Energy Communities in Piedmont Region (IT). The case study in Pinerolo territory

Abstract

In order to reach the climate and energy targets, every country and territory should promote a sustainable energy plan. The Italian National Energy Strategy 2017, in accordance with the long-term scenario of EU Energy Roadmap 2050, defined the actions to reduce GHG emissions and, in this context, the energy communities can play a strategic role. The Council of European Energy Regulators defines energy a cooperative / partnership / non-profit organization of final customers, which can involve different stakeholders, such as municipalities, local societies, public and private companies. The stakeholders work together in energy communities for: the production and distribution of energy generated from renewable sources, the optimization of energy demand and supply and the reduction of energy consumptions, GHG emissions and costs. The communities’ objectives are to boost energy exchanges, to encourage the establishment of inter-company smart grids and to increase energy efficiency in participating companies. A choice for energy independence that guarantees the energy security with a low environment impact and affordable energy costs. Where energy communities are consolidated, there is a 20–30% savings on energy prices, and a self-production level of around 80% on energy needs.The challenge of this work is to present a future local energy community in Italy: a case study in the Pinerolo area of the Piedmont Region. In particular, this work presents a procedure useful to monitor and manage the energy consumption and production of different stakeholders in a territory. The energy data were collected using an online questionnaire sent to municipalities and companies. The first test of the procedure in the Pinerolo area highlighted the problems related to the various stakeholders in the energy community with different formats and quantities of data, and more or less complicated energy management systems that imply a diversified availability of data and response times.