|
|
|
| An Accommodation Strategy for Renewable Energy in Distribution Network Considering Coordinated Dispatching of Multi-Flexible Resources |
| Jiang Yunpeng1, Ren Zhouyang1, Li Qiuyan2, Guo Yong2, Xu Yan3 |
1. State Key Laboratory of Power Transactionsmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing 400044 China;
2. State Grid Henan Economic Research Institute Zhengzhou 450052 China;
3. School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore |
|
|
|
|
Abstract Aiming at the challenges brought by flexible regulation resource scarcity and efficient accommodation with high penetration renewable energy integration under ‘double carbon goal’, an accommodation strategy for renewable energy in distribution network considering coordinated dispatching of multi-flexible resources is proposed. The method is established to depict the flexible interaction between multi-flexible resources. Considering both renewable energy accommodation and operating costs of distribution network. The accommodation optimization model for renewable energy is established considering coordinated dispatching of multi-flexible resources. In order to obtain the feasible region of non-dominant solutions of the accommodation optimization model, a multi-objective optimization solution method is established based on bi-layer embedded structure, and the composite linearization strategy is proposed to recast the complex multi-objective, non-linear and non-convex accommodation optimization model to a multi-objective mixed integer linear optimization model so that the accommodation optimization model can be efficiently solved. Finally, the effectiveness and applicability of the proposed accommodation strategy are verified by IEEE 33 bus system and a practical 110 kV distribution network in China.
|
|
Received: 15 September 2021
|
|
|
|
|
|
[1] 习近平.继往开来,开启全球应对气候变化新征程[EB/OL].人民网,[2020-12-14].http://env.people.com.cn/n1/2020/1214/c1010-31965084.html.
[2] 央视网. 习近平主持召开中央财经委员会第九次会议强调推动平台经济规范健康持续发展把碳达峰碳中和纳入生态文明建设整体布局[EB/OL].[2021-03-15].https://news.cctv.com/2021/03/15/ARTIFUhtqyI0GxogiEDWyY28210315.shtml.
[3] 新华社.中华人民共和国国民经济和社会发展第十四个五年规划和2035年远景目标纲要[EB/OL]. [2021-03-13].http://www.gov.cn/xinwen/2021-03/13/content_5592681.htm.
[4] Cruz M R M, Fitiwi D Z, Santos S F, et al. Multi-flexibility option integration to cope with large-scale integration of renewables[J]. IEEE Transactions on Sustainable Energy, 2020, 11(1): 48-60.
[5] 王雪纯, 陈红坤, 陈磊. 提升区域综合能源系统运行灵活性的多主体互动决策模型[J]. 电工技术学报, 2021, 36(11): 2207-2219.
Wang Xuechun, Chen Hongkun, Chen Lei.Multi-player interactive decision-making model for operational flexibility improvement of regional integrated energy system[J]. Transactions of China Electrotechnical Society, 2021, 36(11): 2207-2219.
[6] 孙惠, 翟海保, 吴鑫. 源网荷储多元协调控制系统的研究及应用[J]. 电工技术学报, 2021, 36(15): 3264-3271.
Sun Hui, Zhai Haibao, Wu Xin.Research and application of multi-energy coordinated control of generation, network, load and storage[J]. Transactions of China Electrotechnical Society, 2021, 36(15): 3264-3271.
[7] 国家发展改革委, 国家能源局. 国家发展改革委国家能源局关于推进电力源网荷储一体化和多能互补发展的指导意见(发改能源规[2021]280号) [EB/OL]. [2021-02-25]. http://www.gov.cn/zhengce/zhengceku/2021-03/06/content_5590895.htm.
[8] 徐浩, 李华强. 火电机组灵活性改造规划及运行综合随机优化模型[J]. 电网技术, 2020, 44(12): 4626-4638.
Xu Hao, Li Huaqiang.Planning and operation stochastic optimization model of power systems considering the flexibility reformation[J]. Power System Technology, 2020, 44(12): 4626-4638.
[9] 孙辉, 刘鑫, 贲驰, 等. 含风储一体化电站的电力系统多目标风险调度模型[J]. 电力系统自动化, 2018, 42(5): 94-101.
Sun Hui, Liu Xin, Ben Chi, et al.Multi-objective risk scheduling model of power system containing power station with integrated wind power and energy storage[J]. Automation of Electric Power Systems, 2018, 42(5): 94-101.
[10] 李则衡, 陈磊, 路晓敏, 等. 基于系统灵活性的可再生能源接纳评估[J]. 电网技术, 2017, 41(7): 2187-2194.
Li Zeheng, Chen Lei, Lu Xiaomin, et al.Assessment of renewable energy accommodation based on system flexibility analysis[J]. Power System Technology, 2017, 41(7): 2187-2194.
[11] 周任军, 石亮缘, 汤吉鸿, 等. 多功率曲线协整度约束下的源-荷-储优化协整模型[J]. 中国电机工程学报, 2019, 39(12): 3454-3465.
Zhou Renjun, Shi Liangyuan, Tang Jihong, et al.Source-load-storage optimization cointegration model under multi-power curve cointegration degree constraints[J]. Proceedings of the CSEE, 2019, 39(12): 3454-3465.
[12] 徐箭, 胡佳, 廖思阳, 等. 考虑网络动态特性与综合需求响应的综合能源系统协同优化[J]. 电力系统自动化, 2021, 706(12): 40-48.
Xu Jian, Hu Jia, Liao Siyang, et al.Coordinated optimization of integrated energy system considering dynamic characteristics of network and integrated demand response[J]. Automation of Electric Power Systems, 2021, 706(12): 40-48.
[13] Mahmud N, Zahedi A.Review of control strategies for voltage regulation of the smart distribution network with high penetration of renewable distributed generation[J]. Renewable and Sustainable Energy Reviews, 2016, 64: 582-595.
[14] Verma A, Krishan R, Mishra S.A novel PV inverter control for maximization of wind power penetration[J]. IEEE Transactions on Industry Applications, 2018, 54(6): 6364-6373.
[15] Nguyen Q, Padullaparti H V, Lao K, et al.Exact optimal power dispatch in unbalanced distribution systems with high PV penetration[J]. IEEE Transactions on Power Systems, 2019, 34(1): 718-728.
[16] 龚思宇, 魏炜, 徐元孚, 等. 面向分布式电源最大消纳的配电网重构[J]. 电力系统及其自动化学报, 2017, 29(3): 7-11, 41.
Gong Siyu, Wei Wei, Xu Yuanfu, et al.Reconfiguration of distribution network for the maximum consumption of distributed generations[J]. Proceedings of the CSU-EPSA, 2017, 29(3): 7-11, 41.
[17] 刘路宁, 彭春华, 温泽之, 等. 基于配电网动态重构的分布式光伏消纳策略[J]. 电力自动化设备, 2019, 39(12): 56-62.
Liu Luning, Peng Chunhua, Wen Zezhi, et al.Distributed photovoltaic consumption strategy based on dynamic reconfiguration of distribution network[J]. Electric Power Automation Equipment, 2019, 39(12): 56-62.
[18] Lei Shunbo, Hou Yunhe, Qiu Feng, et al.Identification of critical switches for integrating renewable distributed generation by dynamic network reconfiguration[J]. IEEE Transactions on Sustainable Energy, 2018, 9(1): 420-432.
[19] Wang Chong, Lei Shunbo, Ju Ping, et al.MDP-based distribution network reconfiguration with renewable distributed generation: approximate dynamic programming approach[J]. IEEE Transactions on Smart Grid, 2020, 11(4): 3620-3631.
[20] Capitanescu F, Bilibin I, Romero E R.A comprehensive centralized approach for voltage constraints management in active distribution grid[J]. IEEE Transactions on Power Systems, 2014, 29(2): 933-942.
[21] Capitanescu F, Bilibin I.A tractable two-step MILP-QCP approach to on-line thermal constraint management in large radial active distribution systems[J]. Electric Power Systems Research, 2016, 140: 580-587.
[22] 沙熠, 邱晓燕, 宁雪姣, 等. 协调储能与柔性负荷的主动配电网多目标优化调度[J]. 电网技术, 2016, 40(5): 1394-1399.
Sha Yi, Qiu Xiaoyan, Ning Xuejiao, et al.Multi-objective optimization of active distribution network by coordinating energy storage system and flexible load[J]. Power System Technology, 2016, 40(5): 1394-1399.
[23] 黄伟, 熊伟鹏, 华亮亮, 等. 基于动态调度优先级的主动配电网多目标优化调度[J]. 电工技术学报, 2018, 33(15): 3486-3498.
Huang Wei, Xiong Weipeng, Hua Liangliang, et al.Multi-objective optimization dispatch of active distribution network based on dynamic schedule priority[J]. Transactions of China Electrotechnical Society, 2018, 33(15): 3486-3498.
[24] 郑能, 丁晓群, 郑程拓, 等. 含高比例光伏的配电网有功——无功功率多目标协调优化[J]. 电力系统自动化, 2018, 42(6): 33-39, 91.
Zheng Neng, Ding Xiaoqun, Zheng Chengtuo, et al.Multi-objective coordinated optimization of active and reactive power for distribution network integrated with high proportion of photovoltaic generation[J]. Automation of Electric Power Systems, 2018, 42(6): 33-39, 91.
[25] Zhu Xiaonan, Wang Hongliang, Zhang Wenyuan, et al.A novel single-phase five-level Transactionsformer-less photovoltaic (PV) inverter[J]. CES Transactions on Electrical Machines and Systems, 2020, 4(4): 329-338.
[26] 徐成司, 董树锋, 朱嘉麒, 等. 基于供电环路非连通条件的配电网辐射状约束描述方法[J]. 电力系统自动化, 2019, 43(20): 82-94.
Xu Chengsi, Dong Shufeng, Zhu Jiaqi, et al.Description method of radial constraints for distribution network based on disconnection condition of power supply loop[J]. Automation of Electric Power Systems, 2019, 43(20): 82-94.
[27] 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 Jiechen, Ai Xin, Hu Junjie.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.
[28] 白桦, 王正用, 李晨, 等. 面向电网侧、新能源侧及用户侧的储能容量配置方法研究[J]. 电气技术, 2021, 22(1): 8-13.
Bai Hua, Wang Zhengyong, Li Chen, et al.Research on capacity allocation method of energy storage for grid side, new energy side and user side[J]. Electrical Engineering, 2021, 22(1): 8-13.
[29] Yang Zhifang, Bose A, Zhong Haiwang, et al. Optimal reactive power dispatch with accurately modeled discrete control devices: a successive linear approximation approach[J]. IEEE Transactions on Power Systems, 2017, 32, (3): 2435-2444.
[30] Sardou I G, Khodayar M E, Ameli M T.Coordinated operation of natural gas and electricity networks with microgrid aggregators[J]. IEEE Transactions on Smart Grid, 2018, 9(1): 199-210.
[31] Yuan Haoyu, Li Fangxing, Wei Yanli, et al.Novel linearized power flow and linearized OPF models for active distribution networks with application in distribution LMP[J]. IEEE Transactions on Smart Grid, 2017, 9(1): 438-448.
[32] Wang Shouxiang, Chen Sijia, Ge Leijiao, et al.Distributed generation hosting capacity evaluation for distribution systems considering the robust optimal operation of OLTC and SVC[J]. IEEE Transactions on Sustainable Energy, 2016, 7(3): 1111-1123.
[33] Stelt S V D, AlSkaif T, Sark W V. Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances[J]. Applied Energy, 2018(209): 266-276.
[34] Soroudi A, Rabiee A, Keane A.Distribution networks' energy losses versus hosting capacity of wind power in the presence of demand flexibility[J]. Renewable Energy, 2017(102): 316-325.
[35] Cerbantes M C, Fernández-Blanco R, Ortega-Vazquez M A, et al. Incorporating a nodal reactive power pricing scheme into the DisCo’s short-term operation[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 3720-3731.
[36] 赵冬梅, 陶然, 马泰屹, 等. 基于多智能体深度确定策略梯度算法的有功-无功协调调度模型[J]. 电工技术学报, 2021, 36(9):1914-1925.
Zhao Dongmei, Tao Ran, Ma Taiyi, et al.Active and reactive power coordinated dispatching based on multi-agent deep deterministic policy gradient algorithm[J]. Transactions of China Electrotechnical Society, 2021, 36(9):1914-1925.
[37] Lazzeroni P, Repetto M.Optimal planning of battery systems for power losses reduction in distribution grids[J]. Electric Power Systems Research, 2019, 167: 94-112.
[38] 翟世涛, 刘泽槐, 杨家豪, 等. 考虑多时段并网点电压控制的光储容量匹配及优化运行[J]. 电网技术, 2017, 41(6): 1855-1865.
Zhai Shitao, Liu Zehuai, Yang Jiahao, et al.Capacity matching and optimal operation of photovoltaic-storage systems based on multi-period PCC voltage control[J]. Power System Technology, 2017, 41(6): 1855-1865.
[39] 谢琳宇, 唐忠, 黄星宇, 等. 考虑分布式电源和电动汽车不确定性的双层动态配网重构[J]. 电力系统保护与控制, 2020, 48(10): 1-11.
Xie Linyu, Tang Zhong, Huang Xingyu, et al.Bi-layer dynamic reconfiguration of a distribution network considering the uncertainty of distributed generation and electric vehicles[J]. Power System Protection and Control, 2020, 48(10): 1-11.
[40] 杨楠, 董邦天, 黄禹, 等. 考虑不确定性和多主体博弈的增量配电网源网荷协同规划方法[J]. 中国电机工程学报, 2019, 39(9): 2689-2702.
Yang Nan, Dong Bangtian, Huang Yu, et al.Incremental distribution network source-load collaborative planning method considering uncertainty and multi-agent game[J]. Proceedings of the CSEE, 2019, 39(9): 2689-2702.
[41] 麻秀范, 陈静, 余思雨, 等. 计及容量市场的用户侧储能优化配置研究[J]. 电工技术学报, 2020, 35(19): 4028-4037.
Ma Xiufan, Chen Jing, Yu Siyu, et al.Research on user side energy storage optimization configuration considering capacity market[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4028-4037.
[42] 张博, 唐巍, 蔡永翔, 等. 基于一致性算法的户用光伏逆变器和储能分布式控制策略[J]. 电力系统自动化, 2020, 44(2):86-96.
Zhang Bo, Tang Wei, Cai Yongxiang, et al.Distributed control strategy of residential photovoltaic inverter and energy storage based on consensus algorithm[J]. Automation of Electric Power Systems, 2020, 44(2): 86-96.
[43] 周丹, 孙可, 张全明, 等. 含多个综合能源联供型微网的配电网日前鲁棒优化调度[J]. 中国电机工程学报, 2020, 40(14): 4473-4485, 4727.
Zhou Dan, Sun Ke, Zhang Quanming, et al.Day-ahead robust dispatch of distribution network with multiple integrated energy system-based micro-grids[J]. Proceedings of the CSEE, 2020, 40(14): 4473-4485, 4727.
[44] 杨明, 程凤璐, 韩学山. 电力系统实时调度的有效静态安全域法[J]. 中国电机工程学报, 2015, 35(6): 1353-1362.
Yang Ming, Cheng Fenglu, Han Xueshan.Real-time dispatch based on effective steady-state security regions of power system[J]. Proceedings of the CSEE, 2015, 35(6): 1353-1362.
[45] 林凯骏, 吴俊勇, 郝亮亮, 等. 基于非合作博弈的冷热电联供微能源网运行策略优化[J]. 电力系统自动化, 2018, 42(6): 25-32.
Lin Kaijun, Wu Junyong, Hao liangliang, et al. Optimization of operation strategy for micro-energy grid with CCHE systems based on non-cooperative game[J]. Automation of Electric Power Systems, 2018, 42(6): 25-32.
[46] 孙建军, 张世泽, 曾梦迪, 等. 考虑分时电价的主动配电网柔性负荷多目标优化控制[J]. 电工技术学报, 2018, 33(2): 401-412.
Sun Jianjun, Zhang Shize, Zeng Mengdi, et al.Multi-objective optimal control for flexible load in active distribution network considering time-of-use tariff[J]. Transactions of China Electrotechnical Society, 2018, 33(2): 401-412.
[47] 王侨侨, 曾君, 刘俊峰, 等. 面向微电网源-储-荷互动的分布式多目标优化算法研究[J]. 中国电机工程学报, 2020, 40(5): 1421-1432.
Wang Qiaoqiao, Zeng Jun, Liu Junfeng, et al.A distributed multi-objective optimization algorithm for resource-storage-load interaction of microgrid[J]. Proceedings of the CSEE, 2020, 40(5): 1421-1432.
[48] Li Qifeng, Ayyanar R, Vittal V.Convex optimization for DES planning and operation in radial distribution systems with high penetration of photovoltaic resources[J]. IEEE Transactions on Sustainable Energy, 2016, 7(3): 985-995. |
|
|
|
2022, Vol. 37 
