The Effect of Increasing Aggregation Levels of Electrical Consumption Data on Renewable Energy Community (REC) Analyses
Marco Raugi,
Valentina Consolo (valentina.consolo@unipi.it) and
Roberto Rugani (roberto.rugani@phd.unipi.it)
Additional contact information
Marco Raugi: Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, L.go Lucio Lazzarino 1, 56122 Pisa, Italy
Valentina Consolo: Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, L.go Lucio Lazzarino 1, 56122 Pisa, Italy
Roberto Rugani: Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, L.go Lucio Lazzarino 1, 56122 Pisa, Italy
Energies, 2024, vol. 17, issue 18, 1-25
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 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/17/18/4647/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/18/4647/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:18:p:4647-:d:1480011
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager (indexing@mdpi.com).