Two-stage multi-objective distributionally robust optimization of the electricity-hydrogen coupling system under multiple markets

Hydrogen production by electricity is one of the effective means of large-scale use of renewable energy, and it is also the inevitable direction of the green and low-carbon development of the hydrogen energy industry. However, the existing studies have not deeply considered the operation of electricity-hydrogen coupling system (EHCS) in multiple markets, such as electricity, carbon, hydrogen, and auxiliary service, and have not fully explored the value of EHCS in terms of economy, environment, and other aspects, and there are still deficiencies in dealing with the uncertainty of EHCS operation. To this end, this paper innovatively proposes a two-stage multi-objective distributionally robust optimization (DRO) model for the EHCS under the coupling of electricity, carbon, hydrogen, and standby auxiliary markets. The first stage is a multi-objective optimization model based on the wind turbine (WT) and photovoltaic (PV) predicted power counting economy, energy supply stability, and users' energy use comfort, which determines the feasible domain of planned power; the second stage is a multi-objective DRO model based on the prediction deviation of WT and PV power, which smoothes out the fluctuation of power. Different scenarios are designed for numerical analyses to verify the validity of the model and the superiority of the simultaneous participation of EHCS in multi-coupled markets. The simulation results show that: 1) Simultaneous participation of the EHCS in various coupled markets such as electricity, carbon, hydrogen, and standby auxiliary service can significantly improve economic efficiency. Compared with only participating in the electricity and hydrogen markets, the simultaneous participation of EHCS in the standby auxiliary service and carbon trading markets increases the economic efficiency by 141.36 %. 2) Under multiobjective optimization, although the EHCS sacrifices some economic benefits, it can improve the stability of energy supply and the comfort of users' energy use. Compared with the pursuit of economic benefits only, under multi-objective optimization, the equivalent load variance of the EHCS is reduced by 45.77 %, and the discomfort of users' energy use is reduced by 55.34 %, which is more conducive to long-term development. 3) The DRO method has significant advantages in dealing with uncertainty, overcoming the drawbacks of the stochastic optimization (SO) method's low solving efficiency and poor robustness, and the robust optimization (RO) method's over-conservative solving results.