Energy System Simulation Models Adapted to the Development of a High Proportion of Renewable Energy - A Systematic Review

The development of future integrated energy systems (IES) targeting high-proportion renewable energy integration necessitates selecting appropriate energy models aligned with research objectives, as simulations are critical for evaluating renewable energy deployment pathways. Current energy system models, categorized into bottom-up, top-down, computable general equilibrium (CGE), and optimization frameworks, address distinct aspects: bottom-up models identify technology-specific solutions, top-down tools forecast macroeconomic trends, CGE models analyze multi-market dynamics, and optimization models determine cost-effective technology portfolios. While studies have explored individual tools and limited comparative analyses, gaps persist in systematic evaluations of the 37 prevalent models. Model selection varies significantly based on scope, sectoral focus, and renewable integration strategies. For instance, EnergyPRO assesses power plant feasibility, WASP calculates renewable capacity requirements, and PERSEUS/STREAM model electric vehicle adoption, whereas MiniCAM and UniSyD3.0 incorporate hydrogen vehicles for enhanced flexibility. Only 10 tools, including EnergyPLAN and MARKAL/TIMES, holistically integrate power, heating, and transportation sectors. Challenges remain in addressing renewable system complexity, parameter uncertainty, and policy relevance. To overcome these, this study proposes the EnergyPLAN model, leveraging hourly-scale data and multisector synergies, combined with genetic algorithm-driven optimization to mitigate uncertainties and deliver robust, policy-relevant solutions for high-renewable IES planning.