Cryogenic energy storage: Standalone design, rigorous optimization and techno-economic analysis. (15th September 2022)

• Record Type: Journal Article
• Authors: Gandhi, Akhilesh; Zantye, Manali S.; Faruque Hasan, M.M.
• Is Part Of: Applied energy. Volume 322(2022)
• Publication Date: 2022-09-15
• Subjects: Cryogenic energy storage -- Bayesian optimization -- Simulation-based optimization -- LCOS -- Techno-economic analysis; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2022.119413
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: Energy storage allows flexible use and management of excess electricity and intermittently available renewable energy. Cryogenic energy storage (CES) is a promising storage alternative with a high technology readiness level and maturity, but the round-trip efficiency is often moderate and the Levelized Cost of Storage (LCOS) remains high. The complex flowsheets with intricate thermodynamics at cryogenic temperatures as well as the presence of multiple loops and refrigeration cycles pose considerable challenges for rigorous model-based design and optimization of CES systems. We present an optimization strategy that couples rigorous process simulation and Bayesian optimization with flowsheet decomposition and identification of hidden coupling constraints to optimally design standalone CES systems. Further refinement is done via a local search using the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. Our results indicate that it is possible to achieve more than 52% round-trip efficiency and an LCOS of $153/MWh for a standalone 100 MW/400 MWh CES system limited to short-term storage with daily charging–discharging. However, a detailed techno-economic assessment reveals that the LCOS considering total capital investment may exceed $267/MWh when all direct and indirect costs of installation and operation are considered. Highlights: A systematic process optimization and techno-economic analysis of stand-alone cryogenic energy systems. Simulation-based black-box optimization technique with embedded convergence algorithm for feasible CES flowsheet simulation. Maximizing the CES round-trip efficiency (RTE). Detailed calculation of the levelized cost of storage (LCOS) for standalone CES. Sensitivity analysis for varying ambient conditions.