Published January 10, 2022 | Version v1
Journal article Open

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

  • 1. School of Business and Economics, RWTH Aachen University
  • 2. E.ON Energy Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University
  • 3. E.ON Energy Research Center, Institute for Future Energy Consumer Needs and Behavior, School of Business and Economics

Description

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.

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Funding

CoordiNet – Large scale campaigns to demonstrate how TSO-DSO shall act in a coordinated manner to procure grid services in the most reliable and efficient way 824414
European Commission