Optimization of liquid air energy storage systems using a deterministic mathematical model

Liquid air energy storage (LAES) systems are a promising technology for storing electricity due to their high energy density and lack of geographic constraints. However, some LAES systems still have relatively low roundtrip efficiencies. This work aims to improve LAES system performance through optimization strategies. Deterministic non-linear mathematical models were implemented in an object-oriented equation-based programming language. An optimization algorithm was applied to the LAES system. The model was designed to facilitate the removal of components and find novel configurations, despite not incorporating discrete decisions (binary variables). After successful verification, the model was used to maximize round-trip efficiency. Compared to the base case, the round-trip efficiency and liquid air yield increased by approximately 63 % and 48 %, respectively. The optimal solution obtained had an impact on the LAES system structure, eliminating a heat exchanger in the cold box compared to the base case and resulting in a new system configuration. The proposed mathematical model is a valuable tool for decision-making in optimizing LAES systems, effectively simulating and optimizing these systems. This work represents an advance in mathematical modeling from the perspective of Process System Engineering (PSE). It showcases the application of simultaneous optimization, derivative-based algorithms, and rigorous property package estimation through dynamic link libraries to optimize a LAES system.