• Journal of Energy Engineering
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• v.11 no.3
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• pp.216-223
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• 2002

Generation facilities of the power system are mainly classified into large-scale concentrated generation and small-scale dispersed generation, but generation planning of the Korea power system has been focusing on the large-scale generation so far. Recently, however, applications of dispersed generation sources including solar cell, fuel cell, wind power, etc. have been rapidly increasing and being strongly promoted, and such generation sources should be comprehensively considered in both planning and operating. Since it is not always possible that the dispersed generation alone meets all the load interconnected to it is especially when a fault occurs, interconnection into the existing utility is desirable and recommended. In relation to wind power generation systems interconnected at the low and extra high voltage levels, this paper performs the simulation and analysis of the system protection and suggests protection coordination plans on various faults which possibly occur.

• Wind and Structures
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• v.13 no.4
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• pp.375-383
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• 2010

A three-dimensional flow simulation was performed to investigate the wind flow around wind-power generation facilities on mountainous area of complex terrain. A digital map of eastern mountainous area of Korea including a wind farm was used to model actual complex terrain. Rotating wind turbines in the wind farm were also modeled in the computational domain with detailed geometry of blade by using the frozen rotor method. Wind direction and speed to be used as a boundary condition were taken from local meteorological reports. The numerical results showed not only details of flow distribution in the wind farm but also the variation in the performance of the wind turbines due to the installed location of the turbines on complex terrain. The wake effect of the upstream turbine on the performance of the downstream one was also examined. The methodology presented in this study may be used in selecting future wind farm site and wind turbine locations in the selected site for possible maximum power generation.

• Journal of Wind Energy
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• v.14 no.1
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• pp.37-43
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• 2023

In this study, synthetic time series wind data was generated numerically using a second-order Markov chain. One year of wind data in 2020 measured by the AWS on Wido Island was used to investigate the statistics for measured wind data. Both the transition probability matrix and the cumulative transition probability matrix for annual hourly mean wind speed were obtained through statistical analysis. Probability density distribution along the wind speed and autocorrelation according to time were compared with the first- and the second-order Markov chains with various lengths of time series wind data. Probability density distributions for measured wind data and synthetic wind data using the first- and the second-order Markov chains were also compared to each other. For the case of the second-order Markov chain, some improvement of the autocorrelation was verified. It turns out that the autocorrelation converges to zero according to increasing the wind speed when the data size is sufficiently large. The generation of artificial wind data is expected to be useful as input data for virtual digital twin wind turbines.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.854-859
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• 2007

A wind farm consists of many wind generator(WG)s therefore, it is generally a complex power system. A wind farm as a distributed generation(DG) affects utility power system. If a conventional protection schemes are applied, it is difficult to detect faults correctly and the schemes can't provide proper coordination in some cases. This paper presents a protection algorithm for a wind farm which consists of a looped collection circuit. Because the proposed algorithm can distinguish between an internal fault and an external fault in a wind farm, The proposed algorithm can disconnect the faulted section in a wind farm. This algorithm is based on an overcurrent protection technique with the change of the ratio of the output current of a generator to the current of the looped line connected to each generator to collect the each generator's power. In addition, operating time of the algorithm is shortened by using the voltage drop at a generator collection point. The performance of the proposed algorithm was verified under various fault conditions using PSCAD/EMTDC simulations.

• Proceedings of the KIEE Conference
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• summer
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• pp.236-238
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• 2004

In recent years wind turbine technology has undergone the rapid development in response to the demands for increased use of renewable sources of energy. Using wind turbines for production of electrical energy requires reliable operation. The increased share of wind power in electrical system makes it necessary to have grid-friendly interfaces between the wind turbines and the grid in order to maintain power quality. Increasingly wind turbines are being connected into electricity distribution system. The grid-connected wind power stations have many impacts on power systems such as voltage variations, harmonics. The paper investigates the influences of grid-connected wind power generation system on substation bus voltage.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.345-347
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• 2006

In this paper, a novel method for wind speed estimation in wind power generation systems is presented. The proposed algorithm is based on estimating the wind speed using Support-Vector-Machines for regression (SVR). The wind speed is estimated using the generator power-speed characteristics as a set of training vectors. SVR is trained off-line to predict a continuos-valued function between the system's inputs and wind speed value. The predicted off-line function as well as the instantaneous generator power and speed are then used to determine the unknown winds speed on-line. The simulation results show that SVR can define the corresponding wind speed rapidly and accurately to determine the optimum generator speed reference for maximum power point tracking.

• Journal of Power Electronics
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• v.8 no.4
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• pp.345-353
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• 2008

In this paper, a novel loss minimization of an induction generator in wind energy generation systems is presented. The proposed algorithm is based on the flux level reduction, for which the generator d-axis current reference is estimated using support vector regression (SVR). Wind speed is employed as an input of the SVR and the samples of the generator d-axis current reference are used as output to train the SVR algorithm off-line. Data samples for wind speed and d-axis current are collected for the training process, which plots a relation of input and output. The predicted off-line function and the instantaneous wind speed are then used to determine the d-axis current reference. It is shown that the effect of loss minimization is more significant at low wind speed and the loss reduction is about to 40% at 4[m/s] wind speed. The validity of the proposed scheme has been verified by experimental results.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.268-270
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• 2005

A tendency to erect more wind turbines can be observed in order to reduce the environmental consequences of electric power generation. As a result of this, in the near future, wind turbines may start to influence the behavior of electric power systems by interacting with conventional generation and loads. Therefore, wind turbine models that can be integrated into power system simulation software are needed. In this paper, a model that can be used to represent all types of variable speed wind turbines in power system simulations is presented. Wind turbine characteristic equation of a wind turbine is implemented in the RTDS, and the real data of weather conditions are interfaced to the RTDS for the purpose of real time simulation of grid-connection wind power system. The outcomes of the simulation demonstrate the effectiveness of the proposed simulation scheme in this paper. The results show that the cost effective verifying for the efficiency and stability of WPGS.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.163-168
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• 2015

In order to integrate high wind generation resources into power grid, it is an essential to predict power outputs of wind generating resources. As wind farm outputs depend on natural wind resources that vary over space and time, spatial modeling based on geographic information such as latitude and longitude is needed to estimate power outputs of wind generation resources. In this paper, we introduce the basic concept of spatial modeling and present the spatial prediction model based on Kriging techniques. The empirical data, wind farm power output in Texas, is considered to verify the proposed prediction model.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.547-554
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• 2018

Wind energy is widely recognized as one of the cheapest forms of clean and renewable energy. In fact, in several countries, wind energy has achieved cost parity with fossil fuel-based sources of electricity generation for new electricity generation plants. Offshore wind energy development promises to be a significant domestic renewable energy source for the target of korea government 3020 plan. A pivotal activity during the development phase of a wind project is wind resource assessment. Several approaches can be categorized as three basic scales or stages of wind resource assessment: preliminary area identification, area wind resource evaluation, and micrositing. This study is to estimate the wind power capacity of chonnam province offshore area using three basic stages based on the six meteorological mast data. WindPRO was used, one of a well-known wind energy prediction programs and based on more than 25 years of experiences in development of software tools for wind energy project development. The design results of offshore wind power generation capacity is calculated as total 2.52GW with six wind farms in chonnam offshore area.