Pattern similarity-based machine learning methods for mid-term load forecasting: A comparative study

Application of SVM Methods for Mid-Term Load Forecasting*

This paper presents an approach for the medium-term load forecasting using Support Vector Machines (SVMs). The proposed SVM model was employed to predict the maximum daily load demand for the period of a month. Analyses of available data were performed and the most important features for the construction of SVM model are selected. It was shown that the size and the structure of the training set...

Machine learning based switching model for electricity load forecasting

In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts...

Similarity-based Approaches to Short-term Load Forecasting

Cloud Computing for Short-Term Load Forecasting Based on Machine Learning Technique

Short-term electric load forecasting (STLF) plays the main role in making operational decisions in any electrical power system. The implementation of forecasting algorithms collides with the high computational power needed to perform the complex perdition processes on large datasets. In this paper, a cloudbased STLF algorithm is implemented. The performance analysis of the proposed system was c...

An Ensemble Model Based on Machine Learning Methods and Data Preprocessing for Short-Term Electric Load Forecasting

The experience with deregulated electricity market has shown the increasingly important role of short-term electric load forecasting in the energy producing and scheduling. However, because of nonlinear, stochastic and nonstable characteristics associated with the electric load series, it is extremely difficult to precisely forecast the electric load. This paper aims to establish a novel ensemb...