LAPSE:2023.8654
Published Article

LAPSE:2023.8654
Big Data Analysis for Optimising the Decision-Making Process in Sustainable Energy Action Plans: A Multi-Criteria Evaluation Approach Applied to Sicilian Regional Recovery and Resilience Plans
February 24, 2023
Abstract
Keeping the global temperature rise below 2 degrees Celsius, as foreseen by the Paris Agreement, requires a new global roadmap for the energy transition. For this reason, the European Commission decided to directly involve local municipalities in reaching these objectives through multilevel, bottom-up actions for sustainable energy. The Covenant of Mayors is a very concrete demonstration of this trend of development and adoption of sustainable energy action plans (SEAP), rethinking the way cities operate and bringing them closer to energy self-sufficiency, with measures favouring local economic development and improving citizens’ quality of life. The numerous RES/RUE actions included in SEAPs at the regional level have led both to the request for huge funding and to increased complexity for regional managers to identify the best projects to be financed. To manage the multitude of data (emissions, energy consumption, cost, etc.) present in the SEAPs at a regional level, a web-based platform called Lex-energetica was developed. In this context, this paper aims to present a participatory supportive framework for the decision-making process involved in financing the SEAPs’ actions, considering the selection of sustainable Renewable Energy Sources (RES) and Rational Use of Energy (RUE) technologies. This study proposes a methodology based on two macro-phases: the first phase consists of a ranking evaluation of categories of areas of intervention based on the analytic hierarchy process, while the second identifies nine criteria, according to the domains corresponding to the three pillars of sustainability, to compare the most appropriate RES/RUE actions.
Keeping the global temperature rise below 2 degrees Celsius, as foreseen by the Paris Agreement, requires a new global roadmap for the energy transition. For this reason, the European Commission decided to directly involve local municipalities in reaching these objectives through multilevel, bottom-up actions for sustainable energy. The Covenant of Mayors is a very concrete demonstration of this trend of development and adoption of sustainable energy action plans (SEAP), rethinking the way cities operate and bringing them closer to energy self-sufficiency, with measures favouring local economic development and improving citizens’ quality of life. The numerous RES/RUE actions included in SEAPs at the regional level have led both to the request for huge funding and to increased complexity for regional managers to identify the best projects to be financed. To manage the multitude of data (emissions, energy consumption, cost, etc.) present in the SEAPs at a regional level, a web-based platform called Lex-energetica was developed. In this context, this paper aims to present a participatory supportive framework for the decision-making process involved in financing the SEAPs’ actions, considering the selection of sustainable Renewable Energy Sources (RES) and Rational Use of Energy (RUE) technologies. This study proposes a methodology based on two macro-phases: the first phase consists of a ranking evaluation of categories of areas of intervention based on the analytic hierarchy process, while the second identifies nine criteria, according to the domains corresponding to the three pillars of sustainability, to compare the most appropriate RES/RUE actions.
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Keywords
energy planning, multi-criteria analysis, multi-level actions, Renewable and Sustainable Energy, sustainable energy action plan
Subject
Suggested Citation
Di Matteo U, Agostinelli S. Big Data Analysis for Optimising the Decision-Making Process in Sustainable Energy Action Plans: A Multi-Criteria Evaluation Approach Applied to Sicilian Regional Recovery and Resilience Plans. (2023). LAPSE:2023.8654
Author Affiliations
Journal Name
Energies
Volume
15
Issue
20
First Page
7487
Year
2022
Publication Date
2022-10-11
ISSN
1996-1073
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Original Submission
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PII: en15207487, Publication Type: Journal Article
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LAPSE:2023.8654
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https://doi.org/10.3390/en15207487
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Feb 24, 2023
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