A grid view on the dynamics of processes participating in demand response programs. (January 2023)

• Record Type: Journal Article
• Authors: Tang, Xin; Baldea, Michael
• Is Part Of: Computers & chemical engineering. Volume 169(2023)
• Publication Date: 2023-01
• Subjects: Energy storage -- Demand response -- Capacity optimization -- Demand side management; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2022.108070
• Languages: English
• ISSNs: 0098-1354

Abstract

Abstract: Reaching a net-zero emissions economy will require a major increase in renewable electricity generation. Accommodating the associated generation rate variability calls, among others, for innovation in energy storage capacity. While technology developments are underway, costs remain high and motivate further work in demand-side management. We explore the potential for manufacturing systems to act as virtual generators, responding to changes in electricity prices. Using a prototype chemical process, optimal operating data are generated by solving a demand response scheduling problem under uncertainty for various cases of process responsiveness and electricity market types. System identification then reveals surprising insights on the system dynamics as viewed from a grid perspective. Highlights: Consider manufacturing processes involved in demand response. Optimize product storage capacity under uncertainty. Study the dynamic response to electricity price changes. Novel insights on storage capacity and agility needed to support the power grid.