Affiliations: [a] Department of Systems and Informatics, Polytechnic Institute of Setúbal, INESC-ID, Setúbal, Portugal | [b] Department of Electrical Engineering, Polytechnic Institute of Setúbal, INESC-Coimbra, Setúbal, Portugal | [x] University of Coimbra and INESC Coimbra, Coimbra, Portugal | [y] Royal Academy of Sciences, Madrid, Spain
Correspondence:
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Corresponding author: J.M. Lourenço, Department of Systems and Informatics, EST Setúbal/IPS, Campus do IPS, Estefanilha 2910-761, Setúbal, Portugal. E-mail: [email protected]
Abstract: This paper establishes a regressive methodology, applied to the electrical distribution sector, to predict the next hour load. The approach followed is based on a Gaussian process model. To create a simple structure for the input regressor only a few instances of the endogenous variables, based on the homologous and contiguous values, were included. Information that allows to evaluate the influence of a derivative term in the quality of the forecasts is also included in the input vector. In order to assess the performance of different load situations the model was tested on a real-load case-study. The case study includes three different electrical distribution substations, representative of typical load consumer's patterns, namely the residential, non-residential and the service sector. The results obtained are in accordance with the values normally accepted in the sector.
Keywords: Gaussian process models, load forecasting, distribution systems, electrical distribution substations
