In this paper we present a novel method for daily short-term load forecasting, belonging to the class of “similar shape” algorithms. In the proposed method, a number of parameters are optimally tuned via a multi-objective strategy that minimizes the error and the variance of the error, with the objective of providing a final forecast that is at the same time accurate and reliable. We extensively compare our algorithm with other state-of-the-art methods. In particular, we apply our approach upon publicly available data and show that the same algorithm accurately forecasts the load of countries characterized by different size, different weather conditions, and generally different electrical load profiles, in an unsupervised manner.

A Multi-Objective Method for Short-Term Load Forecasting in European Countries

TUCCI, MAURO;CRISOSTOMI, EMANUELE;RAUGI, MARCO
2016-01-01

Abstract

In this paper we present a novel method for daily short-term load forecasting, belonging to the class of “similar shape” algorithms. In the proposed method, a number of parameters are optimally tuned via a multi-objective strategy that minimizes the error and the variance of the error, with the objective of providing a final forecast that is at the same time accurate and reliable. We extensively compare our algorithm with other state-of-the-art methods. In particular, we apply our approach upon publicly available data and show that the same algorithm accurately forecasts the load of countries characterized by different size, different weather conditions, and generally different electrical load profiles, in an unsupervised manner.
2016
Tucci, Mauro; Crisostomi, Emanuele; Giunta, Giuseppe; Raugi, Marco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/764783
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