperature PEMFC[J]. International Journal of Hydrogen Energy, 2019, 44(38): 21080-21089.
[3] 鲁宗相, 李海波, 乔颖. 含高比例可再生能源电力系统灵活性规划及挑战[J]. 电力系统自动化, 2016, 40(13): 147-158.
  LU Zongxiang, LI Haibo, QIAO Ying. Power system flexibility planning and challenges considering high proportion of renewable energy[J]. Automation of Electric Power Systems, 2016, 40(13): 147-158.
[4] 李洋, 吴鸣, 周海明, 等. 基于全能流模型的区域多能源系统若干问题探讨[J]. 电网技术, 2015, 39(8): 2230-2237.
  LI Yang, WU Ming, ZHOU Haiming, et al. Study on some key problems related to regional multi energy system based on universal flow model[J]. Power System Technology, 2015, 39(8): 2230-2237.
[5] ELLEN S, ROSE AMY D, MICHELLE G. The third industrial revolution: How lateral power is transforming energy, the economy, and the world[J]. Adult Learning, 2013, 24(1): 50-51.
[6] 艾芊, 郝然. 多能互补、集成优化能源系统关键技术及挑战[J]. 电力系统自动化, 2018, 42(4): 2-10.
  AI Qian, HAO Ran. Key technologies and challenges for multi-energy complementarity and optimization of integrated energy system[J]. Automation of Electric Power Systems, 2018, 42(4): 2-10.
[7] 于潇涵, 赵晋泉. 含P2H、P2G电-气-热综合能源系统多能流算法[J]. 电力建设, 2018, 39(12): 13-21.
  YU Xiaohan, ZHAO Jinquan. Heat-gas-power flow calculation method for integrated energy system containing P2H and P2G[J]. Electric Power Construction, 2018, 39(12): 13-21.
[8] 王英瑞, 曾博, 郭经, 等. 电-热-气综合能源系统多能流计算方法[J]. 电网技术, 2016, 40(10): 2942-2950.
  WANG Yingrui, ZENG Bo, GUO Jing, et al. Calculation method of multi-energy flow in electric-thermal-gas integrated energy system[J]. Power System Technology, 2016, 40(10): 2942-2950.
[9] 闵庆久, 马兆兴, 马英姿. 基于PSO-Newton法的电-气综合能源系统能流计算[J]. 电力工程技术, 2021, 40(1): 33-39.
  MIN Qingjiu, MA Zhaoxing, MA Yingzi. Energy flow calculation of integrated power-gas energy system based on PSO-Newton method[J]. Electric Power Engineering Technology, 2021, 40(1): 33-39.
[10] 董帅, 王成福, 徐士杰, 等. 计及网络动态特性的电-气-热综合能源系统日前优化调度[J]. 电力系统自动化, 2018, 42(13): 12-19.
  DONG Shuai, WANG Chengfu, XU Shijie, et al. Day-ahead optimal scheduling of electricity-gas-heat integrated energy system considering dynamic characteristics of networks[J]. Automation of Electric Power Systems, 2018, 42(13): 12-19.
[11] 卫志农, 仲磊磊, 薛溟枫, 等. 基于数据驱动的电-热互联综合能源系统线性化潮流计算[J]. 电力自动化设备, 2019, 39(8): 31-37.
  WEI Zhinong, ZHONG Leilei, XUE Mingfeng, et al. Linearization flow calculation for integrated electricity-heat energy system based on data-driven[J]. Electric Power Automation Equipment, 2019, 39(8): 31-37.
[12] 贾云辉, 张峰. 考虑分布式风电接入下的区域综合能源系统多元储能双层优化配置研究[J]. 可再生能源, 2019, 37(10): 1524-1532.
  JIA Yunhui, ZHANG Feng. A bi-level optimal configuration of multiple storage in reginal integrated energy system with distribution wind power inclusion[J]. Renewable Energy Resources, 2019, 37(10): 1524-1532.
[13] 钟永洁, 孙永辉, 谢东亮, 等. 含电-热-气-冷子系统的区域综合能源系统多场景优化调度[J]. 电力系统自动化, 2019, 43(12): 76-84.
  ZHONG Yongjie, SUN Yonghui, XIE Dongliang, et al. Multi-scenario optimal dispatch of regional integrated energy system with power-heating-gas-cooling subsystems[J]. Automation of Electric Power Systems, 2019, 43(12): 76-84.
[14] 徐宪东. 电/气/热微型能源系统的建模、仿真与能量管理研究[D]. 天津: 天津大学, 2014.
  XU Xiandong. Research on modeling, simulation and energy management of electric/gas/thermal micro energy system[D]. Tianjin: Tianjin University, 2014.
[15] MOEINI-AGHTAIE M, ABBASPOUR A, FOTUHI-FIRUZABAD M, et al. A decomposed solution to multiple-energy carriers optimal power flow[J]. IEEE Transactions on Power Systems, 2014, 29(2): 707-716.
[16] SHABANPOUR-HAGHIGHI A, SEIFI A R. Simultaneous integrated optimal energy flow of electricity, gas, and heat[J]. Energy Conversion and Management, 2015, 101: 579-591.
[17] 林威, 靳小龙, 穆云飞, 等. 区域综合能源系统多目标最优混合潮流算法[J]. 中国电机工程学报, 2017, 37(20): 5829-5839.
  LIN Wei, JIN Xiaolong, MU Yunfei, et al. Multi-objective optimal hybrid power flow algorithm for integrated local area energy system[J]. Proceedings of the CSEE, 2017, 37(20): 5829-5839.
[18] MANCARELLA P. MES (multi-energy systems): An overview of concepts and evaluation models[J]. Energy, 2014, 65: 1-17.
[19] 于东立, 曹军, 屠聪为, 等. 考虑线性化网络约束的电-热多能源系统最优能量流分析[J]. 中国电机工程学报, 2019, 39(7): 1933-1943.
  YU Dongli, CAO Jun, TU Congwei, et al. Optimal energy flow analysis of electro-thermal multi-energy system considering linearization network constraints[J]. Proceedings of the CSEE, 2019, 39(7): 1933-1943.
[20] 邵世圻, 戴赛, 胡林献, 等. 计及热网特性的电热联合系统调度方法[J]. 电力系统保护与控制, 2018, 46(10): 24-30.
  SHAO Shiqi, DAI Sai, HU Linxian, et al. Research on heat-electricity combined scheduling method considering the characteristics of the heating network[J]. Power System Protection and Control, 2018, 46(10): 24-30.
[21] 刘述欣, 戴赛, 胡林献, 等. 计及回水管网热损失的电热联合系统潮流模型及算法[J]. 电力系统自动化, 2018, 42(4): 77-81.
  LIU Shuxin, DAI Sai, HU Linxian, et al. Power flow model and algorithm of combined power and heat system considering heat loss in return pipe network[J]. Automation of Electric Power Systems, 2018, 42(4): 77-81.
[22] BORRAZ-SáNCHEZ C, BENT R, BACKHAUS S, et al. Convex relaxations for gas expansion planning[J]. INFORMS Journal on Computing, 2016, 28(4): 645-656.
[23] 刘天琪, 张琪, 何川. 考虑气电联合需求响应的气电综合能源配网系统协调优化运行[J]. 中国电机工程学报, 2021, 41(5): 1664-1676.
  LIU Tianqi, ZHANG Qi, HE Chuan. Coordinated and optimal operation of gas-electricity comprehensive energy distribution network system considering gas-electricity joint demand response[J]. Proceedings of the CSEE, 2021, 41(5): 1664-1676.
[24] CORREA-POSADA C M, SáNCHEZ-MARTíN P. Gas network optimization: A comparison of piecewise linear models[J]. Optimization Online, 2014: 1-24.
Options
文章导航

/

〈 〉