With the widespread adoption of renewable energy systems in residential buildings, particularly in the context of collective self-consumption groups (CSC) and Renewable Energy Communities (REC), understanding user behavior becomes pivotal for enhancing energy efficiency and increasing the energy share among participants for an optimal use of renewable resources. Regardless of which configuration is adopted (CSC or REC), a key aspect is how to share the generated economic benefits from the self-produced energy and identify the fairest way to distribute the incentive derived from the shared energy among users. In this context, the aim of this work is to introduce a data-driven energy benchmarking process that leverages the analysis of long-term monitoring data of residential buildings to i) characterize energy consumption patterns of users over time, ii) support the development of an optimal incentive sharing mechanism among users involved in such legal entities. The proposed approach is tested on a monitored residential building, located in Northern Italy, which includes 13 flats and is equipped with a centralized photovoltaic system.
A Data-Driven Process for Optimal Incentive Sharing in Collective Self-Consumption Groups of Residential Users / Giudice, Rocco; Piscitelli, Marco Savino; Chiosa, Roberto; Capozzoli, Alfonso. - ELETTRONICO. - 553 LNCE:(2024), pp. 19-24. (Intervento presentato al convegno 9th International Building Physics Conference, IBPC 2024 tenutosi a Toronto, Canada nel 25 - 27 July, 2024) [10.1007/978-981-97-8309-0_3].
A Data-Driven Process for Optimal Incentive Sharing in Collective Self-Consumption Groups of Residential Users
Giudice, Rocco;Piscitelli, Marco Savino;Chiosa, Roberto;Capozzoli, Alfonso
2024
Abstract
With the widespread adoption of renewable energy systems in residential buildings, particularly in the context of collective self-consumption groups (CSC) and Renewable Energy Communities (REC), understanding user behavior becomes pivotal for enhancing energy efficiency and increasing the energy share among participants for an optimal use of renewable resources. Regardless of which configuration is adopted (CSC or REC), a key aspect is how to share the generated economic benefits from the self-produced energy and identify the fairest way to distribute the incentive derived from the shared energy among users. In this context, the aim of this work is to introduce a data-driven energy benchmarking process that leverages the analysis of long-term monitoring data of residential buildings to i) characterize energy consumption patterns of users over time, ii) support the development of an optimal incentive sharing mechanism among users involved in such legal entities. The proposed approach is tested on a monitored residential building, located in Northern Italy, which includes 13 flats and is equipped with a centralized photovoltaic system.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2996955
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