Multi-layer control strategy to enhance the economy and stability of battery energy storage system in wind farms

This paper proposes a multi-layer control strategy for the Wind-BESS system to enhance the economy and stability. The top layer targets at diminishing BESS power losses for the purpose of enhancing operational economy. By identifying local high-frequency components with strong volatility, a novel adaptive ensemble empirical mode decomposition (NAEEMD) algorithm is proposed to successively decompose the wind power signals and adaptively ascertain decomposition orders to meet the grid-connection standards. This means addresses the deficient analytical prowess of ensemble empirical mode decomposition (EEMD) algorithms in local wind power resolution and their low computational efficiency, while effectively reducing BESS rated power and energy losses. The middle layer is contrived to enhance the robustness of the BESS in smoothing energy imbalances under random wind power fluctuations. The BESS is partitioned into several battery energy storage clusters (BESCs), with each being competent to independently respond to charge–discharge power. On this basis, the notions of standby clusters and a coordinated control mechanism are put forward, along with the introduction of a universal cluster control mode that mandates at least one cluster to be assigned as a standby. The energy coordination amongst clusters empowers the system to tackle the randomness of wind power fluctuations. This guarantees that each cluster can operate at a preset state of charge (SOC) thresholds, thus maximizing the utilization of the available capacity of the BESS. The bottom layer is geared towards bolstering the safety of the BESS, and a dynamic power distribution strategy based on smoothing demand and SOC deviations for battery energy storage units (BESUs) is proposed. By ascertaining the quantity of participating BESUs and subsequently defining power distribution weights, this control strategy substantially curtails SOC deviations among units within each cluster via minimizing the number of charge–discharge actions. This approach efficaciously diminishes operational losses of BESUs while safeguarding their safety. Eventually, the proposed strategy is verified using Chinese wind power data.