基于可信区间的模糊线性回归动态负荷参数预测

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Abstract The accuracy of load model greatly impacts power system stability simulation and control. Since real load characteristics are time-varying all along, load model parameters built on some historical data are only valid within limited scopes. Currently classification and synthesis approach, multi-curve identification method, and dominant parameter online identification technique are mainly adopted to deal with time-variation problem of load characteristics. However these methods decrease model fitting precision to some degree. In addition, because system operating conditions and real load characteristics are changing all along, limited classifications fail to obtain good boundaries, even may have overlap. After analyzing the influencing factors of load model parameters, this paper proposes a prediction method of dynamic load model parameters using confidence-interval-based fuzzy linear regression, to recurrently find dynamic load model parameters from historical database that match the operating condition of real time system. Thus the selected load model parameters will be more suitable to the dynamic characteristics of real load as the database size grows. The proposed method is verified by the field measurement data at two 220kV substations from a certain large city.

Key words： Confidence interval fuzzy linear regression dynamic load model parameters vertices method

Received: 19 June 2014 Published: 30 December 2015

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TM714

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	Huang Yulong
	Liu Mingbo
	Zheng Wenjie
	Liu Xindong
	Chen Xun

Cite this article:

Huang Yulong,Liu Mingbo,Zheng Wenjie等. Dynamic Load Model Parameter Prediction Using Confidence-Interval-Based Fuzzy Linear Regression[J]. Transactions of China Electrotechnical Society, 2015, 30(24): 196-205.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2015/V30/I24/196

[1] 徐伟, 薛禹胜, 陈实, 等. 从实测轨迹提取知识时的困难及展望[J]. 电力系统自动化, 2009, 33(15): 1-7.
Xu Wei, Xue Yusheng, Chen Shi, et al. Difficulties and prospects of knowledge extracting from measured trajectories[J]. Automation of Electric Power Systems, 2009, 33(15): 1-7.
[2] 郝丽丽, 薛禹胜, Dong Zhaoyang, 等. 电力系统受扰轨迹的差异度及其在参数识别中的应用[J]. 电力系统自动化, 2010, 34(11): 1-7.
Hao Lili, Xue Yusheng, Dong Zhaoyang, et al. Difference degree of power system disturbed trajectories and its applications in parameter identification[J]. Auto- mation of Electric Power Systems, 2010, 34(11): 1-7.
[3] 张伶俐, 周文, 章健, 等. 面向综合的电力负荷动特性建模[J]. 中国电机工程学报, 1999, 19(9): 36-40.
Zhang Lingli, Zhou Wen, Zhang Jian, et al. The synthesis of dynamic load characteristics[J]. Proceedings of the CSEE, 1999, 19(9): 36-40.
[4] 鞠平, 金艳, 吴峰, 等. 综合负荷特性的分类综合方法及其应用[J]. 电力系统自动化, 2004, 28(1): 64-68.
Ju Ping, Jin Yan, Wu Feng, et al. Studies on classification and synthesis of composite dynamic loads[J]. Auto- mation of Electric Power Systems, 2004, 28(1): 64-68.
[5] 石景海, 贺仁睦. 基于量测的负荷建模—分类算法[J]. 中国电机工程学报, 2004, 24(2): 78-82.
Shi Jinghai, He Renmu. Measurement-based load modeling—sorting algorithm[J]. Proceedings of the CSEE, 2004, 24(2): 78-82.
[6] 石景海. 考虑负荷时变性的大区电网负荷建模研究[D]. 北京: 华北电力大学, 2004.
[7] 林舜江, 李欣然, 刘杨华, 等. 电力负荷动特性分类方法研究[J]. 电力系统自动化, 2005, 29(22): 33-38.
Lin Shunjiang, Li Xinran, Chen Yanghua, et al. A classification method for aggregated load dynamic characteristics[J]. Automation of Electric Power Systems, 2005, 29(22): 33-38.
[8] 李欣然, 林舜江, 刘杨华, 等. 基于实测响应空间的负荷动特性分类原理与方法[J]. 中国电机工程学报, 2006, 26(8): 39-44.
Li Xinran, Lin Shunjiang, Chen Yanghua, et al. A new classification method for aggregate load dynamic characteristics based on field measured response[J]. Proceedings of the CSEE, 2006, 26(8): 39-44.
[9] 林舜江, 李欣然, 李培强, 等. 基于实测响应空间的负荷动特性直接综合方法[J]. 中国电机工程学报, 2006, 26(21): 36-42.
Lin Shunjiang, Li Xinran, Li Peiqiang, et al. A novel direct synthesis method for aggregate load dynamic characteristics based on field measured response[J]. Proceedings of the CSEE, 2006, 26(21): 36-42.
[10] 林舜江. 负荷动特性的建模及其对电压稳定的影响研究[D]. 长沙: 湖南大学, 2008.
[11] 周开乐, 杨善林. 基于改进模糊C均值算法的电力负荷特性分类[J]. 电力系统保护与控制, 2012, 40(22): 58-63.
Zhou Kaile, Yang Shanlin. An improved fuzzy C-means algorithm for power load characteristics classification[J]. Power System Protection and Control, 2012, 40(22): 58-63.
[12] 白建勋, 杨洪耕, 吴传来, 等. 基于自适应遗传算法的负荷特性分类[J]. 电工电能新技术, 2012, 31(4): 92-96.
Bai Jianxun, Yang Honggeng, Wu Chuanlai, et al. Load characteristics classification based on adaptive genetic algorithm[J]. Advanced Technology of Electrical Engineering and Energy, 2012, 31(4): 92-96.
[13] 黄毅成, 杨洪耕. 改进遗传 K 均值算法在负荷特性分类的应用[J].电力系统及其自动化学报, 2014, 26(7): 70-75.
Huang Yicheng, Yang Hongheng. Application of improved genetic and K -means algorithm on load characteristics classification[J]. Proceedings of the CSU-EPSA, 2014, 26(7): 70-75.
[14] 郑晓雨, 郑静媛, 刘东, 等. 负荷模型参数简化对负荷分类结果的影响[J]. 中国电力, 2013, 46(11): 47-51.
Zheng Xiaoyu, Zheng Jingyuan, Liu Dong, et al. Impact of model parameter reduction on load classification[J]. Electric Power, 2013, 46(11): 47-51.
[15] He Renmu, Ma Jin, David J Hill. Composite load modeling via measurement approach[J]. IEEE Trans- actions on Power Systems, 2006, 21(2): 663-672.
[16] 林济铿, 刘露, 张闻博, 等. 基于随机模糊聚类的负荷建模与参数辨识[J].电力系统自动化, 2013, 37(14): 50-58.
Lin Jikeng, Liu Lu, Zhang Wenbo, et al. Load modeling and parameter identification based on random fuzziness clustering[J]. Automation of Electric Power Systems, 2013, 37(14): 50-58.
[17] Zheng Jinghong, Wang Xiaoyu, Zhu Shouzhen. A novel real-time load modeling method for fast large- disturbance and short-term voltage stability analysis[J]. International Transactions on Electrical Energy Systems, 2013, 23(8): 1373-1395.
[18] 张树卿, 韩英铎, 于松泰, 等. 区域综合负荷动态等值参数在线测辨关键技术[J]. 电力系统自动化, 2012, 36(19): 114-121.
Zhang Shuqing, Han Yingduo, Yu Songtai, et al. Key techniques for composite load area integral equivalence and online parameter identification[J]. Automation of Electric Power Systems, 2012, 36(19): 114-121.
[19] 张旭, 梁军, 贠志皓, 等. 考虑风电接入不确定性的广义负荷建模及应用[J].电力系统自动化, 2014, 38(20): 61-67.
Zhang Xu, Liang Jun, Yun Zhihao, et al. Generalized load modeling and its application considering uncer- tainty of wind power integration[J]. Automation of Electric Power Systems, 2014, 38(20): 61-67.
[20] Watada J, Wang Shunming, Pedrycz W. Building confidence-interval-based fuzzy random regression models[J]. IEEE Transactions on Fuzzy Systems, 2009, 17(6): 1273-1283.
[21] Liu Baoding. Uncertainty theory[M]. Berlin Heidel- berg, Germany: Springer-Verlag, 2010.
[22] Liu B, Liu Y K. Expected value of fuzzy variable and fuzzy expected value models[J]. IEEE Transactions on Fuzzy Systems, 2002, 10(4): 445-450.
[23] Liu Y K, Liu B. Fuzzy random variable: A scalar expected value operator[J]. Fuzzy Optimization Deci- sion Making, 2003, 2(2): 143-160.
[24] Watada J, Wang S. Regression model based on fuzzy random variables, views on fuzzy sets and systems from different perspectives[M]. Berlin, Germany: Springer-Verlag, 2009.
[25] 黄玉龙, 陈迅, 刘明波, 等. 动态负荷模型参数辨识的微分进化算法[J]. 电工技术学报, 2013, 28(11): 270-277.
Huang Yulong, Chen Xun, Liu Mingbo, et al. Differ- ential evolution algorithm for dynamic load model parameter identification[J]. Transactions of China Electrotechnical Society, 2013, 28(11): 270-277.
[26] 尹建华, 黄东启, 艾芊. 基于电能质量装置数据和改进克隆选择算法的电力动态负荷建模[J]. 南方电网技术, 2011, 5(6): 42-47.
Yin Jianhua, Huang Dongqi, Ai Qian. Electrical dynamic load modeling based on the power quality equipments data and the improved clone selection algorithm[J]. Southern Power System Technology, 2011, 5(6): 42-47.
[27] IEEE Task Force on Load Representation for Dynamic Performance. Standard load models for power flow and dynamic performance simulation[J]. IEEE Transa- ctions on Power Systems, 1995, 10(3): 1302-1313.
[28] 周伟, 牟龙华. 一种基于αβ与dq坐标变换的频率检测算法[J]. 电力系统保护与控制, 2012, 40(1): 62-67.
Zhou Wei, Mu Longhua. A frequency detection algorithm based on αβ and dq coordinate transfor- mation[J]. Power System Protection and Control, 2012, 40(1): 62-67.
[29] 岳毅宏, 韩文秀, 张伟波. 基于关联度的混沌序列局域加权线性回归预测法[J]. 中国电机工程学报, 2004, 24(11): 17-20.
Yue Yihong, Han Wenxiu, Zhang Weibo. Local adding-weight linear regression forecasting method of chaotic series based on degree of incidence[J]. Proceedings of the CSEE, 2004, 24(11): 17-20.
[30] 雷绍兰, 孙才新, 周湶, 等. 电力短期负荷的多变量时间序列线性回归预测方法研究[J]. 中国电机工程学报, 2006, 26(2): 25-29.
Lei Shaolan, Sun Caixin, Zhou Quan, et al. The research of local linear model of short-term electrical load on multivariate time series[J]. Proceedings of the CSEE, 2006, 26(2): 25-29.
[31] 郑晓雨, 贺仁睦, 马进. 逐步多元回归法在负荷模型扩展中的应用[J]. 中国电机工程学报, 2011, 31(4): 72-77.
Zheng Xiaoyu, He Renmu, Ma Jin. Application of stepwise multiple regression to load model exten- tion[J]. Proceedings of the CSEE, 2011, 31(4): 72-77.