Hybrid energy storage system control and capacity allocation considering battery state of charge self-recovery and capacity attenuation in wind farm

Abstract

Hybrid energy storage system (HESS) can cope with the complexity of wind power. But frequent charging and discharging will accelerate its life loss, and affect the long-term wind power smoothing effect and economy of HESS. Firstly, for the operational control of HESS, a bi-objective model predictive control (MPC) -weighted moving average (WMA) strategy for energy storage target power controlling is proposed, considering both energy storage state of charge (SOC) self-recovery and grid-connected power stabilization. The strategy can quickly adjust the SOC of HESS in the wind power smoothing process and reduce the battery's life loss. Then, since the energy storage capacity determines its power smoothing ability, this paper proposes a battery life model considering the effective capacity attenuation caused by calendar aging, and introduces it into the HESS cost calculation model to optimize the capacity allocation. Finally, combined with the wind power data, the simulation verifies that the proposed strategy can effectively balance the contradiction between energy storage lifetime and wind power smoothing effect. Simultaneously, the HESS optimized capacity allocation results considering battery's effective capacity attenuation can ensure the long-term wind power smoothing effect and better HESS operational states, contributing to the long-term and stable operation of wind-storage combined system.