Optimal scheduling of a large-scale power-to-ammonia process: Effects of parameter optimization on the indirect demand response potential. (February 2023)

• Record Type: Journal Article
• Authors: Hochhaus, Thorben; Bruns, Bastian; Grünewald, Marcus; Riese, Julia
• Is Part Of: Computers & chemical engineering. Volume 170(2023)
• Publication Date: 2023-02
• Subjects: Haber–Bosch process -- PEM electrolysis -- Flexible operation -- Operating window -- Scheduling; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2023.108132
• Languages: English
• ISSNs: 0098-1354

Abstract

Abstract: In the light of the increasing share of power generation from renewable energy sources, there is a growing interest in flexible operation of power-intensive processes for demand-side management/demand response. In this article, we investigate the potential application of a large-scale power-to-ammonia process in demand response programs. The process system under consideration consists of a polymer exchange membrane electrolysis that is optimally scheduled in accordance with day-ahead prices and a large-scale Haber–Bosch process that serves as a downstream energy storage. We apply a demand-side management framework with a sequential approach to identify the indirect demand response potential of the considered process system. Our results show that the power-to-ammonia process provides significant leverage for demand-side management. Moreover, we find that increasing process flexibility by optimizing operational parameters improves the demand response potential and that price profile dispersion can be used as an indicator to predict the economic performance of demand response scheduling. Graphical abstract: Highlights: Evaluation of the demand response potential of a large-scale power-to-ammonia process. Dynamic optimization to assess demand response scheduling economics. Prediction of cost savings by means of price profile characteristics. Parameter optimization to enhance profitability of demand response scheduling.