An Open-Source IT Tool for Energy Forecast of Renewable Energy Communities

Abstract

Renewable Energy Communities (RECs) are envisaged as a key enabler for a citizen-driven energy transition. The pooling of renewable energy resources at a local level and the active involvement of public entities, Small and Medium-sized Enterprises (SMEs) and private customers can lower the energy costs of end-consumers and increase public acceptance of renewable projects. At the same time, the RECs can support power system operation by leveraging their flexibility and providing ancillary services to the grid. While a significant amount of research has focused on optimizing the operation of existing RECs to maximize their performance and economic benefits, fewer studies have analysed the forecast of future REC performance to support the planning of new communities. The present paper tackles this research gap by developing a novel tool for the forecast of techno-economic performance of REC. The tool relies on two different techniques (based on statistical random sampling and neural networks, respectively) to predict the energy behaviour of RECs on the basis of their fundamental planning parameters (type/number of members, installed generation, geographical location). In order to reach a larger audience of practitioners, a web-based open-source implementation of the tool has been developed and made available to the general public, designing a graphical interface that facilitates the use of the tool by non-technical experts.