Open AccessIndicators and Representation Tools to Measure the Technical-Economic Feasibility of a Renewable Energy Community. The Case Study of Villar Pellice (Italy)
Author(s) -
Guglielmina Mutani,
Silvia Santantonio,
Simone Beltramino
Publication year - 2021
Publication title -
international journal of sustainable development and planning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.29
H-Index - 15
eISSN - 1743-761X
pISSN - 1743-7601
DOI - 10.18280/ijsdp.160101
Subject(s) - environmental economics , incentive , renewable energy , revenue , work (physics) , energy consumption , flexibility (engineering) , business , environmental resource management , economics , engineering , microeconomics , mechanical engineering , accounting , management , electrical engineering
Energy Communities (EC) are intended as legal entities that can ensure environmental, economic, and social benefits for energy exchanges between its members. The Italian legislation has recently introduced incentives to Renewable Energy Communities (REC). This work analyses the case study of the REC in Villar Pellice (Turin) and defines a methodology to assess its technical-economic feasibility. The hourly energy consumption and the local renewable energy production are assessed through a place-based methodology, considering different category of end users (municipalities, residential dwelling, companies), and obtaining data from available online database. The REC energy performance is assessed through the self-consumption and the self-sufficiency indexes. Besides, cost-optimal analysis evaluates its economic feasibility, considering investment costs and economic incentives. Several interventions are hypothesized to compare possible REC scenarios (e.g., photovoltaic panels and storage systems installation, energy efficiency measures for public lighting, and different configurations of end users). Results show that REC allows to aggregate stakeholders, ensuring economic advantages and environmental benefits. The methodology applied in this work can support the design phase of the RECs. Its flexibility makes it adaptable to different territorial and regulatory contexts, in evaluating the optimal REC configuration to maximize revenues from the incentive and reach the highest level of energy independence.