Reliability Assessment of Energy Hubs Using Advanced Monte Carlo Simulation Approaches: A Comprehensive Framework

Energy hubs represent a key concept in the integration of multiple energy carriers, allowing for efficient coordination of various energy sources, conversion technologies, and storage systems. However, the reliability of these complex systems remains a significant challenge due to uncertainties in renewable energy generation, load patterns, and potential component failures. This paper introduces a comprehensive framework for reliability assessment of energy hubs using advanced Monte Carlo simulation techniques. We propose a novel approach that combines traditional sequential Monte Carlo simulation with kernel density estimation (KDE) for more accurate representation of uncertainties in renewable energy resources and load demands. The framework additionally incorporates cyber-physical interdependencies by modeling both physical components and their supporting cyber infrastructure. Two detailed case studies demonstrate the effectiveness of the proposed methodology: (۱) a small-scale residential energy hub with solar photovoltaics, battery storage, and grid connection; and (۲) a large-scale multi-carrier energy hub serving a commercial district with diverse energy conversion technologies. Results indicate that conventional Gaussian-based uncertainty modeling significantly underestimates operational risks, with our KDE-based approach revealing up to ۵۶% higher expected operational costs and substantially greater variability in reliability metrics. The paper provides practical insights for energy hub designers and operators while offering a robust computational tool for reliability-oriented planning and operation of future energy systems.

کلیدواژه ها:

reliability assessment ، energy hub ، kernel density estimation ، monte carlo simulation