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Using grey target theory for Power Quality Evaluation Based on Power Quality Monitoring Data

Energy Engineering 2022年第1期119卷 359-369页

作者： Qiang Yu Xiankai Chen Xiaoyue Li Chaoqun Zhou Zhichao Li State Grid Qingdao Power Supply Company Qingdao266000China

Smart grid puts forward higher requirements for power *** quality evaluation can provide a decision-making basis for quality *** on power quality monitoring data,a grey target method is proposed for power quality *** grey target is composed of power quality evaluation standard and power quality monitoring data to be *** with the characteristics of each power quality evaluation index,the target center of the whole grey target system is ***,the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to construct the power quality grey correlation difference information ***,the target center coefficient and target degree of power quality are calculated to realize the comprehensive evaluation of power quality,and the evaluation grade of power quality monitoring data to be evaluated is *** with the evaluation results of the existing literature,the effectiveness of the proposed method is verified,which shows that grey target theory is reasonable in the comprehensive evaluation of power quality.

关键词： Smart grid power quality evaluation grey target theory monitoring data

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Power System Load Forecasting Based on Fuzzy Clustering and Gray target theory

Power System Load Forecasting Based on Fuzzy Clustering and ...

引用

2012 International Conference on Future Energy,Environment,and Materials

作者： HAO Jing LIU Dawei LI Zhenxin CHEN Zilai KONG Lingguo College of Electrical Engineering Northeast Dianli University Electric Power Dispatching and Communication Center of Chang Chun Power Supply Corporation

Accuracy of power system load forecasting is affected directly by existing considerable uncertainties, which are accompanied with some correlation among load factors. And this relationship between variables can be eliminated with fuzzy clustering based on historical load in a large number of observations. Carrying out the load factors on the reduction tactics, the impact factors have been classified. Then the target theory is adopted under the standard model of predictors. Then the weight coefficients between the factors category and the predictor are determined in the ways of calculating contributing degrees to various components indicators. For verification, an actual data is provided from a power grid and sorted into four types. Contributing degrees for predicting of the 4 factors are found. It is shown by result analysis that the combined method takes advantages of accuracy and efficiency in prediction.

关键词： fuzzy clustering grey target theory contributing degrees weight coefficient

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