From self-consumption to decentralized distribution among prosumers: A model including technological, operational and spatial issues

Abstract

The power sector is undergoing a fundamental transition from centralized fossil-fuelled to distributed production systems. Usually, the decentralization of the energy distribution is treated by considering the interactions between prosumers and main grid, neglecting to include the rising chance for prosumers to directly exchange the produced energy, thus bypassing the grid. In this direction, this paper proposes a prosumer-centred dynamical model able to take the energy interactions among prosumers into account, along with the usual interactions established with the grid. The modelling approach takes inspiration from the methodological framework of agent-based models, particularly appropriate to deal with problems characterized by a significant number of interactions among the parts. Specifically, the developed model has been formulated with the main scope of investigating to what extent energy exchanges among prosumers reduce the supply from traditional plants. The electricity demand and production of each prosumer, the distance among buildings, operational and technological features (usage of the links, installed capacity of the energy production systems have been included in the analysis. Hourly-based simulations run on NetLogo performing a real urban area in Southern Italy as a case study for two scenarios evaluating the distribution from photovoltaic panels and small-scale cogeneration units. In addition, an a posteriori environmental analysis to evaluate the reduction of carbon emissions due to the distribution among prosumers has been conducted. Results reveal that short-range interactions among prosumers are preferred when planning to reduce the electricity supply from the main grid. In addition, the spatial configuration of the buildings within the area as well as the capacity of the installed energy production systems significantly affect the distribution. Finally, simulations highlight the noticeable impact of seasonality on both the distribution and the emissions’ reduction.