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This paper presents a statistical model based on a hybrid computational intelligence technique that merging neural networks and fuzzy logic for wind power forecasting. A mesoscale NWP model is used to forecast meteorological variables at a reference point of a wind farm for the next 36 hours at half-hour intervals. The output of the NWP model, together with measured data form SCADA and wind tower,...
The proposed work aimed to forecasting the load by using Artificial Neural Networks (ANN). Short term load forecasting plays an important role for the planning, economic and reliable operation of power systems. Therefore, many statistical methods have been conventionally used for such forecasting, but it has been difficult to construct a proper functional model. This difficulty can be reduced by using...
Electricity consumption has always been one of the critical economic issues in Wenzhou. This paper presents a combination method of grey prediction models and multivariate statistical techniques to forecast the trend of electrical energy consumption in Wenzhou. Hierarchical cluster analysis and discriminant analysis grouped 18 sampling years into three clusters, i.e., relatively less electrical energy...
The forecast of power consumption and loading to serve the major purpose in commercial relations of regional systems with the wholesale power market. The great number of casual and uncertain factors influences to power consumption and predict closely it is impossible. The submitted results allow formulating conditions of trading-monetary relations in the power market for the year-month period. The...
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