Transactions of China Electrotechnical Society  2015, Vol. 30 Issue (24): 196-205    DOI:
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Dynamic Load Model Parameter Prediction Using Confidence-Interval-Based Fuzzy Linear Regression
Huang Yulong1, Liu Mingbo2, Zheng Wenjie3, Liu Xindong1, Chen Xun3
1. Jinan University Zhuhai 519070 China; 2. South China University of Technology Guangzhou 510640 China; 3. Electric Power Research Institute of Guangdong Power Grid Corporation Guangzhou 510600 China

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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 wordsConfidence interval      fuzzy linear regression      dynamic load model parameters      vertices method     
Received: 19 June 2014      Published: 30 December 2015
PACS: TM714  
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Huang Yulong
Liu Mingbo
Zheng Wenjie
Liu Xindong
Chen Xun
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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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