Assessment of the Impact of Solar Power Integration and AI Technologies on Sustainable Local Development: A Case Study from Serbia

Aco Benović, Miroslav Miškić, Vladan Pantović (), Slađana Vujičić, Dejan Vidojević, Mladen Opačić and Filip Jovanović
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Aco Benović: Faculty of Technical Science, University of Novi Sad, 6 Dositeja Obradovica Sq., 21102 Novi Sad, Serbia
Miroslav Miškić: Faculty of Technical Science, University of Novi Sad, 6 Dositeja Obradovica Sq., 21102 Novi Sad, Serbia
Vladan Pantović: Faculty of Project and Innovation Management, Educons University, 11000 Belgrade, Serbia
Slađana Vujičić: Faculty of Business Economics and Entrepreneurship, 11108 Belgrade, Serbia
Dejan Vidojević: Academy of Professional Studies Sumadija, 34000 Kragujevac, Serbia
Mladen Opačić: Faculty of Management, Metropolitan University, 11000 Belgrade, Serbia
Filip Jovanović: Faculty of Project and Innovation Management, Educons University, 11000 Belgrade, Serbia

Sustainability, 2025, vol. 17, issue 15, 1-23

Abstract: As the global energy transition accelerates, the integration of solar power and artificial intelligence (AI) technologies offers new pathways for sustainable local development. This study examines four Serbian municipalities—Šabac, Sombor, Pirot, and Čačak—to assess how AI-enabled solar power systems can enhance energy resilience, reduce emissions, and support community-level sustainability goals. Using a mixed-method approach combining spatial analysis, predictive modeling, and stakeholder interviews, this research study evaluates the performance and institutional readiness of local governments in terms of implementing intelligent solar infrastructure. Key AI applications included solar potential mapping, demand-side management, and predictive maintenance of photovoltaic (PV) systems. Quantitative results show an improvement >60% in forecasting accuracy, a 64% reduction in system downtime, and a 9.7% increase in energy cost savings. These technical gains were accompanied by positive trends in SDG-aligned indicators, such as improved electricity access and local job creation in the green economy. Despite challenges related to data infrastructure, regulatory gaps, and limited AI literacy, this study finds that institutional coordination and leadership commitment are decisive for successful implementation. The proposed AI–Solar Integration for Local Sustainability (AISILS) framework offers a replicable model for emerging economies. Policy recommendations include investing in foundational digital infrastructure, promoting low-code AI platforms, and aligning AI–solar projects with SDG targets to attract EU and national funding. This study contributes new empirical evidence on the digital–renewable energy nexus in Southeast Europe and underscores the strategic role of AI in accelerating inclusive, data-driven energy transitions at the municipal level.

Keywords: AI technology; IT project management; energy efficiency; sustainability; local development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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