Research On Capacity Configuration And Coordinated Control Of Hybrid Energy Storage System For Smoothing Out Wind Power Fluctuations

The advancement and utilization of intermittent renewable energy has opened the door for fixing the ongoing world energy crisis and environmental pollution. Thus, it is strategically crucial to help upgrade energy structure and ensure sustainable economic evolution of China. Since the energy storage system can absorb or release the power, it is recognized as an effective technique to smooth out power fluctuation and improve the grid-connected ability of the intermittent power. With different storage technologies having differing characteristics, nowadays batteries are used in a complementary mode with other storage devices to match wind power fluctuations. The benefit of combining the different storage technologies into a HESS is that it allows each specific energy storage technology to focus on its "best fit" in terms of time-scale and energy-scale. Thus, research on capacity configuration and coordinated control of the HESS can be substantial both in theories and applications.The main work is presented as follow:1) A novel wavelet-based capacity configuration algorithm is developed for a HESS, which makes full use of ultra-capacitors and lithium batteries and allocates fluctuations using frequency distribution. Based on a wind farm’s power history database, with the suitable wavelet obtained via entropy-based optimal wavelet choosing strategy, wavelet multiresolution signal decomposition is applied to allocate fluctuations with different frequency bands to the LB and the UC within the HESS. The proposed approach uses a good wavelet-based structure that is easy to implement.2) A novel online-wavelet-based coordinated control strategy for a HESS is implemented, consisting of primary filtering (PF) and secondary filtering (SF) stages. The PF stage obtains a combined power output that fully satisfies the FMRs, while the SF stage provides additional smoothing of the wind power output fluctuations after the PF stage. A State-of-Charge (SOC) feedback control maintains the SOC of the battery bank within its proper range. Case studies demonstrate that the required storage ratings are lower than the ratings calculated by conventional FDF-based techniques.3)A novel model predictive control based period divided coordinated control algorithm is proposed for HESS in smoothing out wind power fluctuations. In the computing period, the goal is to minimize the cost of HESS in the next prediction horizon, IPOPT solver is deployed, and the optimal power output of LB is obtained, as well as the optimal time constant of first-delay filter for obtaining the power output of UC. In the non-computing period, the optimal time constant in the last computing period is kept to directly get the power output of UC, and the goal of this stage is to minimize the power output of LB in the next prediction horizon. Rolling-horizon control strategy is employed to realize real-time control, and hence the ability of addressing all kinds of disturbance and uncertainty is enhanced. Certain strategy is adopted to equivalently translate the fluctuation constraints into linear constraint, combined with the constraint relaxation technology, and the success rate of optimization is tremendously lifted. State-of-Charge (SOC) feed-back control strategy is proposed to regulate the SOC of the HESS within its proper range. Furthermore, an adaptive penalty function of roughness is developed to further smooth the combined output. Simulation studies and quantitative comparisons demonstrate that the proposed MPC-based algorithm needs lower power rating and storage capacity to satisfy1-minute and30-minute FMRs.