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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...
In this paper we present a hybrid methodology built on a combination of clustering and forecasting techniques used to solve the short-term bus load forecasting problem. The proposed method was made in two phases: In the first phase a clustering algorithm is used to identify buses clusters with similar daily load profile and in the second phase is proposed an aggregate structure for to foresee each...
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