Advancing Standard Load Profiles with Data-Driven Techniques and Recent Datasets

TL;DR

This paper updates Standard Load Profiles for Germany using recent smart meter data, validates assumptions, proposes improvements, and introduces a Fourier Series-based model as an alternative, enhancing load estimation accuracy.

Contribution

It provides an updated SLP for Germany based on recent data, validates and improves existing methods, and introduces a Fourier Series-based alternative model.

Findings

Updated SLP models show improved accuracy

Fourier Series-based model performs comparably to traditional methods

Proposed improvements enhance applicability and reliability

Abstract

Estimating electricity consumption accurately is essential for the planning and operation of energy systems, as well as for billing processes. Standard Load Profiles (SLP) are widely used to estimate consumption patterns of different user groups. However, in Germany these SLP were formulated using historical data from over 20 years ago and have not been adjusted since. Changing electricity consumption behaviour, which leads to increasing deviations between load patterns and SLP, results in a need for a revision taking into account new data. The growing number of smart meters provides a large measurement database, which enables more accurate load modelling. This paper creates updated SLP using recent data. In addition, the assumptions of the SLP method are validated and improvements are proposed, taking into account the ease of applicability. Furthermore, a Fourier Series-based model is proposed as an alternative SLP model. The different models are compared and evaluated.