基于分布式光伏集群控制的主动配电网电压优化策略
作者:
中图分类号:

TM73

基金项目:

江苏省自然科学基金资助项目(BK20210932)


Voltage optimization strategy for active distribution network based on distributed photovoltaic cluster control
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [49]
  • |
  • 相似文献
  • | | |
  • 文章评论
    摘要:

    对于因高比例分布式光伏接入主动配电网引发的电压越限问题,文中提出一种基于分布式光伏集群控制的主动配电网电压优化策略。首先,在日前阶段以经济性为目标,确定日内阶段的可平移负荷量、有载调压变压器挡位以及离散无功补偿设备出力。然后,基于日前阶段调控结果计算近似电压灵敏度,并采用K-means算法,依据集群综合指标划分集群。最后,日内阶段按照集群调节特性,以集群内部网损最小或节点电压偏差最小为目标进行滚动集群自律优化,基于交替方向乘子法进行集群间协同优化。在IEEE 33节点系统上实施该策略,考虑多种天气及不同调控策略进行电压调控效果对比,结果表明:日前集中优化后节点电压处在限值范围内且不越限,日内集群滚动优化后电压偏移量进一步降低,晴天情况下电压偏移量不超过3%。算例结果验证了所提优化策略可以有效保证电压质量,并提高配电网运行经济性。

    Abstract:

    High penetration of distributed photovoltaic causes voltage violation problem in active distribution network. In order to solve this problem, a voltage optimization strategy based on distributed photovoltaic cluster control is proposed for the active distribution network. Firstly, with economic operation as the objective,shiftable load dispatch, the tap positions of on-load tap-changing transformers, and the output of capacitor banks are determined in the day-ahead stage. Subsequently, the approximate voltage sensitivity is calculated based on the day-ahead scheduling results, and clusters are partitioned using the K-means algorithm according to a comprehensive clustering index. Finally, in the intra-day stage, the cluster self-regulation is carried out based on the cluster adjustment characteristics, aiming at minimizing the internal network losses or the node voltage deviations. The inter-cluster coordination optimization is then performed based on the alternating direction multiplier method. Deploy this strategy on the IEEE 33-node system, and conduct a comparative analysis of voltage regulation effectiveness under various weather conditions and different scheduling strategies. The results show that after the day-ahead centralized optimization, the node voltages are within the limit range. After the intra-day rolling optimization, the voltage deviation is further reduced, and the deviation does not exceed 3% on sunny days. The case study results verify that the proposed optimization strategy guarantees voltage quality and meanwhile improves operational efficiency of distribution network.

    参考文献
    [1] 李晓萍,袁至,王维庆,等. 考虑可再生能源接入的多端MMC交直流混合系统协调控制[J]. 可再生能源,2024,42(5):675-684.
    LI Xiaoping, YUAN Zhi, WANG Weiqing, et al. Coordinated control of multi-terminal MMC AC/DC hybrid system considering renewable energy access[J]. Renewable Energy Resources, 2024, 42(5): 675-684.
    [2] 和萍,刘鑫,宫智杰,等. 高比例可再生能源电力系统源荷储联合调峰分层优化运行[J]. 电力系统保护与控制,2024,52(18):112-122.
    HE Ping, LIU Xin, GONG Zhijie, et al. Hierarchical optimization operation model for joint peak-load regulation of source-load-storage in a high proportion of renewable energy power system[J]. Power System Protection and Control, 2024, 52(18): 112-122.
    [3] 周步祥,蔡宇豪,邱一苇,等. 考虑电、氢、氨市场的可再生能源电制氢合成氨系统多主体合作运行策略[J]. 电力建设,2024,45(11):50-64.
    ZHOU Buxiang, CAI Yuhao, QIU Yiwei, et al. Multi-stakeholder cooperative operation strategy of renewable power to ammonia systems considering the electricity, hydrogen and ammonia markets[J]. Electric Power Construction, 2024, 45(11): 50-64.
    [4] 黄梦旗,李勇汇,曾海燕,等. 计及高渗透率分布式电源的韧性配电网数据驱动鲁棒规划方法[J]. 电力建设,2023,44(6):79-90.
    HUANG Mengqi, LI Yonghui, ZENG Haiyan, et al. Data-driven robust planning method for resilient distribution networks considering high-permeability distributed generation[J]. Electric Power Construction, 2023, 44(6): 79-90.
    [5] 陈春,曹伯仲,曹一家,等. 高比例分布式电源接入下基于变分模态分解的励磁涌流辨识[J]. 电力系统保护与控制,2024,52(20):94-104.
    CHEN Chun, CAO Bozhong, CAO Yijia, et al. Identification of inrush current based on variational modal decomposition under a high proportion of distributed generation[J]. Power System Protection and Control, 2024, 52(20): 94-104.
    [6] 孙宁言,陈羽,徐丙垠,等. 含高比例分布式电源配电网分布式供电恢复方法[J]. 电力系统自动化,2024,48(10):161-170.
    SUN Ningyan, CHEN Yu, XU Bingyin, et al. Distributed power supply restoration method for distribution network with high proportion of distributed generators[J]. Automation of Electric Power Systems, 2024, 48(10): 161-170.
    [7] 陈楚靓,李晓露,纪坤华,等. 考虑源荷储匹配的配电网集群划分与优化运行[J]. 电力建设,2023,44(9):80-93.
    CHEN Chujing, LI Xiaolu, JI Kunhua, et al. Distribution network cluster partition and optimal operation considering source-load-storage matching[J]. Electric Power Construction, 2023, 44(9): 80-93.
    [8] 徐立超,杨景嵛,熊泽昊. 基于改进灰色聚类法的配电网供电分区方法[J]. 电工技术,2021(13):81-84.
    XU Lichao, YANG Jingyu, XIONG Zehao. A method of power distribution network classification based on improved grey cluster[J]. Electric Engineering, 2021(13): 81-84.
    [9] 于琳,孙莹,徐然,等. 改进粒子群优化算法及其在电网无功分区中的应用[J]. 电力系统自动化,2017,41(3):89-95,128.
    YU Lin, SUN Ying, XU Ran, et al. Improved particle swarm optimization algorithm and its application in reactive power partitioning of power grid[J]. Automation of Electric Power Systems, 2017, 41(3): 89-95,128.
    [10] 蔡永翔,唐巍,张璐,等. 基于光伏逆变器无功调节的低压配电网多模式电压控制[J]. 电力系统自动化,2017,41(13):133-141.
    CAI Yongxiang, TANG Wei, ZHANG Lu, et al. Multi-mode voltage control in low distribution networks based on reactive power regulation of photovoltaic inverters[J]. Automation of Electric Power Systems, 2017, 41(13): 133-141.
    [11] 闫丽梅,丁泽华. 基于谱聚类的主动配电网多时间尺度无功优化策略[J]. 浙江电力,2024,43(2):58-68.
    YAN Limei, DING Zehua. A multi-timescale reactive power optimization strategy for active distribution networks based on spectral clustering[J]. Zhejiang Electric Power, 2024, 43(2): 58-68.
    [12] 胡丹尔,彭勇刚,韦巍,等. 多时间尺度的配电网深度强化学习无功优化策略[J]. 中国电机工程学报,2022,42(14):5034-5045.
    HU Daner, PENG Yonggang, WEI Wei, et al. Multi-timescale deep reinforcement learning for reactive power optimization of distribution network[J]. Proceedings of the CSEE, 2022, 42(14): 5034-5045.
    [13] 艾聪林,何东,王振忠,等. 基于Fisher最优分割法的配电网多时间尺度无功优化[J]. 电工技术,2024(4):150-154.
    AI Conglin, HE Dong, WANG Zhenzhong, et al. Multi-time-scale reactive power optimization of distribution network based on Fisher optimal segmentation method[J]. Electric Engineering, 2024(4): 150-154.
    [14] LI W, MONTI A, LUO M, et al. VPNET: a co-simulation framework for analyzing communication channel effects on power systems[C]//2011 IEEE Electric Ship Technologies Symposium. Alexandria, VA, USA. IEEE, 2011: 143-149.
    [15] 顾晨骁,顾伟,陈超,等. 分布式电源集群控制与电力信息实时仿真研究[J]. 电力系统保护与控制,2020,48(4):64-71.
    GU Chenxiao, GU Wei, CHEN Chao, et al. Distributed power cluster control and research on power information real-time simulation[J]. Power System Protection and Control, 2020, 48(4): 64-71.
    [16] 杨珺,侯俊浩,刘亚威,等. 分布式协同控制方法及在电力系统中的应用综述[J]. 电工技术学报,2021,36(19):4035-4049.
    YANG Jun, HOU Junhao, LIU Yawei, et al. Distributed cooperative control method and application in power system[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4035-4049.
    [17] 胡珺如,窦晓波,李晨,等. 面向中低压配电网的分布式协同无功优化策略[J]. 电力系统自动化,2021,45(22):47-54.
    HU Junru, DOU Xiaobo, LI Chen, et al. Distributed cooperative reactive power optimization strategy for medium-and low-voltage distribution network[J]. Automation of Electric Power Systems, 2021, 45(22): 47-54.
    [18] 柴园园,刘一欣,王成山,等. 含不完全量测的分布式光伏发电集群电压协调控制[J]. 中国电机工程学报,2019,39(8):2202-2212,3.
    CHAI Yuanyuan, LIU Yixin, WANG Chengshan, et al. Coordinated voltage control for distributed PVs clusters with incomplete measurements[J]. Proceedings of the CSEE, 2019, 39(8): 2202-2212,3.
    [19] JIAO W S, CHEN J, WU Q W, et al. Distributed coordinated voltage control for distribution networks with DG and OLTC based on MPC and gradient projection[J]. IEEE Transactions on Power Systems, 2022, 37(1): 680-690.
    [20] 葛津铭,刘英儒,庞丹,等. 含高渗透率光伏配电网的集群划分电压控制策略[J]. 高电压技术,2024,50(1):74-82.
    GE Jinming, LIU Yingru, PANG Dan, et al. Cluster division voltage control strategy of photovoltaic distribution network with high permeability[J]. High Voltage Engineering, 2024, 50(1): 74-82.
    [21] LI P, JI J, JI H R, et al. MPC-based local voltage control strategy of DGs in active distribution networks[J]. IEEE Transactions on Sustainable Energy, 2020, 11(4): 2911-2921.
    [22] 王家武,赵佃云,刘长锋,等. 基于目标级联法的多主体主动配电网自治协同优化[J]. 中国电力,2024,57(7):214-226.
    WANG Jiawu, ZHAO Dianyun, LIU Changfeng, et al. Analytical target cascading based active distribution network level multi-agent autonomous collaborative optimization[J]. Electric Power, 2024, 57(7): 214-226.
    [23] 杜红卫,尉同正,夏栋,等. 基于集群动态划分的配电网无功电压自律-协同控制[J]. 电力系统自动化,2024,48(10):171-181.
    DU Hongwei, WEI Tongzheng, XIA Dong, et al. Reactive voltage self-regulation and coordination control in distribution networks based on cluster dynamic partition[J]. Automation of Electric Power Systems, 2024, 48(10): 171-181.
    [24] 赵晶晶,朱炯达,刘帅,等. 基于集群划分的配电网多时间尺度分布式有功-无功协同优化方法[J]. 电测与仪表,2024,61(10):57-66.
    ZHAO Jingjing, ZHU Jiongda, LIU Shuai, et al. Multi-timescale distributed active and reactive power coordinated optimization method of distributed network based on cluster division[J]. Electrical Measurement & Instrumentation, 2024, 61(10): 57-66.
    [25] ZHAO B, XU Z C, XU C, et al. Network partition-based zonal voltage control for distribution networks with distributed PV systems[J]. IEEE Transactions on Smart Grid, 2018, 9(5): 4087-4098.
    [26] LI P S, ZHANG C, WU Z J, et al. Distributed adaptive robust voltage/VAR control with network partition in active distribution networks[J]. IEEE Transactions on Smart Grid, 2020, 11(3): 2245-2256.
    [27] 陈珩. 电力系统稳态分析[M]. 4版. 北京:中国电力出版社,2015.
    CHEN Heng. Steady state analysis of power systems[M]. 4th ed. Beijing: China Electric Power Press, 2015.
    相似文献
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

蒋春容,朱博汶,周旭峰,陆佳妮,曾艾东.基于分布式光伏集群控制的主动配电网电压优化策略[J].电力工程技术,2025,44(3):188-200

复制
分享
文章指标
  • 点击次数:56
  • 下载次数: 146
  • HTML阅读次数: 120
  • 引用次数: 0
历史
  • 收稿日期:2024-09-28
  • 最后修改日期:2024-12-05
  • 在线发布日期: 2025-06-04
  • 出版日期: 2025-05-28
文章二维码