高比例可再生能源接入背景下电网承载能力鲁棒提升策略

doi:10.11930/j.issn.1004-9649.202305103

中国电力 ›› 2023, Vol. 56 ›› Issue (9): 104-111.DOI: 10.11930/j.issn.1004-9649.202305103

• 配电网规划与优化运行 • 上一篇下一篇

高比例可再生能源接入背景下电网承载能力鲁棒提升策略

但扬清¹, 王蕾¹, 郑伟民¹, 武佳卉¹, 王晨轩¹, 余高旺²

1. 国网浙江省电力有限公司经济技术研究院，浙江杭州 310008;
2. 许继电气股份有限公司，河南许昌 461000

收稿日期:2023-05-23 修回日期:2023-08-14 发布日期:2023-09-20
作者简介:但扬清(1983-),男,博士,高级工程师,从事新能源并网控制研究,E-mail:danyangqing@aliyun.com;王蕾(1982-),女,硕士,高级工程师(教授级),从事主动配电网多阶段规划研究,E-mail:wang_lei1@zj.sgcc.com.cn;郑伟民(1971-),男,硕士,高级工程师,从事电网规划与设计研究,E-mail:zheng_weimin@zj.sgcc.com.cn
基金资助:
国网浙江省电力有限公司科技项目（5211JY21N001）。

Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy

DAN Yangqing¹, WANG Lei¹, ZHENG Weimin¹, WU Jiahui¹, WANG Chenxuan¹, YU Gaowang²

1. Economic Research Institute of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 310008, China;
2. XJ Electric Co., Ltd., Xuchang 461000, China

Received:2023-05-23 Revised:2023-08-14 Published:2023-09-20
Supported by:
This work is supported by Science and Technology Project of State Grid Zhejiang Electric Power Co., Ltd. (No.5211JY21N001).

摘要/Abstract

摘要： 高比例可再生能源并网为电网承载能力带来了挑战，提出一种高比例可再生能源接入背景下电网承载能力鲁棒提升策略。首先，考虑线路扩容成本、储能装置成本以及负荷需求响应容量成本，构建可再生能源出力和负荷给定场景下的确定性提升策略模型；其次，基于改进k-means聚类算法得到多个计及风-光-负荷相关性的典型场景，并以典型场景为区间中心的不确定区间描述负荷的不确定性；然后，基于两阶段鲁棒优化理论构建电网承载能力提升策略模型，并采用列和约束生成（column and constraint generation，C&CG）算法对模型进行求解；最后，算例结果验证了所提模型和求解方法的有效性。

关键词: 可再生能源, 电网承载能力, 改进k-means聚类算法, 鲁棒提升策略

Abstract: The high proportion of renewable energy integration into the grid poses challenges to the hosting capacity of the power grid. This paper proposes a robust improvement strategy for the hosting capacity of the power grid with integration of high proportion of renewable energy. Firstly, considering the line expansion cost, energy storage device cost, and demand response capacity cost required for load, a deterministic improvement strategy model is constructed for renewable energy output and load under given scenarios. Secondly, based on the improved k-means clustering algorithm, multiple typical scenarios considering the wind-PV-load correlation are obtained, and the uncertainty of the load is described using the uncertainty interval centered with the typical scenarios. And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. Finally, the effectiveness of the proposed model and solution method is verified by the case study.

Key words: renewable energy, power grid hosting capacity, improved k-means clustering algorithm, robust improvement strategy

但扬清, 王蕾, 郑伟民, 武佳卉, 王晨轩, 余高旺. 高比例可再生能源接入背景下电网承载能力鲁棒提升策略[J]. 中国电力, 2023, 56(9): 104-111.

DAN Yangqing, WANG Lei, ZHENG Weimin, WU Jiahui, WANG Chenxuan, YU Gaowang. Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy[J]. Electric Power, 2023, 56(9): 104-111.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305103

https://www.electricpower.com.cn/CN/Y2023/V56/I9/104

参考文献

[1] 国家电网公司发布“碳达峰、碳中和”行动方案[N]. 国家电网报, 2021-03-02(001).
[2] HASHEMI S, OSTERGAARD J, DEGNER T, et al. Efficient control of active transformers for increasing the PV hosting capacity of LV grids[J]. IEEE Transactions on Industrial Informatics, 2016, 13(1): 270–277.
[3] CHEN L J, DENG Z L, XU X H. Two-stage dynamic reactive power dispatch strategy in distribution network considering the reactive power regulation of distributed generations[J]. IEEE Transactions on Power Systems, 2019, 34(2): 1021–1032.
[4] ZIEGLER M S, MUELLER J M, PEREIRA G D, et al. Storage requirements and costs of shaping renewable energy toward grid decarbonization[J]. Joule, 2019, 3(9): 2134–2153.
[5] WONG P K C, KALAM A, BARR R. Modelling and analysis of practical options to improve the hosting capacity of low voltage networks for embedded photo-voltaic generation[J]. IET Renewable Power Generation, 2017, 11(5): 625–632.
[6] 徐帆, 丁恰, 韩红卫, 等. 促进跨区新能源消纳的直流联络线功率优化模型及分析[J]. 电力系统自动化, 2017, 41(18): 152–159
XU Fan, DING Qia, HAN Hongwei, et al. Power optimization model and analysis of HVDC tie-line for promoting integration of inter-regional renewable energy accommodation[J]. Automation of Electric Power Systems, 2017, 41(18): 152–159
[7] 王秀丽, 李骏, 黄镔, 等. 促进风电消纳的区省两级电力系统调度模型[J]. 电网技术, 2015, 39(7): 1833–1838
WANG Xiuli, LI Jun, HUANG Bin, et al. A two-stage optimal dispatching model for provincial and regional power grids connected with wind farms to promote accommodation of wind power[J]. Power System Technology, 2015, 39(7): 1833–1838
[8] 方一晨, 张沈习, 程浩忠, 等. 含智能软开关的主动配电网分布式光伏准入容量鲁棒优化[J]. 电力系统自动化, 2021, 45(7): 8–17
FANG Yichen, ZHANG Shenxi, CHENG Haozhong, et al. Robust optimization of distributed photovoltaic hosting capacity of active distribution network with soft open point[J]. Automation of Electric Power Systems, 2021, 45(7): 8–17
[9] 吕凯, 唐昊, 王珂, 等. 计及源荷双侧不确定性的跨区互联电网源网荷协同调度[J]. 电力系统自动化, 2019, 43(22): 38–45
LYU Kai, TANG Hao, WANG Ke, et al. Coordinated dispatching of source-grid-load for inter-regional power grid considering uncertainties of both source and load sides[J]. Automation of Electric Power Systems, 2019, 43(22): 38–45
[10] 张逸康, 赵晋泉, 刘子文, 等. 大电网调度自动巡航中经济运行域的构建方法[J]. 电力系统自动化, 2020, 44(12): 64–73
ZHANG Yikang, ZHAO Jinquan, LIU Ziwen, et al. Construction method of economic operation region in automatic cruise for bulk power grid dispatching[J]. Automation of Electric Power Systems, 2020, 44(12): 64–73
[11] WAN C, LIN J, GUO W F, et al. Maximum uncertainty boundary of volatile distributed generation in active distribution network[J]. IEEE Transactions on Smart Grid, 2018, 9(4): 2930–2942.
[12] WAN C, ZHAO J, SONG Y H, et al. Photovoltaic and solar power forecasting for smart grid energy management[J]. CSEE Journal of Power and Energy Systems, 2015, 1(4): 38–46.
[13] ZEPTER J M, WEIBEZAHN J. Unit commitment under imperfect foresight-the impact of stochastic photovoltaic generation[J]. Applied Energy, 2019, 243: 336–349.
[14] WANG S X, CHEN S J, GE L J, 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.
[15] SOROUDI A, CAIRE R, HADJSAID N, et al. Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning[J]. IET Generation, Transmission & Distribution, 2011, 5(11): 1173–1182.
[16] NAVARRO-ESPINOSA A, OCHOA L F. Probabilistic impact assessment of low carbon technologies in LV distribution systems[J]. IEEE Transactions on Power Systems, 2016, 31(3): 2192–2203.
[17] 万灿, 崔文康, 宋永华. 新能源电力系统概率预测: 基本概念与数学原理[J]. 中国电机工程学报, 2021, 41(19): 6493–6508
WAN Can, CUI Wenkang, SONG Yonghua. Probabilistic forecasting for power systems with renewable energy sources: basic concepts and mathematical principles[J]. Proceedings of the CSEE, 2021, 41(19): 6493–6508
[18] 万灿, 宋永华. 新能源电力系统概率预测理论与方法及其应用[J]. 电力系统自动化, 2021, 45(1): 2–16
WAN Can, SONG Yonghua. Theories, methodologies and applications of probabilistic forecasting for power systems with renewable energy sources[J]. Automation of Electric Power Systems, 2021, 45(1): 2–16
[19] VAN DER MEER D W, MUNKHAMMAR J, WIDÉN J. Probabilistic forecasting of solar power, electricity consumption and net load: investigating the effect of seasons, aggregation and penetration on prediction intervals[J]. Solar Energy, 2018, 171(3): 397–413.
[20] HAN X N, CHEN X Y, MCELROY M B, et al. Modeling formulation and validation for accelerated simulation and flexibility assessment on large scale power systems under higher renewable penetrations[J]. Applied Energy, 2019, 237(5): 145–154.
[21] RABIEE A, MOHSENI-BONAB S M. Maximizing hosting capacity of renewable energy sources in distribution networks: a multi-objective and scenario-based approach[J]. Energy, 2017, 120(2): 417–430.
[22] KIM M, RAMAKRISHNA R S. New indices for cluster validity assessment[J]. Pattern Recognition Letters, 2005, 26(15): 2353–2363.
[23] RUIZ C, CONEJO A J. Robust transmission expansion planning[J]. European Journal of Operational Research, 2015, 242(2): 390–401.
[24] ZENG B, ZHAO L. Solving two stage robust optimization problems using a column-and-constraint generation method[J]. Operations Research Letters, 2013, 41(5): 457–461.
[25] 姜涛, 谭洪强, 李雪, 等. 电力系统热稳定安全域边界快速搜索的优化模型[J]. 中国电机工程学报, 2019, 39(22): 6533–6546
JIANG Tao, TAN Hongqiang, LI Xue, et al. A general optimization model for exploring static thermal security region boundary in bulk power systems[J]. Proceedings of the CSEE, 2019, 39(22): 6533–6546

高比例可再生能源接入背景下电网承载能力鲁棒提升策略

Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	姜通海, 王峰, 刘子琪, 单帅杰. 基于改进生成对抗网络的风光气象资源联合场景生成方法[J]. 中国电力, 2025, 58(3): 183-192.
[2]	汤明润, 李若旸, 刘慕然, 程晓钰, 刘铫, 杨淑霞. 电力系统稳态下可再生能源大规模接入量预测[J]. 中国电力, 2025, 58(2): 126-132.
[3]	黄堃, 付明, 翟家祥, 华昊辰. 基于改进线性化ADMM的多微网经济运行分布式协调优化[J]. 中国电力, 2025, 58(2): 193-202.
[4]	鲁玲, 苑涛, 杨波, 李欣, 鲁洋, 蒲秋平, 张鑫. 计及㶲效率和多重不确定性的区域综合能源系统双层优化[J]. 中国电力, 2025, 58(1): 128-140.
[5]	邹小燕, 张瑞宏. 考虑政府干预的可再生能源与储能企业合作模式演化博弈研究[J]. 中国电力, 2025, 58(1): 153-163.
[6]	邵冲, 胡荣义, 余姣, 王明典. 考虑荷电与储氢状态的风光氢储系统动态控制仿真模型[J]. 中国电力, 2024, 57(7): 109-124.
[7]	胡旭, 安锐坚, 杜宇晨, 施啸寒, 王越. 欧洲—北非氢能协同发展研究[J]. 中国电力, 2024, 57(7): 151-162.
[8]	武群丽, 朱新宇. 可再生能源配额制下风光储联合参与现货市场的交易决策[J]. 中国电力, 2024, 57(4): 77-88.
[9]	王麒翔, 韩震焘, 梁毅. 基于博弈论均衡的风险防控经济调度分析[J]. 中国电力, 2024, 57(10): 69-77.
[10]	武震, 霍彦达, 张翼, 黄巨龙, 戴剑锋. 考虑新能源发电量季节性分布的省区级季节性储能需求测算方法[J]. 中国电力, 2023, 56(8): 40-47.
[11]	汤芳, 代红才, 张宁, 吴越, 薛美美, 陈睿. 能耗双控向碳排放双控转变影响分析及推进路径设计[J]. 中国电力, 2023, 56(12): 255-261.
[12]	刘之琳, 许传龙, 郑海峰, 李江涛, 姚力, 刘青, 杜翼. 德国关停核电前后保供应促消纳经验分析[J]. 中国电力, 2023, 56(10): 145-152.
[13]	李民, 刘钦浩, 赵冠, 周步祥, 夏海东, 臧天磊. 考虑多元产业协同的乡村综合能源系统规划[J]. 中国电力, 2022, 55(8): 14-22.
[14]	窦东, 王雁宇, 李欣, 杨文生, 周文奇, 李海清, 张士营. 蒙西地区储能技术经济性优化配置研究[J]. 中国电力, 2022, 55(8): 52-63.
[15]	武群丽, 席曼. 基于电力供应链博弈的可再生能源政策效应研究[J]. 中国电力, 2022, 55(5): 12-20,38.

模态框（Modal）标题

高比例可再生能源接入背景下电网承载能力鲁棒提升策略

Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics