Scenario-based MCDM framework for performance assessment and provincial prioritization of solar domestic hot water systems
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY, cilt.28, sa.10, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 28 Sayı: 10
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s10098-026-03621-6
- Dergi Adı: CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Compendex, Environment Index, Greenfile, INSPEC, Public Affairs Index, Natural Science Collection (ProQuest), Social Science Premium Collection (ProQuest), Materials Science & Engineering Collection (ProQuest), Pharma Collection (ProQuest), Technology Collection (ProQuest)
- Karadeniz Teknik Üniversitesi Adresli: Evet
Özet
Solar domestic hot water (DHW) systems can reduce fossil-fuel consumption and carbon emissions in residential heating; however, their regional performance varies considerably with climatic and technical conditions. This study develops a scenario-based multi-criteria decision-making framework to prioritize the techno-environmental performance of solar DHW systems across 45 provinces in T & uuml;rkiye. The analysis uses simulation-derived indicators for a standardized solar DHW configuration and evaluates five benefit criteria related to emission reduction, solar contribution, system efficiency, demand coverage, and solar-resource availability. Criterion weights are examined through one objective weighting scenario and five policy-oriented scenarios representing alternative planning priorities. Provincial rankings are generated using two compromise-based MCDM methods, and robustness is assessed through inter-method ranking comparison, winter-based seasonal analysis, parameter-sensitivity analysis, and criterion-ablation tests. The results indicate that provinces in Eastern and Southeastern T & uuml;rkiye generally provide the highest solar DHW potential, whereas several Black Sea provinces tend to rank lower due to relatively lower solar availability. The high Spearman correlations between the rankings generated by the two methods suggest that the identification of priority provinces is not strongly dependent on a single ranking method under most scenarios. The proposed framework offers a transparent decision-support approach for regionally differentiated renewable-heating planning.