基于几何加权移动平均滤波算法的改进储能平滑控制策略

doi:10.11930/j.issn.1004-9649.201706191

中国电力 ›› 2018, Vol. 51 ›› Issue (3): 105-112.DOI: 10.11930/j.issn.1004-9649.201706191

基于几何加权移动平均滤波算法的改进储能平滑控制策略

李辉¹, 郭忠涵¹, 李肇汉¹, 邱首东²

1. 上海电力学院自动化工程学院, 上海 200090;
2. 国网安徽省电力公司宿州供电公司, 安徽宿州 234000

收稿日期:2017-06-18 修回日期:2017-12-02 出版日期:2018-03-05 发布日期:2018-03-12
作者简介:李辉(1979—),男,安徽颍上人,博士,副教授,从事新能源微电网控制研究,E-mail: elmerlee@163.com。
基金资助:
上海市自然科学基金项目（15ZR1417600）；上海市国际科技合作项目（15220710500）。

Improved Energy Storage Smoothing Control Strategy Based on Geometric Weighted Moving Average Filter Algorithm

LI Hui¹, GUO Zhonghan¹, LI Zhaohan¹, QIU Shoudong²

1. College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. State Grid Suzhou Power Supply Company, Suzhou 234000, China

Received:2017-06-18 Revised:2017-12-02 Online:2018-03-05 Published:2018-03-12
Supported by:
This work is supported by Natural Science Foundation of Shanghai (No. 15ZR1417600) and Shanghai International Science and Technology Cooperation Program (No.15220710500).

摘要/Abstract

摘要： 针对目前光伏并网中采用储能电池对光伏出力进行平滑，以降低光伏出力波动性对电网的影响，提出一种几何加权移动平均滤波算法，得到光伏并网系统中储能电池出力的参考值。该算法对移动平均滤波算法进行改进，不仅改善了滤波器的延迟性，而且具有自适应平抑的能力。在储能电池出力参考值的基础上，提出了采用模糊控制对该参考值进行修正的方法，使得储能电池的荷电状态维持在合理范围，保证储能电池具有最佳运行状态以及最少容量配置。

关键词: 光伏并网, 功率平滑, 储能系统, 几何加权移动平均滤波, 模糊控制

Abstract: For the current use of energy storage in the PV output smoothing, this paper introduces a geometric weighted moving average filtering algorithm to obtain the reference value of the energy output battery in the PV system so as to reduce the impact of PV power on the power grid. By improving the moving average filtering algorithm, the proposed algorithm not only improves the delay of the filter, but also has the ability of adaptive stabilization. On the basis of energy storage output reference value, a new method of modifying the reference value by fuzzy control is proposed, which maintains the state of charge (SOC) of the energy storage battery in a reasonable range to ensure that the energy storage battery has the best running condition and the minimum capacity configuration.

Key words: photovoltaic grid-connection, power smoothing, energy storage system, geometric weighted moving average filter, fuzzy control

中图分类号:

TM73

李辉, 郭忠涵, 李肇汉, 邱首东. 基于几何加权移动平均滤波算法的改进储能平滑控制策略[J]. 中国电力, 2018, 51(3): 105-112.

LI Hui, GUO Zhonghan, LI Zhaohan, QIU Shoudong. Improved Energy Storage Smoothing Control Strategy Based on Geometric Weighted Moving Average Filter Algorithm[J]. Electric Power, 2018, 51(3): 105-112.

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https://www.electricpower.com.cn/CN/Y2018/V51/I3/105

参考文献

[1] 颜苏莉, 孙婧豪. 我国光伏产业的发展现状、存在问题及解决之道[J]. 华北电力大学学报(社会科学版), 2016(1): 9-12. YAN Suli, SUN Jinghao. PV industry in China: current situation, problems and solutions[J]. Journal of North China Electric Power University(Social Sciences), 2016(1): 9-12.
[2] 谷永刚, 王琨, 张波. 分布式发电技术及其应用现状[J]. 电网与清洁能源, 2010 26(6): 38-43. GU Yonggang, WANG Kun, ZHANG Bo.Distributed generation technologies and their current applications[J]. Power System and Clean Energy, 2010, 26(6): 38-43.
[3] 吕双辉, 蔡声霞, 王守相.分布式光伏-储能系统的经济性评估及发展建议[J]. 中国电力, 2015, 48(2): 139-144. LYU Shuanghui, CAI Shengxia, WANG Shouxiang.Economy evaluation and development suggestions for distributed PV-energy storage system in China[J]. Electric Power, 2015, 48(2): 139-144.
[4] 丁明, 王伟胜, 王秀丽, 等. 大规模光伏发电对电力系统影响综述[J]. 中国电机工程学报, 2014, 34(01): 1-14. DING Ming, WANG Weisheng, WANG Xiuli, et al. A review on the effect of large-scale PV generation on power systems[J]. Proceedings of the CSEE, 2014, 34(1): 1-14.
[5] 叶季蕾, 薛金花, 王伟, 等. 储能技术在电力系统中的应用现状与前景[J]. 中国电力, 2014, 47(3): 1-5. YE Jilei, XUE Jinhua, WANG Wei, et al. Application of energy storage technology and its prospect in power system[J]. Electric Power, 2014, 47(3): 1-5.
[6] MURATA A, YAMAGUCHI H, OTANI K.An approximation of the smoothing effect on the output variation of photovoltaic generation system installed densely in a bounded area[J]. IEEJ Transactions on Power and Energy, 2007, 127(11): 1190-1198.
[7] PAATERO J V, LUND P D. Effect of energy storage on variations in wind power[J]. Wind Energy, 2005, 8(4): 421-441.
[8] 张野, 郭力, 贾宏杰, 等. 基于电池荷电状态和可变滤波时间常数的储能控制方法[J]. 电力系统自动化, 2012, 36(6): 34-38, 62. ZHANG Ye, GUO Li, JIA Hongjie, et al. An energy storage control method based on state of charge and variable filter time constant[J]. Automation of Electric Power Systems, 2012, 36(6): 34-38, 62.
[9] 丁明, 吴建锋, 朱承治, 等. 具备荷电状态调节功能的储能系统实时平滑控制策略[J]. 中国电机工程学报, 2013, 33(01): 22-29. DING Ming, WU Jianfeng, ZHU Chengzhi, et al. A real-time smoothing control strategy with SOC adjustment function of storage systems[J]. Proceedings of the CSEE, 2013, 33(1): 22-29.
[10] 谢涛, 曹军威, 高田, 等. 基于滑动最小二乘算法和电池荷电状态的储能系统平滑控制策略[J]. 电力系统保护与控制, 2015, 43(05): 1-7. XIE Tao, CAO Junwei, GAO Tian, et al. An energy storage system smoothing control strategy based on sliding least square algorithm and battery SOC[J]. Power System Protection and Control, 43(5): 1-7.
[11] PEGUEROLES-QUERALT J, BIANCHI F D, GOMIS-BELLMUNT O. A power smoothing system based on super capacitors for renewable distributed generation[J]. IEEE Transactions on Industrial Electronics, 2015, 62(1): 343-350.
[12] 杨锡运, 曹超, 任杰, 等. 利用储能系统平滑光伏波动的模糊聚类经验模态分解方法[J]. 高电压技术, 2016, 42(07): 2127-2133. YANG Xiyun, CAO Jie, REN Jie, et al. Control Method of Smoothing PV Power Output with Battery Energy Storage System Based on Fuzzy Ensemble Empirical Mode Decomposition[J]. High Voltage Engineering, 2016, 42(07): 2127-2133.
[13] JOSEP M.Guerrero, Poh Chiang Loh, Tzung-Lin Lee, et al. Advanced control architectures for intelligent microgrids[J]. IEEE Transactions on Industrial Electronics, 2013, 60(4): 1263-1270.
[14] PAHLEVANI M, EREN S, BAKHSHAI A, et al. A DC-bus voltage control technique for grid-connected AC/DC converters used in smart energy storage units[C]//2015 IEEE 6th International Symposium on Power Electronics for Distributed Generation Systems(PEDG), IEEE Conference Publications, 2015: 1-7.
[15] KOURO S, LEON J I, VINNIKOV D, et al. Grid-connected photovoltaic systems: An overview of recent research and emerging PV converter technology[J]. IEEE Industrial Electronics Magazine, 2015, 9(1): 47-61.
[16] 刘青, 樊世通, 付超, 等. 基于SOC反馈调节的储能平抑光伏功率应用[J]. 电力系统及其自动化学报, 2016, 28(09): 63-67+81. LIU Qing, FAN Shitong, FU Chao, et al. Application of energy storage to restraining photovoltaic power fluctuation based on SOC feedback[J]. Proceedings of the CSU-EPSA, 2016, 28(9): 63-67+81.
[17] 雷珽, 欧阳曾恺, 李征, 等. 平抑风能波动的储能电池SOC与滤波协调控制策略[J]. 电力自动化设备, 2015, (07): 126-131. LEI Ting, OUYANG Zengkai, LI Zheng, et al. Coordinated control of battery SOC maintaining and filtering for wind power fluctuation smoothing[J]. Electric Power Automation Equipment, 2015, 35(7): 126-131.
[18] LI Guo, YE Zhang, CHENG Shangwang. A new battery energy storage system control method based on SOC and Variable filter time constant[C]//2012 IEEE PES Innovative Smart Grid Technologies(ISGT), IEEE Conference Publications, 2012: 1-7.
[19] 李洪宇. 锂离子电池参数估计[D]. 北京: 北方工业大学, 2014.
[20] PASSION K M, YURKOVICH S. 模糊控制[M]. 北京: 清华大学出版社, 2001.
[21] 张国良.模糊控制及其MATLAB应用[M]. 西安: 西安交通大学出版社, 2002.
[22] 任海鹏, 郭鑫, 杨彧, 等. 光伏阵列最大功率跟踪变论域模糊控制[J]. 电工技术学报, 2013, 28(8): 13-19. REN Haipeng, GUO Xin, YANG Yu, et al. Maximum power point tracking of photovoltaic array using variable universe fuzzy controller[J]. Transactions of China Electrotechnical Society, 2013, 28(8): 13-19.

基于几何加权移动平均滤波算法的改进储能平滑控制策略

Improved Energy Storage Smoothing Control Strategy Based on Geometric Weighted Moving Average Filter Algorithm

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基于几何加权移动平均滤波算法的改进储能平滑控制策略

Improved Energy Storage Smoothing Control Strategy Based on Geometric Weighted Moving Average Filter Algorithm

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