State of Energy Recovery of Battery Energy Storage System With Primary Frequency Control for Battery Aging Mitigation

The aging of battery in the battery energy storage system (BESS) with primary frequency control (PFC) is more complicated than in conventional conditions. To mitigate battery aging, this article proposes a novel state of energy (SOE) recovery strategy for BESSs with PFC. A double-layer long short-term memory (D-LSTM) framework with rolling correction is proposed to predict the SOE of battery under PFC. Then, the predicted SOE is decomposed into signals with different levels of volatility using the empirical mode decomposition (EMD) method. The signals are then reconstructed into high-frequency and low-frequency groups based on gray correlation analysis. By retaining the low-frequency component, the predicted SOE is filtered. The filtered SOE is further divided into predicted charge–discharge segments (PCDSs), which demonstrate the variation of SOE. The SOE is then recovered by considering the estimated SOE variation within the PFC dead band (PFC-DB) (i.e., out of the frequency regulation state), achieving extended application boundary. An index of levelized cost of storage (LCOS)-based assessment approach of battery aging is introduced, which is applied to analyze the economics and effectiveness of the proposed method. The case study results verify that the proposed strategy significantly decreases the charge–discharge times of battery, compared with conventional methods, which effectively prolongs the battery lifespan and lowers the LCOS of BESS operations.