Hybrid energy storage power allocation strategy for smoothing wind power output fluctuations

doi:10.19799/j.cnki.2095-4239.2023.0912

Abstract

Abstract:

In recent years, energy storage technology has become an effective means of smoothing wind power fluctuations and improving the acceptance capacity of wind power in the grid; however, wind power fluctuations are complex and variable, and a single energy storage mechanism does not have the required high energy and high power density characteristics. Therefore, to solve the problem of wind power generation power smoothing in terms of its stochastic gap and other typical characteristics, this study intends to use a hybrid energy storage technology, that combines the advantages of lithium-ion batteries and supercapacitors, to design a two-layer power decomposition and allocation strategy based on the adaptive sliding average filtering-wavelet packet decomposition; further, it aims to utilize the sliding average filtering algorithm to complete the adaptive decomposition of wind power, and obtain the minimum power required for grid-connected power and hybrid energy storage systems. The minimum power required for grid-connected power and hybrid energy storage systems is obtained. Considering that the output power of a hybrid energy storage system continues to contain rich information and the rules for determining the number of wavelet packet decomposition layers and the power cut-off point, the wavelet packet algorithm is used to decompose the suppressed wind power twice and optimize the power allocation of the hybrid energy storage system by combining with the inverter entropy value strategy. This improves the fluctuation of the wind power effectively and realizes the optimal decomposition and reasonable allocation of hybrid energy storage power. Comparative analysis of different power allocation methods uses evaluation indexes such as the fluctuation of the national standard time scale, fluctuation before and after the introduction of energy storage, power amplitude, charging and discharging times, etc. The results show that the proposed method can meet the requirements of national standards for wind farm power fluctuation, reduce the impact of fluctuations on the grid, and show better adaptability compared with the traditional wavelet packet decomposition algorithms, with the overall fluctuation situation being improved by 23.69%. The proposed method reduces the lithium battery charging and discharging times by 58.2%. The model evaluation results show that the proposed method can improve the overall economy of the hybrid energy storage system and extend the life of lithium batteries.

Key words: hybrid energy storage, adaptive sliding average algorithm, wavelet decomposition, variable frequency entropy, power allocation

CLC Number:

TM 614

Dongze GUO, Jihong ZHANG, Qingyu WANG, Shuai ZHANG. Hybrid energy storage power allocation strategy for smoothing wind power output fluctuations[J]. Energy Storage Science and Technology, 2024, 13(5): 1564-1573.

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风电场装机容量/MW	10 min波动限值/MW	1 min波动限值/MW
<30	10	3
30~150	装机容量1/3	装机容量/10
>150	50	15

经济指标	锂电池	超级电容
功率成本/(万元/MW)	930	186
容量成本/(万元/MWh)	930	1240
功率运维成本/(万元/MW)	6	8
容量运维成本/(万元/MWh)	0.001	0.001
充放电效率/%	95	90
SOC上下限	0.2~0.8	0.2~0.8
运行年限	—	20

场景	L	F_1，MAX/MW	F_10，MAX/MW	F_diff/MW
场景1	L₁-1	1.37	10.11	3.43×10³
	L₁	1.29	9.69	3.50×10³
	L₁+1	1.23	9.27	3.55×10³
场景2	L₂-1	2.34	10.79	1.44×10³
	L₂	2.29	9.66	1.49×10³
	L₂+1	2.05	9.66	1.55×10³

指标	F_1，MAX/MW	F_10，MAX/MW	F_all/MW
P_w1(t)	14.61	21.05	—
P_WPD(4,0)	1.15	9.43	2522.36
P_AMAF	1.28	9.69	3119.82

方法	N_bat/(次/天)	P_bat,max/MW	N_sc/(次/天)	P_sc,max/MW
方法1	256	15.29	888	8.50
方法2	107	8.92	650	11.10