The Effect of Increasing Aggregation Levels of Electrical Consumption Data on Renewable Energy Community (REC) Analyses

Abstract

The growing number of renewable energy communities (RECs) exemplifies the potential of citizen-driven actions towards a more sustainable future. However, obtaining hourly measured consumption data from REC members remains challenging, hindering accurate feasibility studies for the development of communities. This study examines the impact of estimating hourly consumption from aggregated data on REC analysis results. A case study with real consumption data from diverse users, representative of a typical community in Tuscany, Italy, was analysed to investigate various influencing factors. Multiple scenarios were simulated: two open-source tools estimated energy production from the community’s PV plants, and two REC configurations were considered—one with consumers and prosumers and another with consumers and a producer (with the same total installed power). Additionally, three locations were evaluated to consider the importance of geographical positioning. The study revealed that the impact of consumption data aggregation is more significant in scenarios with low energy sharing, such as the scenario where prosumers were replaced with a producer. Geographical positioning showed no major discrepancies in energy and economic outcomes, implying that using estimated hourly consumption data from aggregated data has a relevant impact regardless of location. Furthermore, different weather files did not affect the impact of aggregated consumption data.

Keywords

• renewable energy communities
• electricity consumption analysis
• load profile analysis
• technical–economic analysis