MOPREC

MOPREC Project Overview and Objectives for Optimizing Renewable Energy Communities

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MOPREC aims to perfect a monitoring network of Renewable Energy Communities (RECs), with the aim of dynamically optimizing the underlying spatio-temporal configurations, to maximize their performance in terms of social, environmental and economic benefits. The network will be able to detect and analyze the changes that impact the effectiveness of planned and active RECs, including:

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- urban regeneration interventions that modify energy consumption;

- the departure or entry of members, with a consequent redefinition of the energy balance;

- the variation of the incentives available at national,regional and local level;

- the amendments to the legislation relating to areas suitable for RES plants.

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Advanced Monitoring Network for Renewable Energy Communities: Dynamic Optimization and Innovation

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The network represents an innovative technological solution, currently not on the market, designed to enhance the potential of RECs in contributing to European decarbonisation objectives and the fight against energy poverty. At the base of the monitoring network there will be a WEB platform that will integrate different technologies:
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- GenAI technology to create a REC digital twin;

- embedded GeoAI technology, fed with data from satellite, in situ and shared by citizens and stakeholders.

This will be possible thanks to UNISA's partnership with Latitudo 40 and Nexsoft. The network improvement will allow the updating, analysis and consultation of advanced knowledge frameworks, complementary to those already available at national level,relating to existing RECs. These may concern, by way of example:

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- the spatial perimeter and operational characteristics of RES plants in operation in RECs;

- the potential for expansion or optimization of existing plants, considering urban and territorial constraints;

- the potential forincreasing self-consumption and energy sharing in active RECs;

- energy-intensive buildings integrated or integrable in RECs;

- urban areas with socio-economic vulnerabilities, already served or serviceable by RECs;

- energy poverty situations that can be addressed through the strengthening of RECs;

- the building and urban planning incentives that can be activated in the territories in which the RECs operate;

- projects implemented or in progress, with evidence of the objectives achieved orin the process of being
implemented;

- critical issues in the operational management of RECs, including barriers faced by citizens or aspiring members;

- simulations that integrate meteorological, demographic,regulatory and economic variables to predict the RECs evolution.

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Data Sources and Knowledge Framework for Renewable Energy Communities Analysis

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The data necessary to build this knowledge will be taken from:

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- official datasets updated by public bodies;

- urban planning processes;

- satellite imagery.

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Project Workflow and Work Packages: Methodology, AI Integration and Stakeholder Engagement

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The project is divided into Work Packages (WPs), each with specific activities forthe implementation, testing and validation of the proposed methodology.

WP1 involves the design of the optimal REC configurations monitoring system, through an integrated model (1.1) based on heterogeneous data and advanced algorithms of spatial analysis and Machine Learning (1.2).

Evolutionary indicators and information layers will be built to dynamically monitor RECs and associated benefits, also thanks to high-resolution satellite images.

WP2 develops generative Artificial Intelligence methodologies for the creation of a REC Digital Twin (2.1) and the enterprise platform (2.2).

‍WP3 applies remote sensing models to analyze the photovoltaic potential and simulate new installations (3.1), integrating them into the platform (3.2).

The data will be enriched by citizens' contributions through participatory initiatives, coordinated in WP4, which includes activities of involvement (4.1), scientific communication (4.2) and dissemination, also at the international level (4.3).

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