To explore the consumption and diversified utilization of wind and solar resources in a high proportion renewable energy system

a two-stage robust optimization model for a multi energy coupling system with electric ammonia conversion and wind solar spatiotemporal correlation is proposed. Firstly

the operating mechanism of electric ammonia production was analyzed

and combined with direct ammonia fuel cell technology

the system characteristics of the coordinated operation of electric ammonia production and ammonia fuel cells were explored. To comprehensively consider the correlation and uncertainty of wind and solar power output and select the closest extreme scenario

this paper uses the minimum volume enclosing ellipsoid algorithm to construct a high-dimensional ellipsoid set and establishes the probability distribution confidence set of wind and solar power output scenarios through 1-norm and ∞-norm

effectively integrating the distribution information of wind and solar power output uncertainty. In response to the problem of long computation time caused by binary variables in robust optimization models

this paper proposes an improved column and constraint generation (C & CG) algorithm

which uses the three block alternating direction multiplier method and approximate convexification method to handle the main and sub problems respectively

and iteratively solves the main and sub problems through inexact C & CG algorithm

ensuring computational efficiency while quickly approaching the optimal solution. The results show that the extreme scenarios obtained by the proposed model can accurately capture the spatiotemporal correlation and uncertainty of wind and solar power output. The electric ammonia conversion system effectively promotes the rational consumption of renewable energy

while ensuring the safe and stable operation of the system

significantly improving the scheduling economy and solving efficiency.