Equivalent Model Of Wind Farm Research Articles

A Practical Equivalent Method for DFIG Wind Farms

With increasing penetration of wind power, it is recognized that manufacturer-specific models of wind turbines are not appropriate for power system studies, and the equivalent model of wind farms required by dynamic modeling poses a complicated technical challenge. In this paper, a practical equivalent method for wind farms with doubly fed induction generator (DFIG) wind turbines is proposed. Three critical steps are involved in this method. Step 1, modeling of a wind turbine, the model incorporating the complete fault ride through process is constructed and validated for an operational DFIG wind turbine. Step 2, clustering of wind turbines, a practical four-machine equivalent method is proposed. Initially, dynamic responses of active power of a DFIG wind turbine operating at various wind speeds are investigated to obtain three clusters of wind turbines, then four clusters are further determined by improving equivalency error at some typical wind speed scenarios. Step 3, an analytical method is proposed to determine the equivalent collector network parameters for each of the four equivalent machines. The proposed method is validated by comparing with the single-machine representation and the detailed wind farm model. Simulation results show that the proposed method has good performance for different fault durations, voltage dips, and changing wind scenarios.

Review of Recent Development of Dynamic Wind Farm Equivalent Models Based on Big Data Mining

Recently, the big data mining method has been applied in dynamic wind farm equivalent modeling. In this paper, its recent development with present research both domestic and overseas is reviewed. Firstly, the studies of wind speed prediction, equivalence and its distribution in the wind farm are concluded. Secondly, two typical approaches used in the big data mining method is introduced, respectively. For single wind turbine equivalent modeling, it focuses on how to choose and identify equivalent parameters. For multiple wind turbine equivalent modeling, the following three aspects are concentrated, i.e. aggregation of different wind turbine clusters, the parameters in the same cluster, and equivalence of collector system. Thirdly, an outlook on the development of dynamic wind farm equivalent models in the future is discussed.

Study of Time and Meteorological Characteristics of Wind Speed Correlation in Flat Terrains Based on Operation Data

The accurate calculation and characteristic analysis of wind speed correlation (WSC) is the basis of wind farm equivalent modeling, wind power prediction and other advanced applications. It is well known that the accurate calculation of WSC depends on the quality of the raw data, and the WSC of wind turbines is related to spatial, time and meteorological conditions. However, the researches on the statistical analysis of time/meteorological WSC characteristics and the original data quality improvement for WSC calculation are rarely carried out. This paper reviews and redefines the concept and connotation of spatial, time and meteorological WSC. On this basis, a general process is proposed for WSC calculation including data classification, extraction and cleaning. Then the WSC characteristics between wind turbines are analyzed from time and meteorological dimensions based on the actual operation data. In addition, the influence of time WSC and meteorological WSC on wind turbine equivalent modeling and wind power prediction was discussed. The results of case study shows that the proposed general WSC calculation process is feasible and effective; the WSC for different time scales, wind speed ranges and wind directions varies greatly; the spatial WSC cannot characterize the time variability and directionality of the WSC. And the time and meteorological WSC characteristics are of great engineering value to improve the wind turbine equivalent modeling and wind power prediction accuracy, the influence of time scale and meteorological conditions should be considered in the applications of WSC.

Application of gray relational analysis to k-means clustering for dynamic equivalent modeling of wind farm

Considering the characteristics of dynamic gray correlation among operational conditions of wind turbines, an innovative clustering method for dynamic equivalent modeling of wind farms (WFs) based on the dynamic gray cluster algorithm is proposed. The proposed method is used to determine the number and composition of equivalent wind turbine (WT) groups that can be used to represent a WF. Based on an analysis of auto-correlation coefficients among the various monitoring items of a supervisory control and data acquisition (SCADA) system for a WT, the time span of clustering samples is determined. Then, a correlation matrix of the clustering samples is constructed by using the dynamic gray relational analysis method. Finally, WTs are divided into groups by analyzing the abovementioned correlation matrix by using the k-means clustering algorithm, and WTs belonging to the same group are considered equivalent to one turbine to realize dynamic equivalent modeling of WFs. The method is demonstrated on a WF comprising 22 WTs connected to an IEEE 39 bus test system. Dynamic responses of the proposed model for the WF are compared against the response of the detailed model and other models for various scenarios. The comparison results show that the proposed dynamic equivalent model can describe the dynamic response characteristics of a WF with accuracy similar to that of the detailed model, and the proposed model is simpler and has lower computational complexity.

On the Efficient Calculation of the Periodic Steady-State Response of Grid-Connected Wind Parks—Part I

This paper presents a new power systems simulation environment suitable for the swift calculation of the periodic steady-state response of large power networks with large wind parks. In order to achieve the greatest computational efficiency and solution reliability, the wind generator model uses the state-of-the-art voltage-behind-reactance model of the induction generator; in this first part of the paper, the fixed-speed wind generator model is presented. The overall solving environment for the nonlinear system of differential equations representing the power system is the so-called Poincare map method. A rather useful feature to reduce further the calculation times is the availability of an equivalent wind farm model based on multiple wakes. The Poincare acceleration yields a vastly improved numerical solution compared to existing models of fixed-speed wind parks. The application of equivalent wind farm models yields a staggering reduction in the elapsed time to only 1.16% of the time demanded by the detailed model, while retaining a good approximation of the response of the wind farm. Full comparisons of the detailed and equivalent wind park models with PSCAD/EMTDC, are carried out and the agreement of the results is excellent. In this paper the emphasis is on harmonic generation.

Dynamic equivalent modeling of wind farm considering the uncertainty of wind power prediction and a case study

Currently, the clustering of dynamic multi-machine equivalent modeling of wind farm (WF) is based on the deterministic data. To serve the early warning calculation of power system dispatch better, a dynamic multi-machine equivalent modeling method of WF considering the uncertainty of wind power prediction is first proposed in this paper. First, the probability density functions of wind speed and wind power prediction errors are described and the multi-scenario sampling method is adopted to reflect the uncertainty. Second, the probabilistic clustering method is used to obtain the probability of each wind turbine generator (WTG) belonging to each cluster. The cluster with the biggest probability is selected as the clustering result of the WTGs in the spirit of the Bayesian classification. Third, the WTGs and collector system are simplified into a single-machine equivalent model in each cluster. Finally, the WF output response curve is compared among the detailed WF models, the conventional and the proposed equivalent models in the accurate and inaccurate scenarios of wind power prediction, respectively. The results show that the proposed equivalent method considers the uncertainty in reality and has a better accuracy in the inaccurate scenario of wind power prediction.

A Fuzzy Clustering Algorithm-Based Dynamic Equivalent Modeling Method for Wind Farm With DFIG

With the increasing capacity of grid connected wind farms, the influence of wind power to stable operation of an electric power system is becoming more and more important. In order to analyze the active power output characteristics of wind farm, a multimachine representation dynamic equivalent method based on the fuzzy clustering algorithm is proposed. First, indicators which can characterize the active power output performance of a doubly fed induction wind generator (DFIG) are researched. Second, a fuzzy C-means (FCM) clustering algorithm is first applied to the modeling of wind farm. DFIGs are divided into groups by analyzing the indicator data with FCM. Finally, DFIGs of the same group are equivalent as one DFIG to realize the dynamic equivalent modeling of wind farm with DFIG. Simulation results demonstrated that the established dynamic equivalent model can reflect the active power dynamic response characteristics of wind farm with DFIG effectively; meanwhile, the model of wind farm is simplified and computation complexity is reduced.

Probabilistic equivalent model of DFIG-based wind farms and its application in stability analysis

A probabilistic equivalent method for doubly fed induction generator (DFIG) based wind farms is proposed in this paper. First, the wind farm equivalent model is assumed to be composed of three types of equivalent DFIGs with different dynamic characteristics. The structure of equivalent model remains constant, whereas the parameters change with the migration of different scenarios in the wind farm. Then, historical meteorological data are utilized to investigate the probability distribution of key equivalent parameters, such as capacity, wind speed and electrical impedance to the point of common coupling. Each type of equivalent DFIG is further clustered into several groups according to their active power output. Combinations are created to generate representative scenarios. The probabilistic equivalent model of wind farm is finally achieved after removing invalid combinations. Most matched representative scenarios can be predicted according to the real-time measurement. The equivalent model is applied to the probabilistic power flow calculation and the stability analysis of test systems.

Equivalent Modeling of Double-fed Wind Farm Based on Flow Field Characteristics

The entire wind farm is regarded as a large-capacity wind turbine for modeling double-fed wind farm. The influence of flow field characteristics in the wind farm has been ignored. In order to reflect the influence in double-fed wind farm equivalent modeling, an equivalent modeling method of double-fed wind farm based on the flow field characteristics has been proposed. A calculation model of the double-fed wind farm flow field has been built considering the influence of terrain and wake. The wind speed was calculated at each wind turbine installed point based on the flow field calculation model, and using the wind speed as the input wind speed for each wind turbine, the dynamic characteristics of the wind farm production process has been studied. The simulation analysis has been done for the proposed modeling method, and the simulation results show that the proposed modeling method can reflects the dynamic characteristics of the wind farm production process more accurately.

Modelling Wind Farm with Doubly Fed Induction Generators Based on Characteristic Fusion

In this paper, a novel modelling approach based on characteristic fusion is proposed and used to build a static equivalent model of wind farm. Firstly, the modelling framework based on characteristic fusion is given. Secondly, the basic characteristics of wind farm including characteristic of wind turbine generator (WTG), wind speed spatial distribution and characteristic of wind farm are analyzed according to the framework. Then detailed modelling process is provided utilizing SVR as a fusion tool. This approach combines the advantages of both mechanism and non-mechanism methods with both satisfactory fitting ability and generalization ability. It only requires the maximum and minimum value of wind speed among the wind farm, rather than accurate wake model as mechanism method nor massive measurement data as non-mechanism method. Numerical simulation indicates the effectiveness and robustness of the proposed method. When available data is reduced or includes bad measurement, the proposed method can still keep favorable performance.

The Impact of the Offshore Wind Farm Switching Transient Operation on Power System

In this paper, a practical method to establish Doubly Fed Induction Generator (DFIG) based wind farm equivalent model for switching transient analysis is demonstrated. In order to verify this method, a 3.6MW equivalent wind farm model is built. The steady state results and load switching results are verified with those of detailed models of four 0.9MW generators. Using this method, a model of 40MW wind farm, representing the capacity for a proposed South Carolina offshore wind farm is established. To study large wind farm switching transient impacts on a system, different switching operations such as cable energizing and three phase faults at different locations in wind farm are investigated and their impact on system are analysed. Finally, conclusions based on the switching cases are presented.

Reliability Assessment of Wind Power System Considering Multi-Objective Models

The integration of wind farms has a significant impact on the power system reliability. An appropriate model used to assess wind power system reliability is needed. Establishing multi-objective models (wind speed model, wind turbine generator output model and wind farm equivalent model) and based on the non-sequential Monte Carlo simulation method to calculate risk indicators is a viable method for quantitatively assessing the reliability of power system including wind farms. The IEEE-RTS 79 test system and a 300MW wind farm are taken as example.The calculation resluts show that using the multi-objective models can improve accuracy and reduce error; the higher average wind speed obtains the better system reliabitity accordingly.

Wind Farm Equivalent Modeling Based on Eigen Analysis

The increasing size of wind power generation requires considering wind farm model in power system stability analysis. Nowadays, the most widely used wind turbine type is doubly-fed induction generator, which is concerned here. The wind farm detailed model including every individual DFIG is high-dimensional and costs a lot of computation time, thus wind farm equivalent model is required. This paper presents an eigen analysis based approach to settle wind farm equivalent modeling for power system simulation. Simulation results indicate the equivalent model has good accuracy, and can reflect wind farm features, which is proper for large-scale power system simulation.

A Coherency-Based Equivalent Model of a Large Scale Wind Farm

With increasing installation capacity and wind farms penetration, wind power plays more important role in power systems, and the modeling of wind farms has become an interesting research topic. In this paper, a coherency-based equivalent model has been discussed for the doubly fed induction generator (DFIG). Firstly, the dynamic models of wind turbines, DFIG and the mechanisms are briefly introduced. Some existing dynamic equivalent methods such as equivalent wind model, variable speed wind turbine model, parameter identification method and modal equivalent method to be used in wind farm aggregation are discussed. Then, considering wind power fluctuations, a new equivalent model of a wind farm equipped with doubly-fed induction generators is proposed to represent the interactions of the wind farm and grid. The method proposed is based on aggregating the coherent group wind turbines into an equivalent one. Finally, the effectiveness of the equivalent model is demonstrated by comparison with the wind farm response obtained from the detailed model. The dynamic simulations show that the present model can greatly reduce the computation time and model complexity.

Aggregated dynamic model for wind farms with doubly fed induction generator wind turbines

As a result of increasing wind farms penetration in power systems, the wind farms begin to influence power system, and thus the modelling of wind farms has become an interesting research topic. Nowadays, doubly fed induction generator based on wind turbine is the most widely used technology for wind farms due to its main advantages such as high-energy efficiency and controllability, and improved power quality. When the impact of a wind farm on power systems is studied, the behavior of the wind farm at the point common coupling to grid can be represented by an equivalent model derived from the aggregation of wind turbines into an equivalent wind turbine, instead of the complete model including the modelling of all the wind turbines. In this paper, a new equivalent model of wind farms with doubly fed induction generator wind turbines is proposed to represent the collective response of the wind farm by one single equivalent wind turbine, even although the aggregated wind turbines operate receiving different incoming winds. The effectiveness of the equivalent model to represent the collective response of the wind farm is demonstrated by comparing the simulation results of equivalent and complete models both during normal operation and grid disturbances.