A method to bridge energy and process system optimization: Identifying the feasible operating space for a methanation process in power-to-gas energy systems

Abstract

The growing adoption of renewable energy is driving the integration of new, complex process technologies into energy systems, presenting operational optimization challenges. Simple models are necessary for computational tractability, yet detailed models are essential for feasible operating decisions. This work introduces a method for optimally operating an energy system with integrated complex process technologies. The proposed method bridges the mathematical modeling and optimization at energy and process system levels. Simple surrogate models and detailed process models are used to represent complex process technologies at their respective system levels. The resulting operational problems are solved through a sequential iterative approach. Applied to a power-to-gas energy system with an integrated methanation process, our method outperforms a benchmark method by capturing interactions between energy and process system levels, and among different process variables. The proposed method integrates more detailed constraints and ramping costs, yielding an optimal, feasible operating strategy within tractable computational time.