Optimal scheduling of hydrogen blended integrated electricity–gas system considering gas linepack via a sequential second-order cone programming methodology

Abstract

In the context of increasing global environmental pollution and constant increase of carbon emission, hydrogen production from surplus renewable energy and hydrogen transportation using existing natural gas pipelines are effective means to mitigate renewable energy fluctuation, build a decarbonized gas network, and achieve the goal of “carbon peak and carbon neutral” in China. Existing gas network modeling with hydrogen blended is divided into steady-state and dynamic. The steady-state modeling oversimplifies the physical process, while the dynamic modeling is computationally intensive. Thus, a quasi-steady-state modeling method of a hydrogen blended integrated electricity–gas system (HBIEGS) considering gas linepack is developed in this paper. The gas linepack refers to the gas stored in natural gas pipelines due to the compressibility of the gas. As a form of gas energy storage, linepack can enhance system flexibility by coping with wind power uncertainty. In the face of nonlinear gas flow equations in HBIEGS, conventional relaxation or approximate methods cannot provide a sufficiently feasible optimal solution. Therefore, a sequential second-order cone programming (S-SOCP) method is proposed to solve the developed model. It can effectively strike a balance between solution speed and the quality of the solution obtained. Finally, the modified IEEE-24-node power system and 12-node natural gas system are used to validate the effectiveness of the developed model and the proposed method. The optimization results show that the proposed method improves the computational efficiency by 91% compared with a general nonlinear solver.