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author:

Zheng, Xidong (Zheng, Xidong.) [1] | Jin, Tao (Jin, Tao.) [2]

Indexed by:

EI

Abstract:

In order to solve the problem of insufficient smoothing ability and excessive smoothing, this paper proposes a method combining exponential smoothing short-term wind power forecasting with wavelet packet decomposition. According to the optimal decomposition level, the output power in line with the grid connection standard can be obtained. To improve the service life and reliability of HESS, this paper further introduce the concept of standby storage. Then, this work propose a method combining CEEMDAN with NEE and NSE to achieve the optimal power allocation instructions of the HESS. According to the residual uniqueness and adaptive frequency division, the IMF and residual components of different orders can be achieved. Then, the cut-off point with the largest proportion of energy will be obtained by NEE and the cut-off point with the lowest self-similarity by NSE, which leads to the reasonable power allocation. In the simulation and experiment analysis, it further verifies that the introduction of standby storage element can effectively reduce the charge and discharge times of the HESS, decrease the fluctuation index of SOC, which improve the service life and identification accuracy of HESS. The result shows a certain feasibility and actual significance in the practical applications. © 2021

Keyword:

Entropy Wavelet analysis Wavelet decomposition Wind power

Community:

  • [ 1 ] [Zheng, Xidong]Department of Electrical Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Jin, Tao]Department of Electrical Engineering, Fuzhou University, Fuzhou; 350116, China

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Source :

International Journal of Electrical Power and Energy Systems

ISSN: 0142-0615

Year: 2021

Volume: 131

5 . 6 5 9

JCR@2021

5 . 0 0 0

JCR@2023

ESI HC Threshold:105

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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