• Journal of Wind Energy
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• v.3 no.2
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• pp.34-41
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• 2012

The paper is focusing on investigating the control characteristics of the baseline controller of 5 MW wind turbine provided by NREL(National Renewable Energy Laboratory). The baseline controller consist of two control logics, a maximum power tracking control below the rated wind speed and a constant power control above the rated wind speed. In the low wind speed, the mean generator power for changing the turbulent intensity and the optimal constant is studied through numerical simulations using FAST program. On the other hand, the constant power control logic and the constant control logic are compared in the high wind speed. It is confirmed that optimal constant is closely related to the turbulent intensity in low wind speed region and the constant torque control has better performance than the constant power control with respect to mechanical load in high wind speed region.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1358-1360
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• 2002

This paper presents a modeling and simulation of a utility-connected wind energy conversion system with a link of a rectifier and an inverter. It discusses the maximum power control algorithm for the wind turbine and presents the relationship of wind turbine output, rotor speed, power coefficient, tip-speed ratio and wind speed when the wind turbine is operated under the maximum power control algorithm. The control objective is to extract maximum power from wind and transfer the power to the utility. This is achieved by controlling the pitch angle of the wind turbine blades. Pitch control method is mechanically complicated, but the control performance is better than that of the stall regulation method. The simulation results performed on MATLAB will show the variation of generator's rotor speed, pitch angle, and generator output.

• Wind and Structures
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• v.26 no.3
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2268-2277
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• 2017

As constantly increasing wind power penetrates power grid, wind power plants (WPPs) are exerting a direct influence on the traditional power system. Most of WPPs are using variable speed constant frequency (VSCF) wind turbines equipped with doubly fed induction generators (DFIGs) due to their high efficiency over other wind turbine generators (WTGs). Therefore, the analysis of DFIG has attracted considerable attention. Precisely measuring optimum reference speed is basis of utilized maximum wind power in electric power generation. If the measurement of wind speed can be easily taken, the reference of rotation speed can be easily calculated by known system's parameters. However, considering the varying wind speed at different locations of blade, the turbulence and tower shadow also increase the difficulty of its measurement. The aim of this study is to design fuzzy controllers to replace the wind speedometer to track the optimum generator speed based on the errors of generator output power and rotation speed in varying wind speed. Besides, this paper proposes the fuzzy adaptive PID control to replace traditional PID control under rated wind speed in variable-pitch wind turbine, which can detect and analyze important aspects, such as unforeseeable conditions, parameters delay and interference in the control process, and conducts online optimal adjustment of PID parameters to fulfill the requirement of variable pitch control system.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.288-293
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• 2008

A predictive model of wind speed in the wind farm has very important meanings. This paper presents an estimation model of wind speed based on time series analysis using the observed wind data at Hangyeong Wind Farm in Jeju island, and verification of the predictive model. In case of Hangyeong Wind Farm and Haengwon Wind Farm, The ARIMA(Autoregressive Integrated Moving Average) predictive model was appropriate, and the wind speed estimation model was developed by means of parametric estimation using Maximum likelihood Estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.92-99
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• 2016

A wind turbine is controlled for the purpose of obtaining the maximum power below its rated wind speed. Among the methods of obtaining the maximum power, TSR (Tip Speed Ratio) optimal control and P&O (Perturbation and Observation) control are widely used. The P&O control algorithm using the turbine power and rotational speed is simple, but its slow response is a weak point. Whereas TSR control's response is fast, it requires the precise wind speed. A method of measuring or estimating the wind speed is used to obtain a precise value. However, estimation methods are mostly used, because it is difficult to avoid the blade interference when measuring the wind speed near the blades. Neural networks and various numerical methods have been applied for estimating the wind speed, because it involves an inverse problem. However, estimating the wind speed is still a difficult problem, even with these methods. In this paper, a new method is introduced to estimate the wind speed in the wind-power graph by using the turbine power and rotational speed. Matlab/Simulink is used to confirm that the proposed method can estimate the wind speed properly to obtain the maximum power.

• Journal of the Korean Society of Safety
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• v.33 no.1
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• pp.103-108
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• 2018

Since tower cranes are susceptible to wind loads, the operation of the tower crane should be ceased when it exposed to a strong wind. For this reason, even in Korea, the operation limit for wind loading on the tower crane is regulated by a law. Recently the Korean law in which provided the wind speed limit to cease the tower crane operation has been revised from "instantaneous wind speed of 20 m/s" to "instantaneous wind speed of 15 m/s". Although this revision is expected to reduce safety risks in tower crane operation, some field operators still insist to lower the wind speed limit. However, in many countries "wind speed of 20 m/s" is normally used as the maximum in-service wind speed for tower cranes. Therefore, the investigation of the proper wind speed for regulation would be helpful to secure the safety of the tower crane operation under windy condition. In this study the validity of the revised wind speed limit is investigated with the surveys targeted to both tower crane practitioners and parties of concerned in construction companies, in which various questions was provided for a suitable wind speed limit and the answers were analyzed. The results showed that the revised wind speed limit is acceptable to tower crane practitioners as well as the parties of concerned in construction companies and is satisfying the structural stability requirement for in-service state tower crane. Therefore, it can be concluded that the revised wind speed limit is valid in humanly safety point of view.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.852-857
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• 2010

As the wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is on how to efficiently operate the wind turbines in a wide range of wind speeds. In general, the wind speed is the main factor that impact on the dynamics of wind turbine system. Wind turbine algorithms are thus required to improve the performance of wind speed measurements. However, the accurate measurement of the effective wind speed using wind gauge and similar sensors is difficult such that control systems are needed for wind speed estimation using various techniques. Therefore, this research suggests the Maximum Power Point Tracking (MPPT) method for tracking the wind speed based on neural networks. Design experiments were carried out in laboratory environment to validate the application of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.327-333
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• 2015

Wind turbines, in the case of less than rated wind speed, is controlled to achieve maximum power. MPC(Maximun Power Control) method, by controlling the rotational speed of the generator, is a method to achieve maximum power but should know the wind speed. However, for several reasons, there have been proposed methods of estimating the wind speed rather than measuring wind speed. TSR(Tip Speed Ratio) is needed to know to estimate the wind speed. However, a complex interaction formula has to be solved to find a TSR. Therefore, many methods have been suggested to solve a complex interaction formula. In this paper, the new method has been proposed to simplify the complicated interaction formula by using the regression method. Matlab/Simulink is used to simulate and to verify the proposed method.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.650-655
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• 2001

Wind speeds can vary rapidly and wind turbines cannot easily follow these variations because of their inertia and aerodynamic characteristics. For maximum energy extraction. the turbine blades should operate at their optimum tip speed ratio, but with rapid changes in wind speed. this is usually not possible. To improve the energy extraction from turbulent wind, it is necessary to establish an effective measure of the high frequency component of the wind. and then to use this measure to optimise the operation of the turbine controller for maximum energy extraction. This paper presents an approach for combining readings from three anemometers into a composite wind speed measurement. and using this signal to control the operation of a permanent magnet generator to achieve maximum energy extraction. The method combines simulation and experimental investigations into a heuristic algorithm. and demonstrates its effectiveness with field trials.