Simulation or estimation?—Two approaches to calculate financial benefits of energy communities

Abstract

To date, studies examining the profitability of energy communities (ECs) with a specific focus on the distribution of energy and costs between participants have mostly proposed complex optimisation algorithms built upon household flexibility potential. In practice, however, the majority of households are not equipped with load-scheduling equipment. Therefore, this work introduces, a simulation model that aims to better reflect reality in order to assess electricity flows and the according costs in a renewable energy community (REC). To this end, two different distribution keys – static and dynamic allocation – are applied, and their implications are quantified. However, aside from realistic simulation models, simpler tools for assessing the economic viability of RECs are also required. Such tools may support the rapid diffusion of energy community concepts since potential participants are enabled to quantify financial benefits. For this purpose, an estimation model that requires no fine-grained load/generation profiles or significant computing power is presented. Since such a tool is only useful if the estimation still generates realistic outputs, its accuracy is evaluated by comparing the results it yields to those of the simulation. The calculations are conducted for a fictitious REC of ten single-family dwellings, of which five are equipped with a rooftop photovoltaic (PV) system. The results show that dynamic allocation increases the efficiency of electricity use compared to static allocation, thus benefitting all participants since the local electricity consumption is increased by 10% on average. Comparing the results of the simulation and the estimation allows to conclude that a realistic assessment of an EC’s profitability can indeed be provided with proper assumptions.