LAUSR

As an essential part of the future national energy system, hydrogen energy has the advantages of clean, long-time scale energy storage and good complementary characteristics to electrical power, making it an important player in the low-carbon transformation of energies. However, the long timescale storage characteristics and tradability of hydrogen energy are rarely considered in existing capacity allocation optimization methods for hydrogen integrated energy systems(HIES). Meanwhile, the impact of the physical characteristics of the hydrogen storage equipment is rarely considered in the construction of HIES. Therefore, this paper proposes a new capacity allocation method for HIES in industrial park considering hydrogen trading and long-term hydrogen storage. The proposed capacity allocation optimization method is a bilevel mixed-integer linear programming model, which is solved by the reconfiguration decomposition algorithm. The nonlinear constraint problem due to the physical characteristics of the hydrogen storage device is solved by the Big-M method and the binary method. The proposed method can effectively improve the economy of HIES and reduce the cost of hydrogen production. Meanwhile, the reconstruction decomposition algorithm can effectively solve the bilevel mixed integer programing model. Case studies demonstrate that the proposed method can reduce hydrogen production economics by 28%. Considering hydrogen trading, the total investment and operating cost of HIES is reduced by 25%, while long-term hydrogen storage can reduce the cost of hydrogen production for HIES and reduce the impact of hydrogen trading fluctuations.