Effects of Synchronism between Photovoltaic Generation and Energy Demand in a Residential Energy Community

According to many future scenarios, a high penetration of renewable electricity in the electricity mix will be needed in order to limit global warming. To accomplish this, in most countries the share of renewable electricity will need to drastically increase from its present values. Energy communities may be one of the enablers of this growth, due to their potential to support the development of distributed infrastructures and to increase grid flexibility. This work analyses the impacts that yearly energy demand, synchronism between photovoltaic (PV) energy generation and energy demand, PV inclination and orientation, and the presence of energy storage systems have on a residential energy community’s key performance indicators (KPIs). These impacts are assessed through simulations performed with an open-source Python-based program adapted from the literature. In the first part of this thesis, a literature review on energy communities is conducted, with a particular focus on their definitions, their possible activities, their typologies, their current state in Italy, and on their modeling approaches. The method utilized in this work to represent the yearly demand and synchronism (with PV production) of users’ demand profiles is the so-called “PCC-demand plane”, which utilizes the Pearson Correlation Coefficient (PCC) to represent the synchronism between energy demand and PV generation. The potential of the PCC-demand plane is first demonstrated by showing that the presence of demand profiles in different areas of the plane has a significant effect on the KPIs of a simulated energy community. Secondly, the impacts of the inclination and orientation of PV systems are analyzed. The effects of different PV inclinations are found to be mostly limited to changes in the yearly PV-produced energy, with very limited effects on PCCs. Different PV orientations can have a strong impact on both PV energy production and PCCs; however, the eventual improvements of synchronism produced by orientations different from South appear to be generally not enough to compensate for the reduced energy production. Thirdly, a tool to create custom distributions of demand profiles, based on normal distributions for the values of yearly demand and PCC, is developed. Performing simulations with different custom distributions, it is found that the means of PCC and yearly demand significantly affect the KPIs (whose trends are analyzed and discussed) of the simulated energy communities, while the standard deviation of demand does not. Moreover, two distributions of demand profiles derived from different sources but with similar averages and standard deviations of both PCC and yearly demand are used in simulations. The latter produce similar KPIs, suggesting that demand profiles with similar distributions of PCC and yearly demand may cause similar performances of the energy communities. Finally, an analysis is conducted on the effects of the presence of batteries in an energy community, analyzing the variations of KPIs and PCC, comparing several distributed batteries installed in some households and a single centralized battery usable by all of the community’s households. Batteries are found to be an effective way to increase the PCC of an energy community and consequently its KPIs; in particular, a centralized battery appears to be the most effective way of doing this.