Power Quality Prediction, Early Warning, and Control for Points of Common Coupling with Wind Farms

Jingjing Bai, Wei Gu, Xiaodong Yuan, Qun Li, Feng Xue and Xuchong Wang
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Jingjing Bai: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Wei Gu: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Xiaodong Yuan: Jiangsu Electrical Power Company Research Institute, Nanjing 210096, China
Qun Li: Jiangsu Electrical Power Company Research Institute, Nanjing 210096, China
Feng Xue: Dongguan Power Supply Bureau, Dongguan 523000, China
Xuchong Wang: School of Electrical Engineering, Southeast University, Nanjing 210096, China

Energies, 2015, vol. 8, issue 9, 1-18

Abstract: Wind farms can affect the power quality (PQ) of the power supply grid, with subsequent impacts on the safe and stable operation of other electrical equipment. A novel PQ prediction, early warning, and control approach for the common coupling points between wind farms and the network is proposed in this paper. We then quantify PQ problems and provide rational support measures. To obtain predicted PQ data, we first establish a trend analysis model. The model incorporates a distance-based cluster analysis, probability distribution analysis based on polynomial fitting, pattern matching based on similarity, and Monte Carlo random sampling. A data mining algorithm then uses the PQ early warning flow to analyze limit-exceeding and abnormal data, quantify their severity, and output early warning prompts. Finally, PQ decision support is applied to inform both the power suppliers and users of anomalous changes in PQ, and advise on corresponding countermeasures to reduce relevant losses. Case studies show that the proposed approach is effective and feasible, and it has now been applied to an actual PQ monitoring platform.

Keywords: data mining; decision support; early warning; power quality (PQ); trend analysis; wind farm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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