This paper addresses the problem of coordinating the operation of electricity and natural gas (NG) transmission systems with green hydrogen (H2) production and injection into existing NG networks. In ...particular, the operation of the two systems consists of a two-stage optimization framework that solves a network-constrained unit commitment (UC) problem with transmission power losses to obtain the profiles of gas energy demands from gas-powered generators and the maximum allowable H2 injection flow rates from power-to-gas (PtG), which are then used as inputs to an optimal transient NG-H2 flow problem with H2 concentration tracking. The nonlinearities introduced by the discretization of the H2 concentration tracking equations are particularly challenging to solve using second-order nonlinear programming (NLP) methods. Moreover, the nonlinear constraints capturing transmission line losses make the electricity operational problem intractable if solved with mixed-integer NLP methods. Therefore, this work leverages the reliability and scalability of linear programming (LP) by designing two novel and distinct sequential LP (SLP) methods that exploit the particular structures of the two problems to find feasible, possibly optimal solutions, using only first-order information. The algorithmic framework is demonstrated on the IEEE 24-bus RTS connected to the 22-node Belgian gas network. This paper is the first to demonstrate H2 concentration tracking under transient gas flow in a multi-energy optimization framework on a realistic gas transmission network with multiple H2 injection locations.
•H2 concentration tracking under transient gas flow in an optimization framework.•Tracking of H2 molar fractions in a realistic gas network with multiple H2 injections.•Sequential linear programming for the optimal transient NG-H2 flow problem.•Sequential MILP for the unit commitment with transmission line losses.•Analysis of the impact of H2 blending on the NG-H2 system linepack.
