Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2025 , Vol. 59 >Issue 5: 569 - 579

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.590

New Type Power System and the Integrated Energy

Quantitative Method of Response Value of Integrated Energy Equipment Based on Global Sensitivity Analysis

  • HUANG Yixiang ,
  • DOU Xun ,
  • LI Linxi ,
  • YANG Hanyu ,
  • YU Jiancheng ,
  • HUO Xianxu
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  • 1. College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China
    2. State Grid Tianjin Electric Power Company Electric Power Research Institute, Tianjin 300384, China
    3. State Grid Tianjin Electric Power Company, Tianjin 300010, China

Received date: 2023-11-20

  Revised date: 2024-01-03

  Accepted date: 2024-01-24

  Online published: 2024-02-27

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Abstract

Integrated demand response is an effective strategy for improving energy efficiency and facilitating the integration of renewable clean energy, of which the essence is to guide users into bidirectional interactions between source and load by the multi-energy coupling capabilities of integrated energy devices. Accurately evaluating the response values of integrated energy devices is essential for improving the operational control level of integrated energy systems. Therefore, this paper proposes a method for quantifying the response value of integrated energy devices based on Sobol’s global sensitivity analysis. First, an integrated energy system generalized optimization model is developed with the objective function of minimizing total operating costs while considering multiple types of integrated demand response. A surrogate model for the integrated energy system is conducted based on particle swarm optimization-backpropagation (PSO-BP) neural network. The Sobol’s global sensitivity analysis is then applied to quantify the global sensitivity indices of device efficiency parameters in terms of cost, user satisfaction, integrated energy utilization rate, and electricity substitution rate, which are used to assess the response value of integrated energy devices and identify key devices influencing system states. Finally, simulations based on a commercial park in Jiangsu Province are conducted to determine the global sensitivity coefficients of the efficiency for each integrated energy device. The effect of various device efficiencies on system states is investigated with the response value of integrated energy devices calculated precisely, and the effectiveness of the proposed method is verified.

Key words： global sensitivity analysis; value of integrated demand response; integrated energy equipment; integrated energy system; particle swarm optimization-backpropagation (PSO-BP) neural network

Cite this article

HUANG Yixiang , DOU Xun , LI Linxi , YANG Hanyu , YU Jiancheng , HUO Xianxu . Quantitative Method of Response Value of Integrated Energy Equipment Based on Global Sensitivity Analysis[J]. Journal of Shanghai Jiaotong University, 2025 , 59(5) : 569 -579 . DOI: 10.16183/j.cnki.jsjtu.2023.590

References

[1] 辛保安, 陈梅, 赵鹏, 等. 碳中和目标下考虑供电安全约束的我国煤电退减路径研究[J]. 中国电机工程学报, 2022, 42(19): 6919-6931.
  XIN Baoan, CHEN Mei, ZHAO Peng, et al. Research on coal power generation reduction path considering power supply adequacy constraints under carbon neutrality target in China[J]. Proceedings of the CSEE, 2022, 42(19): 6919-6931.
[2] 司方远, 张宁, 韩英华, 等. 面向多元灵活资源聚合的区域综合能源系统主动调节能力评估与优化: 关键问题与研究架构[J]. 中国电机工程学报, 2024, 44(6): 2097-2119.
  SI Fangyuan, ZHANG Ning, HAN Yinghua, et al. Fundamental problems and research framework for assessment and optimization of the functional regulation capacity of the regional integrated energy system under the aggregation of diversified and flexible resources[J]. Proceedings of the CSEE, 2024, 44(6): 2097-2119.
[3] 黄武靖, 张宁, 董瑞彪, 等. 多能源网络与能量枢纽联合规划方法[J]. 中国电机工程学报, 2018, 38(18): 5425-5437.
  HUANG Wujing, ZHANG Ning, DONG Ruibiao, et al. Coordinated planning of multiple energy networks and energy hubs[J]. Proceedings of the CSEE, 2018, 38(18): 5425-5437.
[4] LIU N, WANG J, WANG L F. Hybrid energy sharing for multiple microgrids in an integrated heat-electricity energy system[J]. IEEE Transactions on Sustainable Energy, 2019, 10(3): 1139-1151.
[5] 韩肖清, 李廷钧, 张东霞, 等. 双碳目标下的新型电力系统规划新问题及关键技术[J]. 高电压技术, 2021, 47(9): 3036-3046.
  HAN Xiaoqing, LI Tingjun, ZHANG Dongxia, et al. New issues and key technologies of new power system planning under double carbon goals[J]. High Voltage Engineering, 2021, 47(9): 3036-3046.
[6] KARIMI H, JADID S. Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework[J]. Energy, 2020, 195: 116992.
[7] 赵海彭, 苗世洪, 李超, 等. 考虑冷热电需求耦合响应特性的园区综合能源系统优化运行策略研究[J]. 中国电机工程学报, 2022, 42(2): 573-589.
  ZHAO Haipeng, MIAO Shihong, LI Chao, et al. Research on optimal operation strategy for park-level integrated energy system considering cold-heat-electric demand coupling response characteristics[J]. Proceedings of the CSEE, 2022, 42(2): 573-589.
[8] WANG L, HOU C Q, YE B, et al. Optimal operation analysis of integrated community energy system considering the uncertainty of demand response[J]. IEEE Transactions on Power Systems, 2021, 36(4): 3681-3691.
[9] 李天格, 胡志坚, 陈志, 等. 计及电-气-热-氢需求响应的综合能源系统多时间尺度低碳运行优化策略[J]. 电力自动化设备, 2023, 43(1): 16-24.
  LI Tiange, HU Zhijian, CHEN Zhi, et al. Multi-time scale low-carbon operation optimization strategy of integrated energy system considering electricity-gas-heat-hydrogen demand response[J]. Electric Power Automation Equipment, 2023, 43(1): 16-24.
[10] WANG L Y, LIN J L, DONG H Q, et al. Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system[J]. Energy, 2023, 270: 126893.
[11] 程杉, 陈诺, 徐建宇, 等. 考虑综合需求响应的楼宇综合能源系统能量管理优化[J]. 电力工程技术, 2023, 42(2): 40-47.
  CHENG Shan, CHEN Nuo, XU Jianyu, et al. Optimal energy management of residential integrated energy system with consideration of integrated demand response[J]. Electric Power Engineering Technology, 2023, 42(2): 40-47.
[12] PANG Y X, HE Y X, JIAO J, et al. Power load demand response potential of secondary sectors in China: The case of western Inner Mongolia[J]. Energy, 2020, 192: 116669.
[13] ZHU J, NIU J D, TIAN Z, et al. Rapid quantification of demand response potential of building HAVC system via data-driven model[J]. Applied Energy, 2022, 325: 119796.
[14] WANG Y L, LI F, YANG J L, et al. Demand response evaluation of RIES based on improved matter-element extension model[J]. Energy, 2020, 212: 118121.
[15] 黄莉, 周赣, 张娅楠, 等. 考虑贡献度的聚合商需求响应精准评估与动态激励决策[J]. 电力工程技术, 2022, 41(6): 21-29.
  HUANG Li, ZHOU Gan, ZHANG Yanan, et al. Accurate evaluation and dynamic incentive decision of aggregators’ demand response considering contribution degree[J]. Electric Power Engineering Technology, 2022, 41(6): 21-29.
[16] 郭尊, 李庚银, 周明, 等. 计及综合需求响应的商业园区能量枢纽优化运行[J]. 电网技术, 2018, 42(8): 2439-2448.
  GUO Zun, LI Gengyin, ZHOU Ming, et al. Optimal operation of energy hub in business park considering integrated demand response[J]. Power System Technology, 2018, 42(8): 2439-2448.
[17] 程浩忠, 胡枭, 王莉, 等. 区域综合能源系统规划研究综述[J]. 电力系统自动化, 2019, 43(7): 2-13.
  CHENG Haozhong, HU Xiao, WANG Li, et al. Review on research of regional integrated energy system planning[J]. Automation of Electric Power Systems, 2019, 43(7): 2-13.
[18] 李平姣, 钟文琪, 陈晓乐, 等. 600 MW S-CO2循环燃煤流化床锅炉热量分布及锅炉效率[J]. 中国电机工程学报, 2019, 39(7): 2080-2093.
  LI Pingjiao, ZHONG Wenqi, CHEN Xiaole, et al. Heat distribution and boiler efficiency of 600 MW coal-fired CFB boiler with S-CO2 power cycle[J]. Proceedings of the CSEE, 2019, 39(7): 2080-2093.
[19] TANG Y, REED P, WAGENER T, et al. Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation[J]. Hydrology & Earth System Sciences, 2007, 11(2): 793-817.
[20] 杨晶, 赵津蔓, 孟润泉, 等. 基于粒子群优化和卷积神经网络的电力系统运行状态辨识[J]. 电网技术, 2024, 48(1): 315-324.
  YANG Jing, ZHAO Jinman, MENG Runquan, et al. Power system operation state identification based on particle swarm optimization and convolutional neural network[J]. Power System Technology, 2024, 48(1): 315-324.
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