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

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.