The Trombe wall is a passive system used in buildings that indirectly transfers thermal energy to the adjacent environment by radiation and convection, and directly by the thermo-circulation that arises in the air cavity delimited between a transparent and an absorbing surface. Nevertheless, the latter is painted black to increase the energy gains, but this produces a negative visual impact and promotes the overheating risk in summer. To mitigate these aspects, a hybrid Trombe wall equipped with PV panels can be employed. The PV installation results in a more pleasing wall appearance and the overheating risk reduces because part of the absorbed solar radiation is transformed into electricity. To determine the actual performance of a such system, transient simulation tools are required to consider properly the wall thermal storage features, variation of the optical properties, air thermo-circulation, and PV power production. Alternatively, regarding the traditional Trombe wall, the literature provides a simplified empirical method based on the dimensionless parameter solar load ratio (SLR) that allows for preliminary evaluations and design. In this paper, the SLR method was calibrated to determine the monthly auxiliary energy to be supplied in buildings equipped with PV-Trombe walls in heating applications. The SLR method was tuned by a multiple linear regression by data provided by TRNSYS simulation that allowed to obtain the energy performances in actual conditions of PV-Trombe walls installed on the same building but located in different localities. The comparison between the TRNSYS results and the calibrated SLR method determined average errors ranging between 0.7% and 1.4%, demonstrating the validity of the proposed methodology.

Energy performances of an innovative Temporary Housing Unit (THU), made of natural materials and developed for the Mediterranean area, were determined. Cork panels limit winter transmission losses, whereas bio-PCMs were applied to reduce cooling needs properly. Assuming a split system for air-conditioning purposes, simulations in EnergyPlus allowed for identifying the optimal configuration that minimizes the annual electric demand. Bio-PCM melting temperatures, locations inside the external walls and the PCM quantities were varied. An ideal melting temperature of 23 °C was identified, whereas a double PCM layer uniformly distributed in the external walls is recommended, mainly for the limitation of the cooling demands. Negligible differences in electric requirements have been observed between the continuous and the scheduled functioning of the split system. A PV generator installed on the available roof surface allows for covering the electric demands satisfactorily. Experimental tests carried out in a climatic chamber have allowed for determining the dynamic thermal performance of the optimized panel by considering variable external conditions. Results show how the considered PCM in summer is able to delay and attenuate the indoor air temperature peaks considerably, confirming the crucial role of bio-PCM to reduce cooling demands, in line with the simulation results.

This research investigates the optimization potential of Renewable Energy Communities (RECs) through advanced demand-side management strategies. The study simulates a real distribution network and analyzes load profile optimization in a residential REC configuration, comparing two distinct approaches: Demand-Side Engagement (DSE) and Optimized Demand-Side Management (Opt-DSM). The methodology encompasses load-shifting strategies at the appliance level, progressing from spontaneous behavior patterns to algorithmic optimization. Starting from a baseline scenario of conventional consumption patterns, the research evaluates the effectiveness of both user-driven load shifting (DSE) and automated redistribution through genetic algorithms (Opt-DSM). The analysis framework addresses three key dimensions: economic efficiency through incentive optimization, social cohesion via collaborative engagement, and environmental sustainability through the optimal utilization of locally generated energy. Results demonstrate that enhanced generation-consumption synchronization through Opt-DSM yields superior outcomes for both distribution network performance and participant economics compared to DSE. However, successful implementation requires substantial technological infrastructure investment at individual and community levels, alongside significant modifications to established consumption patterns. This research contributes to the understanding of RECs as innovative socio-technical systems and provides figures to support the analysis related to the balance between technological optimization and user engagement in maximizing shared energy potential.

With Legislative Decree 199/2021, Article 31, Italy introduced an incentive scheme to support the development of Energy Communities. This framework was subsequently implemented through the MASE Ministerial Decree 414/23, the ARERA Resolution 727/2023/R/eel and the GSE operational guidelines. The main objective is to promote the active participation of citizens in the production and consumption of renewable energy, through a premium tariff applied to energy shared by renewable generation plants with a maximum capacity of 1 MW. The incentive is available for a maximum period of 20 years, covering a total capacity of up to 5 GW, and is valid until 31st December 2027. These provisions highlight that the promotion and the dissemination of Energy Communities in Italy is a highly topical issue, and their growth will need to yield real results in the coming years. The aim of this research is to analyse the current diffusion of Energy Communities in Italy . Several available datasets provide insights into the number and size of communities, the installed capacity of renewable generation systems, the number of active configurations, and more — all broken down by region [10] [11]. RSE has started analysing the evolution of energy communities in Italy since 2021 and some of the results of this research are available through an interactive map [12]. This data will be processed to identify current trends across the country. Subsequently, we will develop forecasts regarding the future development of Energy Communities in Italy, based on historical data. Specifically, we aim to estimate: the total number of communities, the total installed renewable capacity, the total annual incentive expenditure, and the potential overall investments in the installation of power plants. This analysis will allow us to evaluate both the present and projected impact of Energy Communities in Italy. The discussion of the results will also highlight possible practices that could give new impetus to the diffusion of these configurations.