Risk-aware low carbon optimization of hydrogen-oriented multi-energy system with linear approximation of bi-product fuel cell

To develop a sustainable and green environment framework, this paper introduces a hydrogen-centric multi-energy system. To reach sustainable clean hydrogen energy, there is a requirement to model electrolyzer and fuel cell constraints accurately. This precise modeling of components leads to non-linear modeling; therefore, to respond to these non-linearities, a linearized multi-objective optimization framework is designed to model the economic and environmental aspects. To make a trade-off between economic and environmental objectives, an epsilon-constraint approach is considered. Furthermore, the proposed hydrogen-centric framework faces several uncertainties, including renewable energy resources' output power, electricity prices, and system hourly consumption, which lead the decision-making procedure to several challenges. To model system uncertainties, scenario-based stochastic programming is proposed. In addition, the potential risks from the worst-case scenarios of uncertainties threaten the scheduling process of the proposed framework; consequently, a conditional value-at-risk (CVaR) technique is developed to immunize the studied system against such unfavorable circumstances. Simulation results indicate that utilizing hydrogen facilities reduces operational expenses by 1.54 % under no conditions and by 1 % under full-risk conditions. The emission level rises by 2.53 % in no-risk conditions and declines by 4.06 % in full-risk conditions. The numerical findings ensure economic and environmental trade-offs in full-risk circumstances.