The integrated energy system of zero-carbon energy coupled with energy storage

such as hydrogen energy

is the mainstream of energy systems nowadays

and the formulation of its energy management strategy and the optimal allocation of its capacity have a large impact on the economy and flexibility of the integrated system. To this end

a method for optimal capacity allocation of integrated energy systems under multi-energy demand scenarios is proposed. Firstly

a typical scenario of source-load is obtained through Latin hypercubic sampling and Euclidean distance reduction to achieve a reasonable portrayal of the source-load prediction error. Secondly

the energy management strategy with the coordination of each device is formulated. Based on the typical scenarios and energy management strategies

a capacity allocation model is established with the objective function of minimizing the daily comprehensive cost of the system

and the optimal capacity allocation scheme is obtained through the Bottle Sea Sheath swarm algorithm based on adaptive inertia weights and economic analysis. The simulation results show that the proposed scheme can reduce the daily comprehensive cost by 5.82% and 10.9%

respectively

compared with the schemes lacking the participation of storage battery in power conditioning and the use of hydrogen waste heat

and at the same time

it ensures that the capacity of each storage device is equal at the beginning and end of an operation cycle

so that the system is more effective in stable operation in the long term.