A review on reliability assessment for wind power

Jiang, Wen; Yan, Zheng; Feng, Donghan

doi:10.1016/j.rser.2009.06.006

Cited by 164 publications

(78 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…v: wind speed (m/s); c : scale factor and k form factor.Parameters of Weibull distribution can be estimated by several methods, the most frequently employed are : moments methods [13]; least squares method [14]; the estimation of the maximum likelihood [15][16]. The last one will be used in our comparative case study [17].…”

Section: Comparative Methods Of Wind Energy Estimationmentioning

confidence: 99%

Horizontal Extrapolation of Wind Speed Distribution Using Neural Network for Wind Resource Assessment

2017

IJSR

View full text Add to dashboard Cite

Abstract:To evaluate the wind potential on a site for future wind energy project, an accurate representation of the wind speed distribution is required. However, due to the lack of observations, wind engineers are conducted to use some statistical tools to estimate the characteristics of wind by the measurements from a nearby reference or data obtained from a short period. In this work, we aim at applying an information processing paradigm that is inspired by biological neurons, formal neurons, for the assessment of wind speed distribution. Two different learning algorithms are used so as to generate Artificial Neural Network with one hidden layer. Results prove that learning by means of Bayesian regularization, in comparison with Levenberg-Marquardt learning algorithm, gives the best performance. In addition, the proposed network allows significant results in horizontal wind extrapolation.

show abstract

Section: Comparative Methods Of Wind Energy Estimationmentioning

confidence: 99%

Horizontal Extrapolation of Wind Speed Distribution Using Neural Network for Wind Resource Assessment

2017

IJSR

View full text Add to dashboard Cite

show abstract

“…V ci and V co are turbine cut-in and cut-out speeds, respectively, and A , B , and C are constants determined from V r , V ci , V co , and the other system parameters. h is the time in hours [7].…”

Section: Generation Time Series Modelmentioning

confidence: 99%

“…Therefore, all wind turbines can be considered as one aggregated unit [11]. In the multistate model [7], all the states are given in the capacity-in probability table, as shown in Table 1. The capacity value of each state is derived from the power output curve of the wind turbine.…”

Section: Reliability Indicesmentioning

confidence: 99%

“…The capacity value of each state is derived from the power output curve of the wind turbine. The probability in each state is obtained from a combination of the Weibull probability distribution function [7,32] for the wind speed data and the FOR of the wind turbine. Table 1 provides the probability of the generated power being less than or equal to a given value.…”

Section: Reliability Indicesmentioning

confidence: 99%

See 1 more Smart Citation

Reliability assessment of a standalone wind-conventional/energy storage system using probabilistic production simulation method

Delavaripour¹,

Dehkordi²

2015

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

This paper presents a reliability evaluation technique for a small standalone system including wind and conventional resources integrated with an energy storage system. A battery bank is considered as the energy storage system. The focus in this analysis is on the effect of battery modeling and its performance on system reliability. In this way, this paper presents an accurate model for the electrochemical batteries, which takes into account all the influential characteristics of the battery related to reliability studies, such as depth of charge, efficiency of charge, and rate of discharge. The proposed reliability evaluation method is based on the combination of a probabilistic production simulation technique as an analytical method and time series technique, in the domain of adequacy studies. By using the probabilistic production simulation technique, not only can the reliability of wind-conventional resources be assessed, but the fuel consumption can also be analyzed. On the other hand, by using the time series approach, the time variation of wind speed and operating constraints of the battery bank can be considered in evaluating the reliability indices. In this paper, a typical lead-acid battery bank is used. It is shown how the accurate modeling of the battery bank can affect the reliability indices. Beneficial results are obtained for different operating strategies and wind penetrations and are then compared.

show abstract

“…The randomness of wind speed determines the WTPO. The relationship between the WTPO and the wind speed is nonlinear due to the combined effects of aero-turbine and generator characteristics [21]. However, the assumption of the linear characteristic of the WTPO with the wind speed simplifies the calculations without roughly errors.…”

Section: Wind Turbine Power Output Modelmentioning

confidence: 99%

A Reliability Model of Wind Farm Considering the Complex Terrain and Cable Failure Based on Clustering Algorithm

Liu¹,

Chen²,

Zhang³

et al. 2014

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-A reliability model of wind farm located in mountainous land with complex terrain, which considers the cable and wind turbine (WT) failures, is proposed in this paper. Simple wake effect has been developed to be applied to the wind farm in mountainous land. The component failures in the wind farm like the cable and WT failures which contribute to the wind farm power output (WFPO) and reliability is investigated. Combing the wind speed distribution and the characteristic of wind turbine power output (WTPO), Monte Carlo simulation (MCS) is used to obtain the WFPO. Based on clustering algorithm the multi-state model of a wind farm is proposed. The accuracy of the model is analyzed and then applied to IEEE-RTS 79 for adequacy assessment.

show abstract

A review on reliability assessment for wind power

Cited by 164 publications

References 24 publications

Horizontal Extrapolation of Wind Speed Distribution Using Neural Network for Wind Resource Assessment

Horizontal Extrapolation of Wind Speed Distribution Using Neural Network for Wind Resource Assessment

Reliability assessment of a standalone wind-conventional/energy storage system using probabilistic production simulation method

A Reliability Model of Wind Farm Considering the Complex Terrain and Cable Failure Based on Clustering Algorithm

Contact Info

Product

Resources

About