The increasing electrification of final energy uses, together with the diffusion of distributed renewable generation, storage systems and prosumers, is profoundly changing the way electricity is produced, consumed and exchanged in distribution networks. It is estimated that this process will lead to a significant increase in future network management costs. For this reason, network tariffs must be effective and well-structured to recover the necessary costs, ensure greater cost-reflectiveness, and provide economic signals capable of steering user behaviour. This relationship between tariff signals, flexibility and network usage becomes even more significant in the context of renewable energy communities. In the Italian model, shared energy is calculated through a virtual mechanism based on the simultaneity between injections and withdrawals on the public grid. As a result, the community's behaviour may have implications not only for the incentive recovered, but also for the impact on the network. This thesis analyses, through a case study of an Italian REC, the effect of different combinations of energy and network tariffs on community performance and on the response to price signals. Using a MILP optimisation model, scenarios are simulated with volumetric, time-of-use and hourly electricity prices, combined with volumetric network tariffs featuring different components and time-of-use structures. The behaviour of each scenario is assessed through energy, economic and network interaction indicators, including shared energy. The results show that the network tariff influences the response of the community and flexible users to a greater extent than electricity price alone, affecting battery operation, incentive generation and network interaction. The thesis highlights a trade-off between user economic convenience, incentive creation, efficient network use and infrastructure cost recovery.
L’aumento dell’elettrificazione dei consumi finali, la crescita della generazione distribuita da fonti rinnovabili, dei sistemi di accumulo e dei prosumer stanno modificando profondamente il modo in cui l’energia elettrica viene prodotta, consumata e scambiata nelle reti di distribuzione. Questo processo è destinato ad aumentare la complessità della gestione della rete e i relativi costi futuri. Per questo motivo, le tariffe di rete devono essere efficaci e ben strutturate, in modo da garantire il recupero dei costi infrastrutturali, migliorare la riflettività dei costi e fornire segnali economici in grado di orientare il comportamento degli utenti. Il rapporto tra segnali tariffari, flessibilità e utilizzo della rete assume particolare rilevanza nel contesto delle Comunità Energetiche Rinnovabili. Nel modello italiano, l’energia condivisa è calcolata tramite un meccanismo virtuale basato sulla simultaneità tra le immissioni e i prelievi dalla rete pubblica. Di conseguenza, il comportamento della comunità può influenzare non solo l’incentivo generato, ma anche l’interazione con la rete di distribuzione. Questa tesi analizza, attraverso il caso studio di una CER italiana, l’effetto di diverse combinazioni di prezzi dell’energia elettrica e tariffe di rete sulle prestazioni della comunità e sulla risposta ai segnali economici. Utilizzando un modello di ottimizzazione MILP, vengono simulati scenari con prezzi dell’energia flat, time-of-use e orari, combinati con tariffe di rete flat, business-as-usual e time-of-use. Le prestazioni di ciascun scenario sono valutate attraverso indicatori energetici, economici e di interazione con la rete, includendo anche l’energia condivisa. I risultati mostrano che la tariffa di rete influenza la risposta della comunità e degli utenti flessibili in misura maggiore rispetto al solo prezzo dell’energia, incidendo sull’utilizzo delle batterie, sulla creazione dell’incentivo e sull’interazione con la rete. La tesi evidenzia quindi un trade-off tra convenienza economica per gli utenti, creazione di incentivo, uso efficiente della rete e recupero dei costi infrastrutturali.
Economic signal interactions in Renewable Energy Communities: the role of electricity prices, network tariffs and sharing incentives
BIAZZI, MARTA
2025/2026
Abstract
The increasing electrification of final energy uses, together with the diffusion of distributed renewable generation, storage systems and prosumers, is profoundly changing the way electricity is produced, consumed and exchanged in distribution networks. It is estimated that this process will lead to a significant increase in future network management costs. For this reason, network tariffs must be effective and well-structured to recover the necessary costs, ensure greater cost-reflectiveness, and provide economic signals capable of steering user behaviour. This relationship between tariff signals, flexibility and network usage becomes even more significant in the context of renewable energy communities. In the Italian model, shared energy is calculated through a virtual mechanism based on the simultaneity between injections and withdrawals on the public grid. As a result, the community's behaviour may have implications not only for the incentive recovered, but also for the impact on the network. This thesis analyses, through a case study of an Italian REC, the effect of different combinations of energy and network tariffs on community performance and on the response to price signals. Using a MILP optimisation model, scenarios are simulated with volumetric, time-of-use and hourly electricity prices, combined with volumetric network tariffs featuring different components and time-of-use structures. The behaviour of each scenario is assessed through energy, economic and network interaction indicators, including shared energy. The results show that the network tariff influences the response of the community and flexible users to a greater extent than electricity price alone, affecting battery operation, incentive generation and network interaction. The thesis highlights a trade-off between user economic convenience, incentive creation, efficient network use and infrastructure cost recovery.| File | Dimensione | Formato | |
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2026_07_Biazzi_Thesis.pdf
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2026_07_Biazzi_Executive Summary .pdf
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https://hdl.handle.net/10589/261327