Standardization of Short-Term Load Forecasting Models

Abstract

There has been a significant production of load forecasting models over the last 5 years. These models present a wide variety of techniques, most of them using novel artificial intelligence approaches. Load forecasting is a complex matter and it is the result of several processes that, depending on the database, may be of more or less importance. However, most models focus their attention only on one process like the “forecasting engine”, neglecting other processes like variable selection or pre-processing. This paper proposes a standard scheme for load forecasting models that includes all subprocesses within load forecasting. The analysis of load forecasting models through this scheme allows identifying the effect of each process on the overall performance of the model. Also, proposing load forecasting models following this scheme will enhance benchmarking possibilities and hybridization of models. Finally, this paper presents such analysis of an actual load forecasting model.