iLESS - Intelligent load profile analysis to maximize self-consumption of solar power

Starting point / motivation

Photovoltaic systems (PV systems) offer a sustainable investment with both economic and ecological benefits. By producing their own electricity, households can reduce energy costs and contribute to the energy transition. 

The PV market has seen significant growth over the past decades, driven by technological advancements, decreasing costs, and increasing demand for renewable energy. Forecasts suggest that this market will continue to expand. However, integrating solar power into existing electricity grids poses a challenge, as some regions are already reaching their capacity limits.

One solution could be expanding the grid infrastructure, although this is expensive and dependent on political decisions. On the consumer side, there is potential to increase the self-consumption of the generated electricity. This reduces the need for feeding electricity into the grid and drawing power from it, thereby easing the load on the grid. 

The idea is to adjust electricity consumption to match production, such as running the washing machine when the sun is shining. When this is not possible, battery storage can help. Optimized consumption planning can lead to smaller battery storage needs, which in turn positively impacts the environmental footprint.

To perform optimized consumption planning, knowledge about individual electricity consumers is necessary, particularly their maximum and total energy requirements per time unit and their characteristic load curves. This information is typically only indirectly available through load profile curves and not explicitly for each consumer. Load profile curves represent cumulative values where individual loads overlap.

Contents and goals

This project focuses on the question of how to extract the contribution of individual electrical devices and components from existing load profiles. Mathematically, this problem is an inverse problem. The goal is to reconstruct the individual contributions of various devices from the available load profile curves. This problem has not been scientifically investigated yet, but it is of fundamental importance in the context of maximizing the self-consumption of solar power.

Methods and expected results

Key research questions include whether this problem is fundamentally solvable, what additional external knowledge is required, and which methods are most suitable. Answering these questions is essential to enable further optimization of consumption planning.

Project management

Fraunhofer Austria Research GmbH

Project or cooperation partners

None – exploratory survey

Priv.-Doz. Dr. Erich Teppan
Lakeside B13a
A-9020 Klagenfurt am Wörthersee

Teil.: +43 (676) 888 61 821
E-Mail: erich.teppan@fraunhofer.at
Web: www.fraunhofer.at