Comparative Analysis of Load Forecasting Models for Varying Time Horizons and Load Aggregation Levels

Leonard Burg, Gonca Gürses-Tran, Reinhard Madlener and Antonello Monti
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Leonard Burg: School of Business and Economics, RWTH Aachen University, 52062 Aachen, Germany
Gonca Gürses-Tran: E.ON Energy Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University, 52074 Aachen, Germany
Antonello Monti: E.ON Energy Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University, 52074 Aachen, Germany

Energies, 2021, vol. 14, issue 21, 1-16

Abstract: Power system operators are confronted with a multitude of new forecasting tasks to ensure a constant supply security despite the decreasing number of fully controllable energy producers. With this paper, we aim to facilitate the selection of suitable forecasting approaches for the load forecasting problem. First, we provide a classification of load forecasting cases in two dimensions: temporal and hierarchical. Then, we identify typical features and models for forecasting and compare their applicability in a structured manner depending on six previously defined cases. These models are compared against real data in terms of their computational effort and accuracy during development and testing. From this comparative analysis, we derive a generic guide for the selection of the best prediction models and features per case.

Keywords: load forecasting; time series; energy flexibility; day-ahead market; supply security (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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