Wind Farm Reliability Research Articles

Discussion and research on electric reliability evaluation of wind turbine

With the rapid development of wind power in China, the installed capacity has leapt to the top of the world in a few short years, and is the fastest growing power source in addition to solar energy. However, power generation capacity and installed capacity of wind turbines in China are not in proportion to the world average; the unplanned outage coefficient of wind turbines in China is much higher than the world level. Therefore, it is urgent to carry out research on the reliability of generator sets. This study analyzes and summarizes the general conditions and problems of China’s generating units, the theoretical basis of reliability evaluation of wind turbines, wind power reliability evaluation procedures, and cases, and proposes major ways to improve the reliability of wind turbines and wind farms for the majority of the Wind power industry professional and technical personnel learn from and exchange.

WIND TURBINE MAINTENANCE. A REVIEW

Climatic change has taxed humanity in terms of the use of renewable energy in most countries around the world. In this context, installed wind power has recently increased at an almost exponential rate. Although there is still a large potential market that could be covered, minimizing costs has become a critical factor for a wind project to be financially justified and competitive. The present work is a bibliographical review of the primary strategies and methodologies used to reduce the cost of these activities while producing the maximum electricity from wind turbines. This review includes tabulated information on the types of faults, occurrence statistics, and associated costs and equipment suppliers for monitoring, detection, diagnosis and fault prediction and although most of it refers to onshore wind turbines, offshore wind turbines are also included in several parts. Research shows that in order to guarantee the reliability and economic feasibility of wind farms, the most used methodologies is CMS, which include vibration analysis, acoustic emission, ultrasonic testing techniques, thermography, oil analysis, structural health monitoring, optical fiber monitoring, strain measurement, radiographic inspection, power signal analysis. Currently, in addition to technical personnel, turbine operation and maintenance include, sensors, software, trucks, cranes, boats, helicopters, drones and smartphone applications. Keywords: wind turbines, maintenance strategies, cost, types of faults, condition monitoring system

Methods for Advanced Wind Turbine Condition Monitoring and Early Diagnosis: A Literature Review

Condition monitoring and early fault diagnosis for wind turbines have become essential industry practice as they help improve wind farm reliability, overall performance and productivity. If not detected and rectified at early stages, some faults can be catastrophic with significant loss or revenue along with interruption to the business relying mainly on wind energy. The failure of Wind turbine results in system downtime and repairing or replacement expenses that significantly reduce the annual income. Such failures call for more systematized operation and maintenance schemes to ensure the reliability of wind energy conversion systems. Condition monitoring and fault diagnosis systems of wind turbine play an important role in reducing maintenance and operational costs and increase system reliability. This paper is aimed at providing the reader with the overall feature for wind turbine condition monitoring and fault diagnosis which includes various potential fault types and locations along with the signals to be analyzed with different signal processing methods.

Reliability Assessment of Wind Farm Electrical System Based on a Probability Transfer Technique

The electrical system of a wind farm has a significant influence on the wind farm reliability and electrical energy yield. The disconnect switch installed in an electrical system cannot only improve the operating flexibility, but also enhance the reliability for a wind farm. Therefore, this paper develops a probabilistic transfer technique for integrating the electrical topology structure, the isolation operation of disconnect switch, and stochastic failure of electrical equipment into the reliability assessment of wind farm electrical system. Firstly, as the traditional two-state reliability model of electrical equipment cannot consider the isolation operation, so the paper develops a three-state reliability model to replace the two-state model for incorporating the isolation operation. In addition, a proportion apportion technique is presented to evaluate the state probability. Secondly, this paper develops a probabilistic transfer technique based on the thoughts that through transfer the unreliability of electrical system to the energy transmission interruption of wind turbine generators (WTGs). Finally, some novel indices for describing the reliability of wind farm electrical system are designed, and the variance coefficient of the designed indices is used as a convergence criterion to determine the termination of the assessment process. The proposed technique is applied to the reliability assessment of a wind farm with the different topologies. The simulation results show that the proposed techniques are effective in practical applications.

Availability estimation of a multi-state wind farm in fuzzy environment

ABSTRACTWind is one of the fastest growing renewable energy resources in the electric power system. Availability of wind energy is volatile in nature due to the stochastic behavior of wind speed and non-linear variation of the wind power curve of wind turbine generator. Because of this impression and uncertainty, the availability estimation of wind power has become a challenging issue. In this paper, Markov Fuzzy Reward technique has been proposed for finding out the reliability of wind farm by assessing the availability of wind power. According to this technique, availability of the wind power has been estimated considering wind farm and demand both as a multi-state system. In addition to the availability, different reliability indices such as the number of absolute failures, mean time to deficiency, and probability of failures of a wind farm have been assessed in a time horizon, which can provide useful information for the power system planner at wind farm installing stage. A comparison of this study reveals the efficacy of the proposed Markov Fuzzy Reward approach over the conventional Markov Reward approach.

A Wind Farm Reliability Model Considering Both Wind Variability and Turbine Forced Outages

This paper presents an analytical method to model the output of large wind farms for power system reliability assessment. The model considers the variability of wind, random failures (forced outages) of turbines, as well as the correlation between turbine outputs that results from the turbines on a farm being subjected to similar incident wind speeds. Due to this correlation, the outputs of individual turbines cannot be modeled as independent random variables. The problem is addressed here by separately modeling the independent outages of wind turbines and the dependency on wind speed, and then convolving the two distributions. The resulting model includes both probability and frequency distributions of the power output of the wind farm. The proposed method is demonstrated on the IEEE Reliability Test System. Monte Carlo simulation is used to validate the results.

ARIMA Based Wind Speed Modeling for Wind Farm Reliability Analysis and Cost Estimation

Necessity has compelled man to improve upon the art of tapping wind energy for power generation; an apt reliever of strain exerted on the non-renewable fossil fuel. The power generation in a Wind Farm (WF) depends on site and wind velocity which varies with time and season which in turn determine wind power modeling. It implies, the development of an accurate wind speed model to predict wind power fluctuations at a particular site is significant. In this paper, Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) time series model for wind speed is developed for a 99MW wind farm in the southern region of India. Because of the uncertainty in wind power developed, the economic viability and reliability of power generation is significant. Life Cycle Costing (LCC) method is used to determine the economic viability of WF generated power. Reliability models of WF are developed with the help of load curve of the utility grid and Capacity Outage Probability Table (COPT). ARIMA wind speed model is used for developing COPT. The values of annual reliability indices and variations of risk index of the WF with system peak load are calculated. Such reliability models of large WF can be used in generation system planning.

Climatic Impacts and Reliability of Large Scale Wind Farms in Tamil Nadu

Objective: The main objective of this paper describes how the large scale windfarms affect the climate of south west monsoon region. Methods/Analysis: Method used for analysing climatic parameters of before and after installation of wind farms is Gaussian mixture model. ArcGIS and QGIS software is used for image and geo-information analysis. Data from the commercial wind turbine of south west monsoon region like temperature, relative humidity, precipitation, wind speed is used to find the climatic variation. Findings: Large scale wind farms significantly affect the various climatic parameters. These impacts depends on the static stability, increase or decrease in the climatic parameters. Conclusion/ Application: Improvements can be made by taking the ground temperature measured by satellite image and identify the warming effect of night and day time warming effect of large scale wind farm area of southwest monsoon regions.

Wind Farm Reliability Modelling Using Bayesian Networks and Semi-Markov Processes

Wind Farm Reliability Modelling Using Bayesian Networks and Semi-Markov Processes

풍력발전단지 관리·분석 시스템의 Real-Time Simulator 도입을 위한 계통모델 연동방안 연구

Owing to the variability of large-scaled wind power system, the development of wind farm management technologies and related compensation methods have been receiving attention. To provide an accurate and reliable output power, certain wind farm adopts a specified management system including a wind prediction model and grid expectation solutions for considering grid condition. Those technologies are focused on improving the reliability and stability issues of wind farms, which can affect not only nearby system devices but also a voltage condition of utility grid. Therefore, to adapt the develop management system, an expectation process about voltage condition of Point of Common Coupling should be integrated in operating system for responding system requirements in real-time basis. This paper introduce a grid imposing method for a real-time based wind farm management system. The expected power can be transferred to the power flow section and the required quantity about reactive power can be calculated through the proposed system. For the verification process, the gauss-seidel method is introduced in the Matlab/Simulink for analysing power flow condition. The entire simulation process was designed to interwork with PSCAD for verifying real power system condition.

Improving stability of utility-tied wind generators using dynamic voltage restorer

The generation of electricity using wind power is significantly increasing and has received considerable attention in recent years. One important problem with the induction generator based wind farms is that they are vulnerable to voltage disturbances and short circuit faults. Any such disturbance may cause wind farm outages. Since wind power contribution is in considerable percentage, such outages may lead to power system stability issues and also violate the grid code requirements. Thus, improving the reliability of wind farms is essential to maintain the stability of the system. The proposed strategy is to use Dynamic Voltage Restorer (DVR), which is one of the promising devices to compensate the voltage disturbance and to improve the stability of the system. It provides the wind generator with the fault ride through capability and improves the reliability of the system. Extensive simulation results are included to illustrate the operation of DVR and fault compensation.

Wind Farm Collector System Research

As environment problem becomes increasingly prominent and energy supply becomes more and more tension, wind power as a kind of clean and renewable energy is more and more popular. The installation of large scale wind farms has been paid much attention. Collector system consolidates the power generated by turbine units to a substation from where the generated power is transmitted to the power system. Where designing a wind farm collector system, the economics and reliability of operation should be taken consideration. This paper introduces the concept and some typical layouts of the wind farm collector system, then take comparison of those layout around the economics and reliability, this may help to choose an appropriate cable layout when building a new wind farm.

Assessing Wind Farm Reliability Using Weather Dependent Failure Rates

Using reliability data comprising of two modern, large scale wind farm sites and wind data from two onsite met masts, a model is developed which calculates wind speed dependant failure rates which are used to populate a Markov Chain. Monte Carlo simulation is then exercised to simulate three wind farms which are subjected to controlled wind speed conditions from three separate potential UK sites. The model then calculates and compares wind farm reliability due to corrective maintenance and component failure rates influenced by the wind speed of each of the sites. Results show that the components affected most by changes in average daily wind speed are the control system and the yaw system. A comparison between this model and a more simple estimation of site yield is undertaken. The model takes into account the effects of the wind speed on the cost of operation and maintenance and also includes the impact of longer periods of downtime in the winter months and shorter periods in the summer. By taking these factors into account a more detailed site assessment can be undertaken. There is significant value to this model for operators and manufacturers.

A probabilistic model for assessing the reliability of wind farms in a power system

Modeling the generation of a wind farm and its effect on power system reliability is a challenging task, largely due to the random behavior of the output power. In this paper, we propose a new probabilistic model for assessing the reliability of wind farms in a power system at hierarchical level II (HLII), using a Monte Carlo simulation. The proposed model shows the effect of correlation between wind and load on reliability calculation. It can also be used for identifying the priority of various points of the network for installing new wind farms, to promote the reliability of the whole system. A simple grid at hierarchical level I (HLI) and a network in the north-eastern region of Iran are studied. Simulation results showed that the correlation between wind and load significantly affects the reliability.

Reliability Modeling of Wind Farm Considering the Outages of Connection Cables

Considering the randomness of wind speed and wind direction, the partial wake effect between wind turbines (WTs) in complex terrain was analyzed and a multiple wake model in complex terrain was established. Taking the power output characteristic of WT into consideration, a wind farm reliability model which considered the outages of connection cables was presented. The model is implemented in MATLAB using sequential Monte Carlo simulation and the results show that this model corrects the power output of wind farm, while improving the accuracy of wind farm reliability model.

Reliability Assessment of Composite Generation and Transmission System with Wind Farms

Wind energy will affect the reliability of power system for its randomness and fluctuation. In this paper, the steady state model for the asynchronous generator is established and wind farms are considered as special PQ buses during power flow calculation. Combining with state models of conventional generating units, transmission lines and transformers, a time-sequential Monte Carlo simulation based on wind farm reliability model is established to do reliability assessment of composite generation and transmission system with wind farm. Meanwhile, an optimal load shedding model is used to decrease shedding load. IEEE-RTS test system is used to prove the proposed method. Analysis and comparison of results show that reliability can be improved clearly after integration of wind farm.

Performance, reliability and failure analysis of wind farm in a developing Country

In this paper, an analysis of the performance, failure and reliability, as well as a spare parts analysis have been conducted for a wind farm, which has 15 wind turbine generators (WTGs), each of 225 kW capacity. This wind farm is located at Muppandal, Tamil Nadu, South India. The average value of performance parameters such as technical availability, real availability and capacity factor for the wind farm were 94%, 82.88% and 24.9% respectively during the years 2000–2004. This paper also deals with Pareto analysis to find out the reduction in problems, when one problem is tackled partly and completely. The Weibull technique was also used for the reliability analysis. The reliability factor in the initial period after one year seems to be good as the wind farm has a lower failure rate of 0.000019. As a supplemental activity, spare parts optimization was also carried out for a few vital components of this wind farm and the results are presented. The failure and its financial implications are also analyzed in this paper.

Aspects of Relevance in Offshore Wind Farm Reliability Assessment

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The worldwide increase of installed wind power capacity demands the inclusion of wind farm (WF) models into power system reliability assessment. This paper looks at this issue from available literature, and presents a list of factors that highly influence offshore WF generation. An example of sequential Monte Carlo simulation applied to an offshore WF is described using a new synthetic wind-speed generator. The simulation includes some of the reliability factors highlighted in the paper and their influence on reliability assessment. </para>