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<p>The accelerating need to decarbonize energy systems in climate-sensitive and remote regions demands integrated design approaches that balance economic viability, environmental performance, technical reliability, and socio-economic co-benefits. This study develops and applies a multi-objective optimization framework for a hybrid renewable energy system (HRES) combining photovoltaic, wind, battery energy storage, and hydrogen subsystems in an off-grid island context. The optimization simultaneously minimizes Levelized Cost of Energy (LCOE), life-cycle greenhouse gas (LC-GHG) emissions, and Loss of Power Supply Probability (LPSP), while maximizing Renewable Energy Fraction (REF) and climate resilience under projected resource variability. Advanced metaheuristics, including Gravitational Search Algorithm, enhanced Particle Swarm Optimization, and deep reinforcement learning, are employed for high-dimensional Pareto optimization. The best-performing configuration (Scenario S4) achieves a resilience-constrained mean LCOE of 0.213 USD kWh⁻<sup>1</sup> (95% CI [0.201–0.225]), an REF of 78.6% (95% CI [76.8–80.3%]), lifecycle GHG reductions exceeding 80% (95% CI [82.5–86.8%]), and an LPSP of ≈ 0.8%, alongside indicative improvements in local employment and reduced energy poverty. Life-cycle assessment reveals that targeted interventions in upstream manufacturing and end-of-life management can further enhance environmental gains. Comparative analysis with recent Q1 literature confirms that coupling techno-economic, LCA, and resilience objectives consistently yields balanced performance superior to conventional single-criteria designs. The findings highlight critical policy levers—such as storage-focused investment incentives, resilience metrics in procurement, and LCA-based regulatory frameworks—for scaling sustainable HRES adoption. The proposed approach offers a transferable blueprint for decision-makers aiming to deliver low-carbon, reliable, and socially inclusive energy solutions in resource-constrained regions.</p>

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Policy-driven design of hybrid renewable energy systems under climate change uncertainty: multi-criteria decision-making and life cycle sustainability assessment

  • 期刊论文

  • 发表日期：

    2026年6月22日

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  • Z. Hamidzadeh,
  • A. Ahmadi

摘要

The accelerating need to decarbonize energy systems in climate-sensitive and remote regions demands integrated design approaches that balance economic viability, environmental performance, technical reliability, and socio-economic co-benefits. This study develops and applies a multi-objective optimization framework for a hybrid renewable energy system (HRES) combining photovoltaic, wind, battery energy storage, and hydrogen subsystems in an off-grid island context. The optimization simultaneously minimizes Levelized Cost of Energy (LCOE), life-cycle greenhouse gas (LC-GHG) emissions, and Loss of Power Supply Probability (LPSP), while maximizing Renewable Energy Fraction (REF) and climate resilience under projected resource variability. Advanced metaheuristics, including Gravitational Search Algorithm, enhanced Particle Swarm Optimization, and deep reinforcement learning, are employed for high-dimensional Pareto optimization. The best-performing configuration (Scenario S4) achieves a resilience-constrained mean LCOE of 0.213 USD kWh⁻1 (95% CI [0.201–0.225]), an REF of 78.6% (95% CI [76.8–80.3%]), lifecycle GHG reductions exceeding 80% (95% CI [82.5–86.8%]), and an LPSP of ≈ 0.8%, alongside indicative improvements in local employment and reduced energy poverty. Life-cycle assessment reveals that targeted interventions in upstream manufacturing and end-of-life management can further enhance environmental gains. Comparative analysis with recent Q1 literature confirms that coupling techno-economic, LCA, and resilience objectives consistently yields balanced performance superior to conventional single-criteria designs. The findings highlight critical policy levers—such as storage-focused investment incentives, resilience metrics in procurement, and LCA-based regulatory frameworks—for scaling sustainable HRES adoption. The proposed approach offers a transferable blueprint for decision-makers aiming to deliver low-carbon, reliable, and socially inclusive energy solutions in resource-constrained regions.