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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

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Front. Energy    2016, Vol. 10 Issue (1) : 46-56    https://doi.org/10.1007/s11708-015-0384-4
RESEARCH ARTICLE
A novel method for reliability and risk evaluation of wind energy conversion systems considering wind speed correlation
Seyed Mohsen MIRYOUSEFI AVAL, Amir AHADI(), Hosein HAYATI
Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran
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Abstract

This paper investigates an analytical approach for the reliability modeling of doubly fed induction generator (DFIG) wind turbines. At present, to the best of the authors’ knowledge, wind speed and wind turbine generator outage have not been addressed simultaneously. In this paper, a novel methodology based on the Weibull-Markov method is proposed for evaluating the probabilistic reliability of the bulk electric power systems, including DFIG wind turbines, considering wind speed and wind turbine generator outage. The proposed model is presented in terms of appropriate wind speed modeling as well as capacity outage probability table (COPT), considering component failures of the wind turbine generators. Based on the proposed method, the COPT of the wind farm has been developed and utilized on the IEEE RBTS to estimate the well-known reliability and sensitive indices. The simulation results reveal the importance of inclusion of wind turbine generator outage as well as wind speed in the reliability assessment of the wind farms. Moreover, the proposed method reduces the complexity of using analytical methods and provides an accurate reliability model for the wind turbines. Furthermore, several case studies are considered to demonstrate the effectiveness of the proposed method in practical applications.
Keywords doubly-fed induction generator (DFIG)      composite system adequacy assessment      wind speed correlation     
Corresponding Author(s): Amir AHADI   
Online First Date: 04 November 2015    Issue Date: 29 February 2016
 Cite this article:   
Seyed Mohsen MIRYOUSEFI AVAL,Amir AHADI,Hosein HAYATI. A novel method for reliability and risk evaluation of wind energy conversion systems considering wind speed correlation[J]. Front. Energy, 2016, 10(1): 46-56.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-015-0384-4
https://academic.hep.com.cn/fie/EN/Y2016/V10/I1/46
Fig.1  DFIG-based wind turbine structure
Fig.2  Wind turbine output power
Fig.3  Homogenous Markov model and alternative representation
Fig.4  Single line diagram of the RBTS
Fig.5  System load model
Fig.6  Weibull distribution failure rate function
Fig.7  Reliability function after 25 years of operation
Size/MW Type Number Force outage rate (FOR) MTTF/h MTTR/h Maintenance/ (week·a−1)
5 Hydro 2 0.010 4380 45 2
10 Thermal 1 0.020 2190 45 2
20 Hydro 4 0.015 3650 55 2
20 Thermal 1 0.025 1752 45 2
40 Hydro 1 0.020 2920 60 2
40 Thermal 2 0.030 1460 45 2
Tab.1  Generating unit reliability data for the RBTS
Components Failure rate/(occ·a−1) Repair time/h
Tower 0.006 104.1
Blade and pitch control system 0.052 91.6
Yaw system 0.026 259.4
Gearbox 0.045 256.7
Brake system 0.005 125.4
Generator 0.021 210.7
Converters 0.067 106.6
Control system 0.050 184.6
Sensors 0.054 49.4
Transformer 0.054 200
Tab.2  Components’ failure and repair rates
Cap./MW Individual prob. Cumulative prob.
240 0.386386253425036 1
200 1.17478669934231 × 10−20 1.22094237127171 × 10−20
160 4.71396420153462 × 10−53 4.78825252211568 × 10−53
120 4.10280758991903 × 10−92 4.13515844876768 × 10−92
80 5.02030192395467 × 10−137 5.04010052879223 × 10−137
40 1.33243531266718 × 10−188 1.33453755303304 × 10−188
0 4.66715620627261 × 10−253 4.66715620627261 × 10−253
Tab.3  Outage state enumeration of the wind farm based on monotonically increasing order
Fig.8  Impact of different compensators on reliability indices of RBTS
Fig.9  Results of increasing the number of WTGs on reliability indices of RBTS
Fig.10  Degradation of reliability indices in 40?MW generation outage and compensation with WTG
Index Default FOR
(0.03) (0.015) (0.007893) (0.003) (0.001)
LOLE/(h·a−1) 7.4167 0.13739 0.12829 0.12401 0.12106 0.11986
EENS/(MWh·a−1) 77.785 1.0639 0.97556 0.93551 0.90862 0.89778
PLC 0.0083416 0.00019092 0.00019002 0.00018982 0.00018973 0.00018969
EDNS/MW 0.093979 0.0017409 0.0016256 0.0015713 0.001534 0.0015188
EDC/(103$·a−1) 343.81 4.7025 4.312 4.135 4.0161 3.9682
BPECI/(MWh·MW−1·a−1) 0.42046 0.0057509 0.0052733 0.0050568 0.0049115 0.0048529
MBECI/(MW·MW−1) 0.00050799 9.4102×10−6 8.7871×10−6 8.4937×10−6 8.2921×10−6 8.2097×10−6
SI/(system min·a−1) 25.228 0.34505 0.3164 0.30341 0.29469 0.29117
Tab.4  Impact of adding WTG with different FORs on reliability indices
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