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Deep Learning Surrogate model to Explain Decision Variable Synergies in Energy System Modelling
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DOI：10.1016/j.segy.2026.100246.png)
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Abstract
En 中文
• Method to study synergies between decision variables and objective functions results • Expert-based analysis: Power-to-X needs >50% renewable share for net CO2 benefit • Deep learning surrogate of EnergyPLAN is robust method to reproduce EPLANopt results • SHAP and Sobol XAI methods identify photovoltaics and synthetic gas as pivotal variables • Third-order analysis reveals photovoltaics, Power-to-X and batteries key synergies
Keywords:
Energy Systems
Energy Modeling
Energy Scenarios
Deep learning
Surrogate modelling
Sensitivity analysis
Explainable AI
Technology synergies
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