DISTRIBUTION NETWORK RESILIENCE IMPROVEMENT STRATEGY BASED ON THERMOELECTRIC DECOUPLING CCHP AND INTEGRATED DEMAND RESPONSE COLLABORATIVE OPTIMIZATION

Liu Yan; Chen Guohua; Gu Xueping

doi:10.19912/j.0254-0096.tynxb.2023-0932

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (10) : 186-198. DOI: 10.19912/j.0254-0096.tynxb.2023-0932

DISTRIBUTION NETWORK RESILIENCE IMPROVEMENT STRATEGY BASED ON THERMOELECTRIC DECOUPLING CCHP AND INTEGRATED DEMAND RESPONSE COLLABORATIVE OPTIMIZATION

Liu Yan, Chen Guohua, Gu Xueping

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Abstract

For the post-disaster emergency recovery stage, this paper proposes a power grid resilience improvement strategy based on thermoelectric decoupling CCHP and integrated demand response collaborative optimization. This strategy takes into account resource utilization efficiency while improving resilience. By characterizing the response willingness curve of cold and hot users that takes into account uncertainty, the available temperature range is obtained, and based on this, a temperature deviation index is proposed to measure user comfort. Finally, a multi-objective optimization model is constructed with the goal of maximizing the value of electrical load recovery during power outage period and minimizing the temperature deviation of cold and hot loads. The ε constraint method is used to convert it into a single objective model for solution. The effectiveness of the strategy is verified through simulation of the IEEE-69 power system coupled with a 20 node natural gas network in Belgium.

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electric power distribution gird / uncertainty analysis / multi-objective optimization / resilience / thermoelectric decoupling / Integrated demand response（IDR）

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Liu Yan, Chen Guohua, Gu Xueping. DISTRIBUTION NETWORK RESILIENCE IMPROVEMENT STRATEGY BASED ON THERMOELECTRIC DECOUPLING CCHP AND INTEGRATED DEMAND RESPONSE COLLABORATIVE OPTIMIZATION[J]. Acta Energiae Solaris Sinica. 2024, 45(10): 186-198 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0932

References

[1] MA S S, CHEN B K, WANG Z Y.Resilience enhancement strategy for distribution systems under extreme weather events[J]. IEEE transactions on smart grid, 2018, 9(2): 1442-1451.
[2] 杨丽君, 高鹏, 王伟浩, 等. 考虑时间尺度的配电网故障恢复方法研究[J]. 太阳能学报, 2021, 42(1): 453-459.
YANG L J, GAO P, WANG W H, et al.Research on fault recovery method considering time scale for distribution network[J]. Acta energiae solaris sinica, 2021, 42(1): 453-459.
[3] 田晶京, 李安乐, 高锋阳, 等. 含光伏发电和时变负荷的主动配电网孤岛划分[J]. 太阳能学报, 2021, 42(9): 125-131.
TIAN J J, LI A L, GAO F Y, et al.Islanding division of active distribution network with photovoltaic generation and time-varying load[J]. Acta energiae solaris sinica, 2021, 42(9): 125-131.
[4] ZHU X, ZENG B, LI Y G, et al.Co-optimization of supply and demand resources for load restoration of distribution system under extreme weather[J]. IEEE access, 2021, 9: 122907-122923.
[5] 张冠宇, 付炜, 陈晨, 等. 面向电-气-热综合能源系统的恢复力研究现状与展望[J]. 智慧电力, 2023, 51(1): 69-77.
ZHANG G Y, FU W, CHEN C, et al.Status and prospects of resilience research for electric-gas-thermal integrated energy system[J]. Smart power, 2023, 51(1): 69-77.
[6] 韩高岩, 吕洪坤, 蔡洁聪, 等. 燃气冷热电三联供发展现状及前景展望[J]. 浙江电力, 2019, 38(1): 18-24.
HAN G Y, LYU H K, CAI J C, et al.Development status and prospect of CCHP of gas energy station[J]. Zhejiang electric power, 2019, 38(1): 18-24.
[7] ZOU B, WANG C, ZHOU Y, et al.Resilient co-expansion planning between gas and electric distribution networks against natural disasters[J]. IET generation, transmission & distribution, 2020, 14(17): 3561-3570.
[8] 陈玮, 丁筱, 施云辉, 等. 考虑双向耦合的电-气综合能源系统时序故障恢复方法[J]. 电力自动化设备, 2019, 39(8): 86-94.
CHEN W, DING X, SHI Y H, et al.Sequential fault restoration method for electricity-gas integrated energy system considering two-way coupling[J]. Electric power automation equipment, 2019, 39(8): 86-94.
[9] LIN Y L, CHEN B, WANG J H, et al.A combined repair crew dispatch problem for resilient electric and natural gas system considering reconfiguration and DG islanding[J]. IEEE transactions on power systems, 2019, 34(4): 2755-2767.
[10] 李雪, 孙霆锴, 侯恺, 等. 地震灾害下海岛综合能源系统韧性评估方法研究[J]. 中国电机工程学报, 2020, 40(17): 5476-5492.
LI X, SUN T K, HOU K, et al.Evaluating resilience of island integrated energy systems with earthquake[J]. Proceedings of the CSEE, 2020, 40(17): 5476-5492.
[11] CLEGG S, MANCARELLA P.Integrated electricity-heat-gas network modelling for the evaluation of system resilience to extreme weather[C]//2017 IEEE Manchester PowerTech. Manchester, UK, 2017: 1-6.
[12] 姜婷玉, 李亚平, 江叶峰, 等. 温控负荷提供电力系统辅助服务的关键技术综述[J]. 电力系统自动化, 2022, 46(11): 191-207.
JIANG T Y, LI Y P, JIANG Y F, et al.Review on key technologies for providing auxiliary services to power system by thermostatically controlled loads[J]. Automation of electric power systems, 2022, 46(11): 191-207.
[13] 卿玉良, 刘天琪, 刘绚, 等. 考虑多等级加固的气电联合配网系统韧性鲁棒提升策略研究[J]. 电网技术, 2022, 46(12): 4938-4946.
QING Y L, LIU T Q, LIU X, et al.Robust strategy of improving resilience of integrated gas-electricity distribution system considering multi-level reinforcement[J]. Power system technology, 2022, 46(12): 4938-4946.
[14] TAO R, ZHAO D M, XU C Y, et al.Resilience enhancement of integrated electricity-gas-heat urban energy system with data centres considering waste heat reuse[J]. IEEE transactions on smart grid, 2023, 14(1): 183-198.
[15] 曾博, 方伟, 徐豪, 等. 基于楼宇分布式能源提升配电网韧性的智能表计优化配置方法[J]. 电网技术, 2021, 45(1): 292-301.
ZENG B, FANG W, XU H, et al.Optimal allocation of smart energy meters for improving distribution network resilience based on distributed energy resources in buildings[J]. Power system technology, 2021, 45(1): 292-301.
[16] 林明明. 低温余热发电过程建模与先进控制策略研究[D]. 北京: 华北电力大学, 2016.
LIN M M.Research on modeling and advanced control strategy of low temperature waste heat power generation process[D]. Beijing: North China Electric Power University, 2016.
[17] 魏震波, 黄宇涵, 高红均, 等. 含电转气和热电解耦热电联产机组的区域能源互联网联合经济调度[J]. 电网技术, 2018, 42(11): 3512-3519.
WEI Z B, HUANG Y H, GAO H J, et al.Joint economic scheduling of power-to-gas and thermoelectric decoupling CHP in regional energy Internet[J]. Power system technology, 2018, 42(11): 3512-3519.
[18] 赵扉, 胡程平, 施云辉. 考虑温控负荷需求响应的电热联合系统多阶段鲁棒调度方法[J]. 电力需求侧管理, 2022, 24(5): 15-21.
ZHAO F, HU C P, SHI Y H.Multi-stage robust dispatch of integrated electric and heating system considering demand response of thermostatically controlled load[J]. Power demand side management, 2022, 24(5): 15-21.
[19] 张慧颖. 智能化低频低压减载模型及其敏感性分析研究[D]. 天津: 天津大学, 2014.
ZHANG H Y.Intelligent low-frequency and low-voltage load shedding model and its sensitivity analysis[D]. Tianjin: Tianjin University, 2014.
[20] 吴界辰, 艾欣, 胡俊杰. 需求侧资源灵活性刻画及其在日前优化调度中的应用[J]. 电工技术学报, 2020, 35(9): 1973-1984.
WU J C, AI X, HU J J.Methods for characterizing flexibilities from demand-side resources and their applications in the day-ahead optimal scheduling[J]. Transactions of China Electrotechnical Society, 2020, 35(9): 1973-1984.
[21] 宋恒森. 三循环风冷冰箱优化设计及其特性试验与分析[D]. 南京: 东南大学, 2020.
SONG H S.Optimal design and characteristic test and analysis of three-cycle air-cooled refrigerator[D]. Nanjing: Southeast University, 2020.
[22] 艾欣, 周树鹏, 赵阅群. 基于场景分析的含可中断负荷的优化调度模型研究[J]. 中国电机工程学报, 2014, 34(增刊1): 25-31.
AI X, ZHOU S P, ZHAO Y Q.Research on optimal dispatch model considering interruptible loads based on scenario analysis[J]. Proceedings of the CSEE, 2014, 34(S1): 25-31.
[23] LI Z Z, LI Z K.Linear programming-based scenario reduction using transportation distance[J]. Computers & chemical engineering, 2016, 88: 50-58.
[24] 贺培春. 基于舒适度的室内空气调节系统研究[D]. 重庆: 重庆大学, 2010.
HE P C.Research on Indoor Air Conditioning System Based on Comfort[D]. Chongqing: Chongqing University, 2010.
[25] 董京营, 周博, 刘晋源, 等. 考虑用户舒适度的虚拟电厂热电联合调度模型[J]. 电力建设, 2019, 40(1): 19-26.
DONG J Y, ZHOU B, LIU J Y, et al.Heat and power scheduling of a virtual power plant considering comfort level of customers[J]. Electric power construction, 2019, 40(1): 19-26.
[26] 牛文娟. 计及不确定性的需求响应机理模型及应用研究[D]. 南京: 东南大学, 2015.
NIU W J.Research on demand response mechanism model considering uncertainty and its application[D]. Nanjing: Southeast University, 2015.
[27] 孙毅, 张辰, 李泽坤, 等. 计及多区域用户差异化PMV的柔性负荷多功率级调控策略[J]. 中国电机工程学报, 2021, 41(22): 7574-7585.
SUN Y, ZHANG C, LI Z K, et al.Flexible load multi-power level control strategy taking into account the differentiated PMV of multi-region users[J]. Proceedings of the CSEE, 2021, 41(22): 7574-7585.
[28] 徐青山, 刘梦佳, 戴蔚莺, 等. 计及用户响应不确定性的可中断负荷储蓄机制[J]. 电工技术学报, 2019, 34(15): 3198-3208.
XU Q S, LIU M J, DAI W Y, et al.Interruptible load based on deposit mechanism considering uncertainty of customer behavior[J]. Transactions of China Electrotechnical Society, 2019, 34(15): 3198-3208.
[29] 王守相, 黄仁山, 潘志新, 等. 极端冰雪天气下配电网弹性恢复力指标的构建及评估方法[J]. 高电压技术, 2020, 46(1): 123-132.
WANG S X, HUANG R S, PAN Z X, et al.Construction and evaluation of resilience restoration capability indices for distribution network under extreme ice and snow weather[J]. High voltage engineering, 2020, 46(1): 123-132.
[30] 勇蔚柯, 李扬, 曹阳. 基于需求响应的配电网韧性提升技术研究[J]. 电力需求侧管理, 2022, 24(2): 20-26.
YONG W K, LI Y, CAO Y.Research on improvement technology of distribution network resilience based on demand response[J]. Power demand side management, 2022, 24(2): 20-26.
[31] 卫志农, 张思德, 孙国强, 等. 基于碳交易机制的电-气互联综合能源系统低碳经济运行[J]. 电力系统自动化, 2016, 40(15): 9-16.
WEI Z N, ZHANG S D, SUN G Q, et al.Carbon trading based low-carbon economic operation for integrated electricity and natural gas energy system[J]. Automation of electric power systems, 2016, 40(15): 9-16.
[32] 施云辉. 考虑可再生能源不确定性的电力系统多阶段鲁棒调度方法[D]. 杭州: 浙江大学, 2021.
SHI Y H.Multi-stage robust scheduling method of power system considering uncertainty of renewable energy[D]. Hangzhou: Zhejiang University, 2021.