高级检索

考虑储能的地区电网有功和电压联合控制策略研究

罗金山, 周泊宇, 张艳, 艾欣

罗金山, 周泊宇, 张艳, 等. 考虑储能的地区电网有功和电压联合控制策略研究[J]. 现代电力, 2018, 35(6): 1-8.
引用本文: 罗金山, 周泊宇, 张艳, 等. 考虑储能的地区电网有功和电压联合控制策略研究[J]. 现代电力, 2018, 35(6): 1-8.
shu
LUO Jinshan, ZHOU Boyu, ZHANG Yan, et al. Joint Control Strategy Study of Active Power and Voltage in Regional Power Network Considering Energy Storage[J]. Modern Electric Power, 2018, 35(6): 1-8.
Citation: LUO Jinshan, ZHOU Boyu, ZHANG Yan, et al. Joint Control Strategy Study of Active Power and Voltage in Regional Power Network Considering Energy Storage[J]. Modern Electric Power, 2018, 35(6): 1-8.
shu

考虑储能的地区电网有功和电压联合控制策略研究

  • 1.

    国网经济技术研究院有限公司,北京 102209;

  • 2.

    新能源电力系统国家重点实验室(华北电力大学),北京 102206

基金项目: 国家重点研发计划(2016YFB0900500)
详细信息
    作者简介:

    罗金山(1980—),男,硕士,高级工程师,研究方向为电网规划设计,E-mail:luojinshan@chinasperi.sgcc.com.cn; 周泊宇(1992—),男,硕士研究生,研究方向为电力系统分析与电网规划,E-mail:zhouboyu916@163.com;张 艳(1983—),女,博士,高级工程师,研究方向为电网规划设计,E-mail:zhangyan@chinasperi.sgcc.com.cn;艾 欣(1964—),男,教授,博士生导师,主要研究方向为新能源电力系统及微网,E-mail:aixin@ncepu.edu.cn。

  • 中图分类号: TM71

Joint Control Strategy Study of Active Power and Voltage in Regional Power Network Considering Energy Storage

  • 1.

    State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China;

  • 2.

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University), Beijing 102206, China

摘要

    摘要
  • 摘要: 由于分布式新电源的间歇性和波动性,地区电网的功率波动和电压波动问题凸显。为解决这一问题,本文提出一种考虑储能设备的联合控制策略,首先建立以电网功率波动最小为目标函数的数学模型,然后通过改进粒子群算法进行求解,以此来控制储能的出力,使得地区电网的功率波动最小,并通过储能系统荷电状态反馈控制,保证储能设备不会过度充放电。通过潮流计算得到风电接入时母线的电压波动,选取波动较大的时段,在该母线上进行离散无功补偿,进一步对电压波动进行调节。最后通过IEEE14节点算例进行仿真,在电网中接入风电和储能装置,同时在风电接入母线配置离散无功补偿设备,在完整的一个调度周期内,对比储能不出力和不采用离散无功补偿策略情况下的功率波动和电压波动,表明联合控制策略的有效性。
    Abstract: Because of the intermittent and fluctuation of the distributed renewable power generation, the power fluctuation and voltage fluctuation of the distribution network are serious. In order to solve this problem, a joint control strategy considering energy storage equipment is proposed in this paper. Firstly, the mathematic model with the minimum power fluctuation as the objective function is established, and then the particle swarm optimizer is used to control the energy output, which makes the distribution network power fluctuations minimum. Through the feedback control strategy of charge state for energy storage system, the energy storage equipment will not be excessively charged and discharged. Because the power flow calculation is used to obtain the voltage fluctuation on the access bus of the wind power, the periods that voltage fluctuates greatly are selected. And discrete reactive power compensation is carried out on the bus to further adjust the voltage fluctuation. Finally, the IEEE14-bus distribution network is taken as case, in which the wind power and an energy storage device are connected to the distribution network, and the discrete reactive power compensation equipment is arranged on the access bus of the wind power. In addition, power fluctuations and voltage fluctuations are compared in the case of no storage output or no discrete reactive power compensation in one scheduling period, which shows the validity of joint control strategy.
    • HTML全文
    • 参考文献(22)
  • 艾欣, 董春发. 储能技术在新能源电力系统中的研究综述[J]. 现代电力,2015,32(5):19.

    AI Xin, DONG Chunfa. Review on the application of energy storage technology in power system with renewable energy sources[J]. Modern Electric Power, 2015, 32(5): 19.
    FENG Lin, ZHANG Jingning, LI Guojie, et al. Cost reduction of a hybrid energy storage system considering correlation between wind and PV power[J]. Protection and Control of Modern Power Systems, 2016, 1: 9.
    陈宇豪, 王磊, 杨宇,等. 风储直流微网孤岛运行控制研究[J]. 分布式能源,2016, 1(1):4046.

    CHEN Yuhao, WANG Lei, YANG Yu, et al. Study on autonomous operation and control of wind power and energy storage DC microgrid[J]. Distributed Energy, 2016, 1(1):4046.
    杨李星, 严晓杰, 周宇. 一种基于混合储能的低压直流配电网母线电压控制策略[J].电工电气, 2017(1):3034,42. YANG Lixing, YAN Xiaojie, ZHOU Yu. A kind of busbar voltage control strategy of low-voltage direct current power distribution network based on hybrid energy storage[J]. Electrotechnics Electric, 2017(1): 3034, 42.
    车勇, 彭超锋, 袁铁江, 等. 计及储能的风电平衡区域电网优化划分方法[J].电网技术, 2017, 41(3): 775781.

    CHE Yong, PENG Chaofeng, YUAN Tiejiang, et al. An optimized partitioning method balancing wind power in local power grid considering energy storage system[J]. Power System Technology, 2017, 41(3): 775781.
    MA T, CINTUGLU M H, MOHAMMED O A. Control of a hybrid AC/DC microgrid involving energy storage and pulsed loads[J]. IEEE Transactions on Industry Applications, 2017, 53(1): 567575.
    HASSAN S Z, LI H, ÇAGˇRIYENER uayb, et al. Integration and simulation of wind with hydrogen/supercapacitor storage hybrid system[C]//2017 International Conference on Electrical Engineering (ICEE), Lahore, Pakistan, 2017: 16.
    XIAO J, WANG P, SETYAWAN L. Hierarchical control of hybrid energy storage system in DC microgrids[J]. IEEE Transactions on Industrial Electronics, 2015, 62(8): 49154924.
    赵晶晶, 徐传琳, 吕雪, 等. 微电网一次调频备用容量与储能优化配置方法[J]. 中国电机工程学报, 2017, 37(15): 43244332,4572.

    ZHAO Jingjing, XU Chuanlin, LYU Xue, et al. Optimization of micro-grid primary frequency regulation reserve capacity and energy storage system[J]. Proceedings of the CSEE, 2017, 37(15): 43244332, 4572.
    PULENDRAN S, TATE J E. Energy storage system control for prevention of transient under-frequency load shedding[J]. IEEE Transactions on Smart Grid, 2017,8(2): 927936.
    熊超, 马瑞. 考虑降损和平抑峰谷的配电网储能电池Pareto优化模型[J]. 电力建设, 2015,36(8):3440.

    XIONG Chao, MA Rui. A pareto optimal model for energy storage battery in distribution network considering network loss and peak-valley difference alleviation[J]. Electric Power Construction, 2015, 36(8): 3440.
    吴小刚, 刘宗歧, 田立亭, 等. 基于改进多目标粒子群算法的配电网储能选址定容[J]. 电网技术, 2014,38(12):34053411.

    WU Xiaogang, LIU Zongqi, TIAN Liting, et al. Energy storage device locating and sizing for distribution network based on improved multi-objective particle swarm optimizer[J]. Power System Technology, 2014, 38(12): 34053411.
    赵波,王财胜,周金辉,等. 主动配电网现状与未来发展[J]. 电力系统自动化, 2014, 38(18): 125135.

    ZHAO Bo, WANG Caisheng, ZHOU Jinhui, et al. Present and future development trend of active distribution network[J]. Automation of Electric Power Systems, 2014, 38(18): 125135.
    陈明,顾伟,李鹏,等. 主动配电网分区分布式无功优化控制方法[J]. 现代电力,2017, 34(6): 4044.

    CHEN Ming, GU Wei, LI Peng, et al. Distributed reactive power optimization control method for active distribution network based on subarea division[J]. Modern Electric Power, 2017, 34(6): 4044.
    王永全,李振坤,王永志. 主动配电网多级无功电压协调控制研究[J]. 现代电力,2018,35(1):17. WANG Yongquan, LI Zhenkun, WANG Yongzhi. Research on multi-level reactive power and voltage control of active distribution networks[J]. Modern Electric Power: 2018, 35(1): 17.
    卢锦玲,赵大千,任惠,等. 考虑储能和无功补偿的主动配电网分布式电源规划[J]. 现代电力,2017,34(4):5964.

    LU Jinling, ZHAO Daqian, REN Hui, et al. Distributed generation planning for active distribution network by considering energy storage and reactive power compensation[J]. Modern Electric Power, 2017, 34(4): 5964.
    钟清,张文峰,周佳威,等. 主动配电网分层分布控制策略及实现[J]. 电网技术,2015, 39(6): 15111517.

    ZHONG Qing, ZHANG Wenfeng, ZHOU Jiawei, et al. Hierarchical and distributed control strategy for active distribution network & its implementation[J]. Power System Technology, 2015, 39(6): 15111517.
    曾博,杨煦,张建华. 考虑可再生能源跨区域消纳的主动配电网多目标优化调度[J]. 电工技术学报,2016,31(22):148158.

    ZENG Bo, YANG Xu, ZHANG Jianhua. Multi-objective optimization for active distribution network scheduling considering renewable energy harvesting across regions[J]. Transactions of China Electrotechnical Society, 2016, 31(22): 148158.
    刘文颖, 郭鹏, 但扬清, 等. 含大规模风电接入电网的双时间尺度无功协调控制[J]. 可再生能源, 2016,34(12):18111818.

    LIU Wenying, GUO Peng, DAN Yangqing, et al. Dual-scale scalar coordinated control of large scale wind power connected to power grid[J]. Renewable Energy Resources, 2016, 34(12): 18111818.
    杜波, 刘文颖, 汪宁渤, 等. 基于灵敏度方法的大规模风电接入区域电压优化控制[J]. 电力科学与工程, 2012,28(8):1317.

    DU Bo, LIU Wenying, WANG Ningbo, et al. Voltage optimization control of large scale wind power access area based on sensitivity method[J]. Electric Power Science and Engineering, 2012, 28(8): 1317.
    乔俊飞, 王超, 魏静. 一种具有局部搜索的自适应粒子群算法[J]. 信息与控制, 2015(4):385392. QIAO Junfei, WANG Chao, WEI Jing. An adaptive particle swarm optimization algorithm with local search[J]. Information and Control, 2015(4): 385392.
    吴立坤. 基于粒子群算法的风电场并网电力系统的无功优化[D].南京:南京邮电大学, 2016.
    • 相关文章
    • 施引文献(10)

  • 期刊类型引用(6)

    1. 马锐，李相俊，李文启，高冬学，张景超，宋宁希. 可再生能源供电区域电网中储能系统协同调度策略. 发电技术. 2021(01): 31-39 . 百度学术
    2. 谷哲飞，宋立国，王卫，戴罕奇，王岗红，高雪，宋阳，胡刚，林栋，王雨宸. 集中式储能电站接入下的区域电网自动电压控制. 机械与电子. 2021(03): 39-43+64 . 百度学术
    3. 马实一，衣传宝，周泊宇，牛翔宇，段聪. 考虑储能对减小网架约束新能源弃电的影响研究. 供用电. 2021(12): 74-80 . 百度学术
    4. 张铁峰，左丽莉，李谦，王书峰. 基于PSO-DE算法的分布式光伏优化配置研究. 华北电力大学学报(自然科学版). 2020(02): 56-63 . 百度学术
    5. 于静，金秀章. 基于RBF神经网络的PFC-PID主汽温串级预测控制. 华北电力大学学报(自然科学版). 2020(06): 91-98 . 百度学术
    6. 刘罡. 基于电压灵敏度矩阵的分布式配电网电压控制. 信息技术. 2019(02): 93-97 . 百度学术

    其他类型引用(4)

    • 资源附件(0)
计量
  • 文章访问数:  425
  • HTML全文浏览量:  13
  • PDF下载量:  81
  • 被引次数: 10
出版历程
  • 收稿日期:  2017-07-27
  • 修回日期:  2018-12-17
  • 发布日期:  2018-12-08

目录

摘要
HTML全文
    参考文献(22)
    相关文章
    施引文献(10)
    资源附件(0)

    /

    返回文章
    返回

    《现代电力》编辑部京ICP备12043220号-13

    通讯地址：北京昌平北农路2号华北电力大学D座D0539 邮编：102206 电话: 010-61772300 Email: xddl@vip.163.com

    本系统由北京仁和汇智信息技术有限公司开发  百度统计