基于互近似熵的微电网并网同步检测方法
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摘要
针对经典的微电网并网同步检测方法需同时比较两侧电压相位、幅值和频率的繁琐过程,提出基于互近似熵的微电网并网同步检测方法。该方法只需利用单一的互近似熵值就能比较并网开关两侧电压的相似度。分析基于互近似熵的微电网并网同步检测方法的原理和优势,研究微电网并网同步检测方法中互近似熵参数取值等关键问题,进而具体介绍基于互近似熵的微电网并网同步检测方法的实现步骤。最后在Matlab中搭建微电网通过断路器并入配电网的简化模型,仿真微电网开关两侧电压相位、幅值和频率变化时的互近似熵值。仿真结果证明了该方法的有效性。
Classic synchronization closing detection method of microgrid needs the tedious process to simultaneously compare the voltage phase, amplitude and frequency on both sides. Synchronization closing detection method of microgrid based on mutual approximate entropy is proposed, which only needs the single value of mutual approximate entropy to compare the voltage similarity on both sides. The principle and advantage of synchronization detection closing method of microgrid based on mutual approximate entropy are analyzed. And the key issue such as the value setting of the method is studied. Then the implementation steps of the method is introduced in detail. Finally the simplified model of microgrid connecting to distribution network is constructed in Matlab, where the value of mutual approximate entropy is simulated on the change of voltage phase, amplitude and frequency. The simulation result verifies the effectiveness of the method.
Classic synchronization closing detection method of microgrid needs the tedious process to simultaneously compare the voltage phase, amplitude and frequency on both sides. Synchronization closing detection method of microgrid based on mutual approximate entropy is proposed, which only needs the single value of mutual approximate entropy to compare the voltage similarity on both sides. The principle and advantage of synchronization detection closing method of microgrid based on mutual approximate entropy are analyzed. And the key issue such as the value setting of the method is studied. Then the implementation steps of the method is introduced in detail. Finally the simplified model of microgrid connecting to distribution network is constructed in Matlab, where the value of mutual approximate entropy is simulated on the change of voltage phase, amplitude and frequency. The simulation result verifies the effectiveness of the method.
引文
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[2]陈海东.于细菌菌落优化算法分布式电源优化配置[J].电力系统保护与控制,2015,43(21):106-111.CHEN Haidong.Optimal power flow of distribution network with distributed generation based on bacterial colony optimization[J].Power System Protection and Control,2015,43(21):106-111.
[3]胡文平,于腾凯,巫伟南.一种基于云预测模型的电网综合风险评估方法[J].电力系统保护与控制,2015,43(5):35-41.HU Wenping,YU Tengkai,WU Weinan.A comprehensive power grid risk assessment method based on cloud prediction model[J].Power System Protection and Control,2015,43(5):35-41.
[4]黄文焘,邰能灵,唐跃中.交流微电网系统并网保护分析[J].电力系统自动化,2013,37(1):180-185.HUANG Wentao,TAI Nengling,TANG Yuezhong.Analysis of interconnection protection in AC microgrid[J].Automation of Electric Power Systems,2013,37(1):180-185.
[5]国家标准“微电网接入配电网系统调试及验收规范”启动[EB/OL].[2013-07-02/2013-11-12].http://xinxihua.bjx.com.cn/news/20130702/443159.html.National standard test and acceptance guide for connecting microgrids to distribution systems[EB/OL].[2013-07-02/2013-11-12].http://xinxihua.bjx.com.cn/news/20130702/443159.html.
[6]杨志淳,乐健,刘开培,等.微电网并网标准研究[J].电力系统保护与控制,2012,40(2):66-71,76.YANG Zhichun,LE Jian,LIU Kaipei,et al.Study on the standard of the grid-connected microgrids[J].Power System Protection and Control,2012,40(2):66-71,76.
[7]蔡宇,林今,宋永华,等.基于模型预测控制的主动配电网电压控制[J].电工技术学报,2015,30(23):42-49.CAI Yu,LIN Jin,SONG Yonghua,et al.Voltage control of active distribution network based on model predictive control[J].Transactions of China Electrotechnical Society,2015,30(23):42-49.
[8]刘振国,胡亚平,陈炯聪,等.基于双层优化的微电网系统规划设计方法[J].电力系统保护与控制,2015,43(8):123-133.LIU Zhenguo,HU Yaping,CHEN Jiongcong,et al.A planning and design method for microgrid based on two-stage optimization[J].Power System Protection and Control,2015,43(8):123-133
[9]迟吉运,韦钢,李功新,等.复杂有源配电网供电路径快速优化[J].电工技术学报,2017,32(13):219-228.CHI Jiyun,WEI Gang,LI Gongxin,et al.Fast optimization of power supply path for complex active distribution networks[J].Transactions of China Electrotechnical Society,2017,32(13):219-228.
[10]郝晓弘,田江博,陈伟,等.基于信息嫡和数学形态学的电压跌落持续时间检测方法[J].电力系统保护与控制,2012,40(11):30-35.HAO Xiaohong,TIAN Jiangbo,CHEN Wei,et al.Detection method of voltage sag duration based on information-entropy and mathematical morphology[J].Power System Protection and Control,2012,40(11):30-35.
[11]李志民,李卫星,李勃龙.熵原理及其在电力系统可靠性中的应用[J].电力系统及其自动化学报,2001,13(3):37-39.LI Zhimin,LI Weixing,LI Bolong.Entropy principle and its application in power system reliability[J].Proceedings of the CSU-EPSA,2001,13(3):37-39.
[12]陈汝斯,林涛,余光正,等.计及电能质量影响的智能配电网孤岛划分策略[J].电工技术学报,2016,31(增刊2):150-158.CHEN Rusi,LIN Tao,YU Guangzheng,et al.Island separation strategy of smart distribution grid considering the effects of power quality factors[J].Transactions of China Electrotechnical Society,2016,31(S2):150-158.
[13]刘荣荣,张靠社,张刚,等.基于自适应人工鱼群算法的微电网优化运行[J].电网与清洁能源,2017,32(4):71-76.LIU Rongrong,ZHANG Kaoshe,ZHANG Gang,et al.Optimized operation of microgrid based on adaptive artificial fish swarm algorithm[J].Power System and Clean Energy,2017,32(4):71-76.
[14]顾雪楠,陈星莺,王勇,等.面向源网互动的智能配电网日前调度研究[J].电网与清洁能源,2017,32(4):57-63.GU Xuenan,CHEN Xingying,WANG Yong,et al.The scheduling of intelligent distribution network for the interaction of the source network[J].Power System and Clean Energy,2017,32(4):57-63.
[15]崔立明,孟丽霞,袁红.超低排放改造及其对供电成本的影响[J].热力发电,2017,46(6):119-124.CUI Liming,MENG Lixia,YUAN Hong.Ultra-low emission and its effect on power supply cost[J].Thermal Power Generation,2017,46(6):119-124.
[16]曾德良,简一帆.火电厂负荷分配的多目标优化算法[J].热力发电,2017,46(5):98-104.ZENG Deliang,JIAN Yifan.Multi-objective optimization algorithm for load distribution in thermal power plant[J].Thermal Power Generation,2017,46(5):98-104.