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Modern Optimization Technologies in Hybrid Renewable Energy Systems: A Systematic Review of Research Gaps and Prospects for Decisions

Author

Listed:
  • Vitalii Korovushkin

    (Institute of Energy Safety and Energy Management, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 03056 Kyiv, Ukraine)

  • Sergii Boichenko

    (Institute of Energy Safety and Energy Management, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 03056 Kyiv, Ukraine)

  • Artem Artyukhov

    (Faculty of Commerce, Bratislava University of Economics and Business, 852-35 Bratislava, Slovakia
    Academic and Research Institute of Business, Economics and Management, Sumy State University, 40007 Sumy, Ukraine
    Faculty of Administration and Social Sciences, Slovakia (University of Economics and Innovation) WSEI University in Lublin, 20-209 Lublin, Poland)

  • Kamila Ćwik

    (Faculty of Administration and Social Sciences, Slovakia (University of Economics and Innovation) WSEI University in Lublin, 20-209 Lublin, Poland)

  • Diana Wróblewska

    (Faculty of Administration and Social Sciences, Slovakia (University of Economics and Innovation) WSEI University in Lublin, 20-209 Lublin, Poland)

  • Grzegorz Jankowski

    (Faculty of Management, Katowice Business University, 40-659 Katowice, Poland)

Abstract

Hybrid Renewable Energy Systems are pivotal for the sustainable energy transition, yet their design and operation present complex optimization challenges due to diverse components, stochastic resources, and multifaceted objectives. This systematic review formalizes the HRES optimization problem space and identifies critical research gaps. Employing the PRISMA 2020 guidelines, it comprehensively analyzes the literature (2015–2025) from Scopus, IEEE Xplore, and Web of Science, focusing on architectures, mathematical formulations, objectives, and solution methodologies. The results reveal a decisive shift from single-objective to multi-objective optimization (MOO), increasingly incorporating environmental and emerging social criteria alongside traditional economic and technical goals. Metaheuristic algorithms (e.g., NSGA-II, MOPSO) and AI techniques dominate solution strategies, though challenges persist in scalability, uncertainty management, and real-time control. The integration of hydrogen storage, vehicle-to-grid (V2G) technology, and multi-vector energy systems expands system boundaries. Key gaps include the lack of holistic frameworks co-optimizing techno-economic, environmental, social, and resilience objectives; disconnect between long-term planning and short-term operation; computational limitations for large-scale or real-time applications; explainability of AI-based controllers; high-fidelity degradation modeling for emerging technologies; and bridging the “valley of death” between simulation and bankable deployment. Future research must prioritize interdisciplinary collaboration, standardized social/resilience metrics, scalable and trustworthy AI, and validation frameworks to unlock HRESs’ potential.

Suggested Citation

  • Vitalii Korovushkin & Sergii Boichenko & Artem Artyukhov & Kamila Ćwik & Diana Wróblewska & Grzegorz Jankowski, 2025. "Modern Optimization Technologies in Hybrid Renewable Energy Systems: A Systematic Review of Research Gaps and Prospects for Decisions," Energies, MDPI, vol. 18(17), pages 1-45, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:17:p:4727-:d:1742704
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    References listed on IDEAS

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