RT Journal Article
T1 Advancing Sustainability Assessment of Renewable Energy: A Study on Indicator-to-Framework Methods and Associated Rule Mining
A1 Faraji Abdolmaleki, Shoeib
A1 Bello Bugallo, Pastora María
K1 data-driven
K1 Indicators
K1 Renewable energy
K1 Sustainable development
K1 Enerxías renovables
AB Divergent sustainable development perspectives, mathematical model limitations, and varying scenarios contribute to uncertainty in assessing renewable energy sustainability. To tackle these challenges, this study conducts a comprehensive literature review, employs an analogy, and utilizes knowledge discovery techniques with an indicator-to-framework approach. Qualitative classification and rule mining elucidate the interrelationships among dimensions, indicators, and scopes, enhancing assessment coherence. The study identifies 227 indicators across five dimensions and nine scopes, highlighting key rules through Apriori algorithm. Strong rules, meeting a support threshold of 0.22, confidence of 0.7, and Lift of 2.512, underscore the significance of environmental, economic, social, and technological dimensions. Environmental indicators like CO2 emissions, NOX emissions, and SO2 emissions feature prominently. The harmonization of dimensions, indicators, and scopes streamlines research and mitigates ambiguities. Appendices augment rules with frequent indicators, enriching insights. This data-drivenmethodology provides a practical solution to the complexities of selecting appropriate indicators for such assessments.
PB Wiley
SN 0968-0802
YR 2025
FD 2025-01-18
LK https://hdl.handle.net/10347/39985
UL https://hdl.handle.net/10347/39985
LA eng
NO Faraji Abdolmaleki, S., Bello Bugallo, P. M. (2025). Advancing Sustainability Assessment of Renewable Energy: A Study on Indicator-to-Framework Methods and Associated Rule Mining. "Sustainable Develpoment"
DS Minerva
RD 26 abr 2026