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 eff...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.展开更多
基金supported by the National Key R&D Program of China“Large-scale energy storage systems based on high temperature solid oxide electrolysis cells and biogas methanation technologies”(No.2021YFE0191200)。
文摘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.
