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ZENODO
Report . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2023
License: CC BY
Data sources: Datacite
ZENODO
Report . 2023
License: CC BY
Data sources: Datacite
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Planning Renewable Energy Communities (REC): the perspective of Municipalities and Small and Medium Enterprises (SME) (PLANREC)

Authors: Gregori, Francesco;

Planning Renewable Energy Communities (REC): the perspective of Municipalities and Small and Medium Enterprises (SME) (PLANREC)

Abstract

This project represents the follow-up of the Project M-ECHaII #107 (Renewable Energy Community "Energy City Hall") coordinated in 2022 by the City of Magliano Alpi (Italy), that was as well part of the ERIGrid 2.0 Lab Access programme. The goal of the project was the implementation of a software platform for REC - Renewable Energy Communities, aimed at estimating and forecasting techno-economic metrics and having the form of a web platform that can be used by research centres and companies in the sector to support the formulation of REC business plans, estimating the financial incentives of the REC in a rapidly evolving regulatory framework. The software is based on previous research, jointly accomplished by EU JRC and City of Magliano Alpi during a previous ERIGRID 2.0 Laboratory Access activity, whose result has been the implementation of a forecast model of the aggregate demand/generation profiles of the RECS and their self-consumed energy. The forecast model for the energy profiles of the communities can support the planning and expansion of the RECS and provide robust quantitative information for the development of business plans. This point is particularly relevant in light of the latest regulatory developments in the Italian framework, with an extension of the aggregation perimeter prescribed for the RECs. During the above mentioned research several impacts have been evaluated through the model. They comprise: Seasonal trends Weather Conditions Number and type of prosumers Number and type of consumers Geographical extension The model, whose creation encompassed input data processing, random sampling and metric evaluation, correlations determination with possible impact factors can be used in one of two ways: Evaluation of a specific scenario (e.g. REC with types and number of prosumers/consumers already well defined) Sensitivity studies: simulations iterated over the space of the parameters of interest evaluating derivatives of input parameters on output The prototype model was developed using the MATLAB language. The aim of the project was to create a web application that guarantees: Engineering and porting of the prototype model to improve its industrial solidity increasing its TRL from level 6 to 9 Open-Source code availability Multiuser experience over a web UI Scenario configurability Input data treatment pipeline (dataflow) Data segregation (security) between different entities Data quality assurance guided procedures Simulation capabilities over real cases and studies This web application also includes a forecasting tool that introduces space-time correlation tools such as weather data and geolocation, integrated with historical data.

Keywords

User Project, PLANREC, Report, ERIGrid 2.0, H2020, European Union (EU), Lab Access, GA 870620

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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