Cost-optimizing ESS Environmental Control Based on Internal Resistance and Time-Series Forecasting of External Conditions

Energy storage system(ESS) based on rechargeable battery have varying energy efficiency depending on its internal resistance. Among the many factors that affect the internal resistance, temperature is one of the major factor. The external temperature of ESS operating environment can be controlled to improve the energy efficiency, however such control comes with its own cost. The recent development of internet of things(IoT) technology and time-series forecasting allows the ESS operator to monitor and predict the short-term external environment. In this paper we model a scenario which low outside temperature may affect the battery internal resistance, and compare the net cost under various temperature control scheme. We show that adequate temperature control based on short-term forecast is more beneficial than the baseline scheme of no control.