Designing integrated and resilient multi-energy systems via multi-objective optimization and scenario analysis

Marco Tangi and Alessandro Amaranto

Applied Energy, 2025, vol. 382, issue C, No S030626192500011X

Abstract: Decarbonizing local energy systems is imperative to achieve climate neutrality by 2050 and limit global temperature rise to 1.5 °C, aligning with the European Green Deal. Effective planning relies on accurate energy modeling tools, with a shift towards multi-energy systems which integrate diverse energy vectors and technologies for enhanced flexibility and renewable energy hosting capacity. Traditional single-metric cost-focused approaches in multi-energy systems planning are evolving towards multi-objective optimization strategies, balancing costs with sustainability objectives like global warming potential, environmental impacts, and reliability. The complexity of renewable energy sources, market volatility, and climate change necessitates robust solutions resilient to multiple uncertainty sources. This study introduces a decision analytic framework for optimal planning of sustainable, resilient multi-energy systems, integrating the single-objective CALLIOPE simulation-optimization model with multi-objective evolutionary algorithms. Multiple algorithms are tested, and the best-performing algorithm is used to extract optimal configurations under alternating scenarios of renewable energy generation potential and energy prices.

Keywords: Multi-objective optimization; Multi-energy systems; Energy system configuration; Robust planning (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.125281

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