Thermal Modelling of Utility-Scale Stationary Battery Energy Storage Systems: Analysis of Energetic and Environmental Performance

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Thermal modelling is a crucial step in the simulation and system design of stationary battery energy storage systems (BESS). The Lithium-ion battery is highly temperature-sensitive, with critical aspects such as safety, performance and lifetime duration being strongly dependent on the operating temperature of the battery. The performance of a BESS is determined by the temperature of the cells as the values of the open-circuit voltage, the available capacity, and the resistance of the cells, are all functions of the operating temperature. The energetic efficiency of a BESS is also dependent on the amount of energy consumed by auxiliary components, such as the Heating Ventilation Air Conditioning (HVAC) system to keep the temperature within permitted bounds. A Lithium-ion battery undergoes relatively lower degradation if operated within temperature limits favorable to the battery chemistry. Rates of undesired side-reactions such as solid-electrolyte interphase (SEI) growth, Lithium plating and others can be lowered by ensuring the system operates in these temperature windows. In summary, a suitably designed thermal management system can reduce inhomogeneous performance and aging of cells within a BESS, yielding substantial gains in technical, economic, and environmental performance.

As most research in this area focuses on automotive applications, an exclusive focus on stationary applications can yield new insights into the thermal aspects of a BESS. The authors seek to investigate how major aspects of the thermal design of a BESS, such as the HVAC thermal power, and the set-point for the inner air temperature affect the energetic, technical, and environmental performance of these storage systems over their lifetimes. The investigations presented in this work focus on the application of industrial peak shaving. A lumped capacity and equivalent circuit approach (0D model) is used to model the thermal behavior of the system, and is directly linked to an existent in-house time series modeling tool to simulate battery systems, and can estimate HVAC power consumption. The battery system simulation tool is integrated into an energy system simulation tool, which can model several scenarios and can estimate the carbon dioxide emissions, allowing quantities of interest to be tracked at the system level.

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