Variable charge/discharge time-interval control strategy of BESS for wind power dispatch
A variable charge/discharge time-interval ($T_{C/D})$ control strategy of a battery energy storage system (BESS) for wind power dispatch is proposed in this paper, aiming at: 1) extending the BESS life, 2) reducing the total BESS energy loss, and 3) increasing the dispatch tracking accuracy. A multifactor life model of a large-scale BESS containing four factors, charge/discharge rate, times, $T_{C/D}$, and temperature, is developed, which has taken into account the cell series/parallel effects and BESS operational characteristics. A comprehensive evaluation system including BESS aging level (BAL), energy loss index (ELI), and tracking inaccuracy index (TII) is proposed, and the relationships between $T_{C/D}$ and the three indices are discussed. In order to combine the advantages of low BAL and low ELI under long $T_{C/D}$ and low TII under short $T_{C/D}$, a fuzzy controller is designed to regulate $T_{C/D}$ in real time. The effectiveness of the proposed control strategy is verified by actual data from a wind farm in eastern China.
Variable charge/discharge time-interval control strategy of BESS for wind power dispatch
A variable charge/discharge time-interval ($T_{C/D})$ control strategy of a battery energy storage system (BESS) for wind power dispatch is proposed in this paper, aiming at: 1) extending the BESS life, 2) reducing the total BESS energy loss, and 3) increasing the dispatch tracking accuracy. A multifactor life model of a large-scale BESS containing four factors, charge/discharge rate, times, $T_{C/D}$, and temperature, is developed, which has taken into account the cell series/parallel effects and BESS operational characteristics. A comprehensive evaluation system including BESS aging level (BAL), energy loss index (ELI), and tracking inaccuracy index (TII) is proposed, and the relationships between $T_{C/D}$ and the three indices are discussed. In order to combine the advantages of low BAL and low ELI under long $T_{C/D}$ and low TII under short $T_{C/D}$, a fuzzy controller is designed to regulate $T_{C/D}$ in real time. The effectiveness of the proposed control strategy is verified by actual data from a wind farm in eastern China.
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