Optimal Stochastic Scheduling Strategy of Multi-vector Energy Complex Integrated with Full-blown Power-to-biomethane Model

We propose an optimal stochastic scheduling strategy for a multi-vector energy complex（MEC）, considering a fullblown model of the power-to-biomethane（Pt M） process. Unlike conventional optimization that uses a simple efficiency coefficient to coarsely model energy conversion between electricity and biomethane, a detailed Pt M model is introduced to emphasize the reactor kinetics and chemical equilibria of methanation. This model crystallizes the interactions between the Pt M process and MEC flexibility, allowing to adjust the operating condition of the methanation reactor for optimal MEC operation in stochastic scenarios. Temperature optimization and flowsheet design of the Pt M process increase the average selectivity of methane（i.e., ratio between net biomethane production and hydrogen consumption） up to 83.7% in the proposed synthesis flowsheet. Simulation results can provide information and predictions to operators about the optimal operating conditions of a Pt M unit while improving the MEC flexibility.