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| Sag Immunity Level Evaluation of Sensitive Equipment at Node Based on Latin Hypercube Sampling |
| Wei Pengfei1, Xu Yonghai1, Wang Jinhao2, Lei Da2, Chang Xiao2 |
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electrical Power University Beijing 102206 China;
2. State Grid Electric Power Research Institute of Shanxi Electric Power Company Taiyuan 030001 China |
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Abstract According to the poor stability and convergence of Monte Carlo method(MC method), the different tolerance capability of sensitive equipment to different sag types, and the different evaluation scenarios of sensitive equipment operation and planning, a node evaluation method for the immunity level of sensitive equipment based on Latin hypercube sampling(LHS method) is proposed. The random models of short circuit fault are established, the fault information are obtained through LHS method, then a series of sag events can be obtained through the fault simulation and each node immunity level of sensitive equipment in the system is evaluated. The sag type is chosen as one of the basic sag characteristics, and the node sag evaluation is based on the tolerance curves of sensitive equipment to different sag types; then considering the evaluation scenarios of node sensitive equipment operation and planning, the evaluation method and process are given respectively; in view of the planning evaluation scenario, in order to further reflect the difference of immunity level of sensitive equipment at each node, the equipment immunity level index set is proposed. The proposed method can provide a reference for the operation and planning of the sensitive equipment in actual network.
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Received: 10 July 2017
Published: 14 August 2018
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[1] 黄小庆, 曹阳, 吴卫良, 等. 考虑电压暂降指标的电压协调控制方法研究[J]. 电力系统保护与控制, 2015, 43(22): 147-154.
Huang Xiaoqing, Cao Yang, Wu Weiliang, et al.Research on voltage coordination control method considering voltage sag index[J]. Power System Protection and Control, 2015, 43(22): 147-154.
[2] 蒋素琼. 一种用于检测电压暂降的新方法[J]. 电气技术, 2016, 17(11): 56-61.
Jiang Suqiong.The new method of analyzing voltage sags detection[J]. Electrical Engineering, 2016, 17(11): 56-61.
[3] 程志友, 王雪菲, 徐佳. 一种基于复阻抗的电压暂降定位方法[J]. 电力系统保护与控制, 2016, 44(4): 149-154.
Cheng Zhiyou, Wang Xuefei, Xu Jia.A voltage sag detection method based on complex impedance[J]. Power System Protection and Control, 2016, 44(4): 149-154.
[4] 李春海, 李华强, 刘勃江. 基于过程免疫不确定性的工业用户电压暂降经济损失风险评估[J]. 电力自动化设备, 2016, 36(12): 136-142.
Li Chunhai, Li Huaqiang, Liu Bojiang.Risk assessment based on process immunity uncertainty for industrial customers’ financial losses due to voltage sags[J]. Electric Power Automation Equipment, 2016, 36(12): 136-142.
[5] 付锦, 丁蓝, 苟长松. 基于仿电磁学算法的电压暂降状态估计[J]. 电力系统保护与控制, 2017, 45(10): 98-103.
Fu Jin, Ding Lan, Gou Changsong.Voltage sag state estimation based on electromagnetism-like mechanism[J]. Power System Protection and Control, 2017, 45(10): 98-103.
[6] 徐永海, 陶顺, 肖湘宁. 电网中电压暂降和短时间中断[M]. 北京: 中国电力出版社, 2015.
[7] IEEE std 1346-1998. IEEE recommended practice for evaluating electric power system compatibility with electronic process equipment std 1346-1998. IEEE recommended practice for evaluating electric power system compatibility with electronic process equipment[S].1998.
[8] Djokic S Z, Stockman K, Milanovic J V.Sensitivity of AC adjustable speed drives to voltage sags and short interruptions[J]. IEEE Transactions on Power Delivery, 2005, 20(1): 494-505.
[9] Working Group C4.110. Voltage Dip Immunity of Equipment and Installations[R]. CIGRE, 2010.
[10] Santos A D, Barros M T C D. Voltage sags tolerance and responsibility curves[C]// 2015 IEEE Eindhoven PowerTech, Eindhoven, 2015: 1-6.
[11] 易杨, 张尧, 钟庆. 基于蒙特卡罗方法的大型电力用户电压暂降评估[J]. 电网技术, 2008, 32(6): 57-60.
Yi Yang, Zhang Rao, Zhong Qing.Assessment of voltage sags in large power consumer based on Monte Carlo method[J]. Power System Technology, 2008, 32(6): 57-60.
[12] 曾江, 蔡东阳. 基于组合权重的蒙特卡罗电压暂降评估方法[J]. 电网技术, 2016, 40(5): 1469-1475.
Zeng Jiang, Cai Dongyang.A Monte Carlo assessment method of voltage sags based on combination weight[J]. Power System Technology, 2016, 40(5): 1469-1475.
[13] 贾东梨, 刘科研, 盛万兴, 等. 有源配电网故障场景下的电压暂降仿真与评估方法研究[J]. 中国电机工程学报, 2016, 36(5): 1279-1288.
Jia Dongli, Liu Keyan, Sheng Wanxing, et al.Voltage sag simulation and evaluation in active distribution network with fault cases[J]. Proceedings of the CSEE, 2016, 36(5): 1279-1288.
[14] Santos A D, Barros M T C D. Predicting equipment outages due to voltage sags[J]. IEEE Transactions on Power Delivery, 2016, 31(4): 1683-1691.
[15] IEEE Std 1564-2014. IEEE Guide for Voltage Sag Indices Std 1564-2014. IEEE Guide for Voltage Sag Indices[S]. 2014.
[16] 贾清泉, 艾丽, 董海艳, 等. 考虑不确定性的电压暂降不兼容度和影响度评价指标及方法[J]. 电工技术学报, 2017, 32(1): 48-57.
Jia Qingquan, Ai Li, Dong Haiyan, et al.Uncertainty description and assessment of incompatibility & influence index for voltage sags[J]. Transactions of China Electrotechnical Society, 2017, 32(1): 48-57.
[17] 于晗, 钟志勇, 黄杰波, 等. 采用拉丁超立方采样的电力系统概率潮流计算方法[J]. 电力系统自动化, 2009, 33(21): 32-35, 81.
Yu Han, Chung Chiyong, Wong Kitpo, et al.A probabilistic load flow calculation method with Latin hypercube sampling[J]. Automation of Electric Power System, 2009, 33(21): 32-35, 81.
[18] 蒋程, 王硕, 王宝庆, 等. 基于拉丁超立方采样的含风电电力系统的概率可靠性评估[J]. 电工技术学报, 2016, 31(10): 193-206.
Jiang Cheng, Wang Shuo, Wang Baoqing, et al.Probabilistic reliability assessment of power system containing wind power based on Latin hypercube sampling[J]. Transactions of China Electrotechnical Society, 2016, 31(10): 193-206.
[19] 缪鹏彬, 余娟, 史乐峰, 等. 基于改进非参数核密度估计和拉丁超立方抽样的电动公共客车负荷模型[J]. 电工技术学报, 2016, 31(4): 188-193.
Miao Pengbin, Yu Juan, Shi Lefeng, et al.Electric public bus load model based on improved kernel density estimation and Latin hypercube sampling[J]. Transactions of China Electrotechnical Society, 2016, 31(4): 188-193.
[20] Goswnmi S K, Basu S K.A new algorithm for the reconfiguration of distribution feeders for loss minimization[J]. IEEE Transactions on Power Delivery, 1992, 7(3): 1484-1491.
[21] Myo T A, Jovica V M.Stochastic prediction of voltage sags by considering the probability of the failure of the protection system[J]. IEEE Transactions on Power Delivery, 2006, 21(1): 322-329.
[22] Juan A M, Jacinto M A.Voltage sag studies in distribution networks-part III: voltage sag index calculation[J]. IEEE Transactions on Power Delivery, 2006, 21(3): 1689-1697.
[23] 袁媛, 吴丹岳, 林焱, 等. 电压暂降评估体系研究[J]. 电网技术, 2010, 34(6): 128-133.
Yuan Yuan, Wu Danyue, Lin Yan, et al.Study on assessment system of voltage sags[J]. Power System Technology, 2010, 34(6): 128-133.
[24] 孔祥雨, 徐永海, 陶顺. 基于一种电压暂降新型描述的敏感设备免疫能力评估[J]. 电工技术学报, 2015, 30(3): 165-171.
Kong Xiangyu, Xu Yonghai, Tao Shun.Sensitive equipment immunity assessment based on a new voltage sag description[J]. Transactions of China Electrotechnical Society, 2015, 30(3): 165-171.
[25] 杨锡运, 刘欢, 张彬, 等. 基于熵权法的光伏输出功率组合预测模型[J]. 太阳能学报, 2014, 35(5): 744-749.
Yang Xiyun, Liu Huan, Zhang Bin, et al.A Combination method for photovoltaic power for ecasting based on entropy weight method[J]. Acta Energiae Solaris Sinica, 2014, 35(5): 744-749.
[26] 杨晓东, 李庚银, 周明, 等. 电压暂降随机预估的自适应信赖域方法[J]. 中国电机工程学报, 2011, 31(4): 39-44.
Yang Xiaodong, Li Gengyin, Zhou Ming, et al.Adaptive trust region method for stochastic estimation of voltage sags[J]. Proceedings of the CSEE, 2011, 31(4): 39-44.
[27] Park C H, Jang G.Stochastic estimation of voltage sags in a large meshed network[J]. IEEE Transactions on Power Delivery, 2007, 22(3): 1655-1664.
[28] 孔祥雨. 电压暂降特性及其对敏感设备影响评估研究[D]. 北京: 华北电力大学, 2014.
[29] 徐永海, 兰巧倩, 孔祥雨, 等. 电压暂降特征值统计分析及暂降传播特性[J]. 电工技术学报, 2016, 31(11): 165-175.
Xu Yonghai, Lan Qiaoqian, Kong Xiangyu, et al.Statistical analysis of voltage sag characteristics and research on sag propagation property[J]. Transactions of China Electrotechnical Society, 2016, 31(11): 165-175. |
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2018, Vol. 33 
