Real Wind Speed Research Articles

Wind Turbine Simulator Development Using a Separately Excited DC Motor

Abstract This paper proposes a new wind turbine simulator using a separately-excited DC motor for both steady state and transient conditions. The turbine torque is modeled as a function of the wind speed and the blade pitch angle. The effect of the tower shadow and wind shear is included in the turbine torque. To produce the realistic wind speed, a wind speed simulator is designed, too. The wind speed profile is developed as a sum of deterministic component and the stochastic component which composed of a sum of harmonics with wide range frequencies. The dynamic aspects such as wind speed simulator, wind shear, tower shadow and pitch angle control are modeled and implemented experimentally.

Forecasting storms over Lake Victoria using a high resolution model

Lake Victoria in East Africa is one of the world's largest freshwater lakes and is used on a daily basis by thousands of fishermen. Each year, severe storms on the lake cause multiple boating accidents which often result in fatalities. Recent initiatives have seen an effort to reduce accidents by issuing storm warnings when severe weather is expected. Here the Met Office global Unified Model is evaluated along with a 4 km limited-area model which has been set up to assist forecasters in the region to issue these warnings. Findings indicate the 4 km model is capable of producing more realistic strong wind speeds and rain rates than the global model. Case studies relating to fatal boating accidents on 1 March and 4 March 2012, showed improved warning signals of severe storms in the 4 km model compared to the global model. Objective comparisons between model and observations were conducted on 2 months of data. An objective method was used to determine ‘storm’/‘no storm’ in the model forecasts. These were then compared against cloud top temperature from IR satellite and lightning data from the arrival time difference (ATD) radio ground network to determine whether each model was successful at forecasting storm/calm events. The 4 km model was able to capture more storm hits (thus had fewer storm misses), but also gained more false alarm events. Overall, the objective analysis showed that both models had some predictive skill and both were an improvement on a persistence forecast.

Design and Control HVDC of Connected Wind Power Plant

This paper presents the design and control of HVDC connected wind power plant. Wind power plant composed of variable wind turbine with double fed induction generator (DFIG). In this paper HVDC system is designed using hybrid multilevel voltage source converter (VSC) with VSC based HVDC system provides the operational flexibility in terms of active and reactive power control, improved ac fault ride through capability and current limiting capability during fault. To illustrate the feasibility of the proposed system both steady state and dynamic analyses are performed and the control is implemented using closed loop PI controller. Real wind speed data is used in this simulation study. The model for the design and control of this system is simulated using MATLAB- Simulink.

Mitigation of Load Frequency Fluctuation Using a Centralized Pitch Angle Control of Wind Turbines

In this paper an application of centralized pitch angle controller for fixed speed wind turbines based wind farm to mitigate load frequency fluctuation is presented. Reference signal for the pitch angle of each wind turbine is calculated by using proposed centralized control system based on wind speed information. The wind farm in the model system is connected to a multi machine power system which is composed of 4 synchronous generators and a load. Simulation analyses have been carried out to investigate the performance of the controller using real wind speed data. It is concluded that the load frequency of the system can be controlled smoothly.

Neural MPPT of Variable-Pitch Wind Generators With Induction Machines in a Wide Wind Speed Range

This paper proposes a maximum power point tracking (MPPT) technique for variable-pitch wind generators with induction machines (IMs), which can suitably be adopted in both the maximum power range and the constant-power range of the wind speed. To this aim, an MPPT technique based on the growing neural gas (GNG) wind turbine surface identification and corresponding function inversion has been adopted here to cover also the situation of variable-power region. To cope with the constant-power region, the blade pitch angle has been controlled on the basis of the closed-loop control of the mechanical power absorbed by the IM. The wind speed is then estimated in the constant-power region on the basis of the actual position of the blade pitch angle. The proposed methodology has been verified both in numerical simulation and experimentally on a properly devised test setup. In addition, a comparison between the proposed approach and the previously developed GNG-based MPPT has been performed on a real wind speed profile. Finally, the effect of the torsional stiffness of the mechanical transmission system has been analyzed.

Empirical investigation on using wind speed volatility to estimate the operation probability and power output of wind turbines

In this paper, we introduce a quantitative methodology that performs the interval estimation of wind speed, calculates the operation probability of wind turbine, and forecasts the wind power output. The technological advantage of this methodology stems from the empowered capability of mean and volatility forecasting of wind speed. Based on the real wind speed and corresponding wind power output data from an offshore wind turbine, this methodology is applied to build an ARMA–GARCH-M model for wind speed forecasting, and then to compute the operation probability and the expected power output of the wind turbine. The results show that the developed methodology is effective, the obtained interval estimation of wind speed is reliable, and the forecasted operation probability and expected wind power output of the wind turbine are accurate.

Quantum-Inspired Particle Swarm Optimization for Power System Operations Considering Wind Power Uncertainty and Carbon Tax in Australia

In this paper, a computational framework for integrating wind power uncertainty and carbon tax in economic dispatch (ED) model is developed. The probability of stochastic wind power based on nonlinear wind power curve and Weibull distribution is included in the model. In order to solve the revised dispatch strategy, quantum-inspired particle swarm optimization (QPSO) is also adopted, which shows stronger search ability and quicker convergence speed. The dispatch model is tested on a modified IEEE benchmark system involving six thermal units and two wind farms using the real wind speed data obtained from two meteorological stations in Australia.

Reduction of frequency fluctuation for wind farm connected power systems by an adaptive artificial neural network controlled energy capacitor system

Frequency fluctuations are a major concern for transmission system operators and power grid companies from the beginning of power system operation due to their adverse effects on modern computer-controlled industrial systems. Because of the huge integration of wind power into the power grid, frequency fluctuations are becoming a serious problem, where randomly varying wind power causes the grid frequency fluctuations of the power system. Therefore, in this paper, the minimisation of the frequency fluctuation of a power system, including a wind farm, is proposed using an energy capacitor system (ECS). A scaled-down, multi-machine power system model from Hokkaido prefecture, Japan, is considered for the analysis. A novel adaptive artificial neural network (ANN) controller is considered for controlling the DC-bus connected ECS. The control objective is to standardise the line power of the wind farm, taking into consideration the frequency deviation. The effects of wind power penetration levels, as well as load variations, are also analysed. The proposed control method is verified by simulation analysis, which is performed with PSCAD/EMTDC using real wind speed data. The adaptive ANN-controlled ECS was found to be an effective means of diminishing the frequency fluctuation of multi-machine power systems with connected wind farms.

Dynamic wind turbine output power reduction under varying wind speed conditions due to inertia

ABSTRACTThe inertia of wind turbines causes a reduction in their output power due to their inability to operate at the turbine maximum co‐efficient of performance point under dynamic wind conditions. In this paper, this dynamic power reduction is studied analytically and using simulations, assuming that a steady‐state optimal torque control strategy is used.The concepts of the natural and actual turbine time‐constant are introduced, and typical values for these parameters are examined. It is shown that for the typical turbine co‐efficient of performance curve used, the average turbine speed can be assumed to be determined by the average wind speed. With this assumption, analytical expressions for the power reduction with infinite and then finite turbine inertia are determined for sine‐wave wind speed variations. The results are then generalized for arbitrary wind speed profiles.A numerical wind turbine system simulation model is used to validate the analytical results for step and sine‐wave wind speed variations. Finally, it is used with real wind speed data to compare with the analytical predictions. Copyright © 2012 John Wiley & Sons, Ltd.

Growing Neural Gas-Based MPPT of Variable Pitch Wind Generators With Induction Machines

This paper proposes a maximum power point tracking (MPPT) technique for variable pitch wind generators with induction machines, which can suitably be adopted in both the maximum power range and the constant power range of the wind speed. For this purpose, an MPPT technique based on the growing neural gas (GNG) wind turbine surface identification and the corresponding function inversion has been adopted to cover also the situation of constant rated power region. This has been obtained by including the blade pitch angle in the space of the data learnt by the GNG and feeding back the estimated wind speed to compute the correct value of the pitch angle, which permits the machine to work at rated power and torque. A further enhancement of the pitch angle selection by a simple perturb & observe method has been added to cope with slight wind estimation errors occurring at machine rated speed. The proposed methodology has been verified both in numerical simulation and experimentally on a properly devised test setup. The correct behavior of the system has been proved also on a real wind speed profile on a daily scale.

Effects of time-varying sea surface in marine seismic data

A method of imaging sea surfaces based on marine seismic measurements has recently been developed. The imaging technique is based on extrapolating decomposed wavefields obtained from dual-sensor streamers to the sea surface where an adequate imaging condition is applied. Earlier feasibility tests of the method involved only controlled data associated with frozen sea surfaces. Here, the issue of time-varying effects will be in focus. We introduced a modeling approach based on the Kirchhoff-Helmholtz integral and computed the scattered wavefield from time-varying rough sea surfaces (e.g., Pierson-Moskowitz sea surfaces). We generated data for a realistic wind speed and verify the robustness of the proposed sea surface imaging technique by taking into account possible effects of moving receivers as well as streamers with variable shape. We investigate the feasibility of estimating the surface wave velocity from the spectra of the imaged sea surfaces and finally present a successful application of the sea surface imaging technique to data from the North Sea.

Complete methodology on generating realistic wind speed profiles based on measurements

Complete methodology on generating realistic wind speed profiles based on measurements

Penetration impact of wind farms equipped with frequency variations ride through algorithm on power system frequency response

Focus of power system engineers is currently directed to the impact of wind power on system frequency. Research efforts concentrate on the ability of wind farms to contribute in the frequency droop events by injecting active power to the grid. This paper presents a detailed analysis for the effect of wind farm connection to a certain power system on the system frequency response. Most of wind farm parameters were considered, namely, the actual wind speeds, wake effects inside the wind farm, the different arrangements of wind turbines inside the wind farm and pitch control mechanism. Moreover, the major data of a h power system were included; different conventional generation technologies and their suitable speed governors. In addition, instant dynamic load variations were implemented. Five case studies were conducted through this system to test the system frequency attitude during normal operation and in case of sudden and large load changes. Three basic values are used to estimate the mentioned impact; the time needed to reach the safe margin after a certain droop, the RMS value of frequency deviation after the fault initiation by a given fixed time span and the maximum frequency drop for each event. All the previously stated studies are performed using MATLAB and Simulink simulations depending on real wind speeds data.

Power Regulation of Variable Speed Wind Turbines using Pitch Control based on Disturbance Observer

Most variable speed wind turbines have pitch control mechanisms and one of their objectives is to protect turbines when the wind speed is too high. By adjusting pitch angles of wind turbine, the inlet power and the torque developed by the turbine are regulated. In this paper, the difference between the real wind speed and its rated value is regarded as a disturbance, and a component called disturbance observer (DOB) is added to the pre-designed control loop. The additional DOB based controller estimates the disturbance and generates a compensating signal to suppress the effect of disturbance on the system. As a result, the stability and the performance of the closed loop system guaranteed by an outer-loop controller (designed for a nominal system without taking into account of disturbances) are approximately recovered in the steady state. Simulation results are presented to verify the performance of the proposed control scheme.

Stabilization of Power System Including Wind Farm by PWM Voltage Source Converter and Chopper Controlled SMES

This paper presents a dynamic model of Superconducting Magnetic Energy Storage (SMES) device developed, which can significantly decrease the voltage and power fluctuations of grid connected fixed speed wind generators. The SMES system with a voltage–source IGBT converter and two–quadrant DC–DC chopper is analyzed as a controllable energy source. The objective of the proposed SMES control strategy is to smooth the wind farm output by absorbing or providing real power. Moreover, its reactive power output can also be controlled to keep the wind farm terminal voltage constant. The control methodology of SMES system is suitable for the two objectives stated above. The performance of the proposed system is evaluated by dynamic simulations using a test power system. Real wind speed data is used in the simulation analyses, which validates the effectiveness of the proposed control strategy. Simulation results clearly show that the proposed control strategy can smooth well the wind generator output power and also maintain the terminal voltage at rated level. Key words: Minimization of fluctuations; superconducting magnetic energy storage (SMES); wind generator stabilization; voltage source converter (VSC); DC–DC chopper

Wind Turbine Building for Saving Home Electricity

This paper presents design and building wind energy system. Even though, wind power is not popular in Iraq but it is widely used in other countries. Nowadays, our electricity bill always increases every year cause of increasing fuel and generation price. This paper will discuss about small wind energy system construction and building to save our home electricity. Building small wind turbine as alternative to reduce our electricity bill every months, and also compensate the poor of electricity provided from national grid. This system will use home inverter with battery storage, three blades small wind turbine and wiring. If the wind speeds at our area are high to generate enough power, we will supply that power from home inverter that use storage energy in battery that provided from wind turbine to low electrical equipment such as lighting, wireless gateway and more. Also install this home small wind system and make study on it by using real wind speed data inIraq in Najaf city. For providing electricity use permanent magnet DC generator connected to three blade wind turbine constructed on 1.8 m tower practically build as the wind energy system.

Estimation of Effective Wind Speed for Fixed-Speed Wind Turbines Based on Frequency Domain Data Fusion

The rotator of the wind turbine is subject to a spatially and temporally distributed wind field; the wind speed varies significantly at different points over the blades plane. This makes a direct measurement of effective wind speed impossible. We analyze the spectrums of the measurement of the anemometer and generator power of a wind turbine, and point out that the characteristics of these two signals are complementary in the frequency domain. Then an observer for effective wind speed is proposed based on frequency-domain data fusion. The observer design is formulated as a mixed-sensitivity problem with linear matrix inequalities (LMIs). Simulations were carried out to assess the performance under a realistic wind speed profile. The simulation results show that the observer can not only guarantee the static accuracy, but also improve the dynamic accuracy of the measurements of the effective wind.

Speed control of grid-connected switched reluctance generator driven by variable speed wind turbine using adaptive neural network controller

In wind energy conversion system, variable speed operation is becoming popular nowadays, where conventional synchronous generators, permanent magnet synchronous generators, and doubly fed induction generators are commercially used as wind generators. Along with the existing and classical solutions of the aforementioned machines used in wind power applications, the switched reluctance generator (SRG) can also be considered as a wind generator due to its inherent characteristics such as simple construction, robustness, low manufacturing cost, etc. This paper presents a novel speed control of switched reluctance generator by using adaptive neural network (ANN) controller. The SRG is driven by variable speed wind turbine and it is connected to the grid through an asymmetric half bridge converter, DC-link, and DC–AC inverter system. Speed control is very important for variable speed operation of SRG to ensure maximum power delivery to the grid for any particular wind speed. Detailed modeling and control strategies of SRG as well as other individual components including wind turbine, converter, and inverter systems are presented. The effectiveness of the proposed system is verified with simulation results using the real wind speed data measured at Hokkaido Island, Japan. The dynamic simulation study is carried out using PSCAD/EMTDC.

Modeling wind energy flux by a Birnbaum–Saunders distribution with an unknown shift parameter

In this paper, we discuss a Birnbaum–Saunders distribution with an unknown shift parameter and apply it to wind energy modeling. We describe structural aspects of this distribution including properties, moments, mode and hazard and shape analyses. We also discuss estimation, goodness of fit and diagnostic methods for this distribution. A computational implementation in R language of the obtained results is provided. Finally, we apply such results to two unpublished real wind speed data from Chile, which allows us to show the characteristics of this statistical distribution and to model wind energy flux.

Smoothing Control of Wind Farm Output Fluctuations by Fuzzy Logic Controlled SMES

Due to random variations of wind speed, the output power and terminal voltage of a fixed speed wind generator fluctuate continuously. These irregularities in power output are affecting both the power quality and reliability. It is reported that STATCOM/SMES (Superconducting Magnetic Energy Storage) system can significantly decrease voltage and output power fluctuations of grid connected fixed speed wind generator. But the main problem in wind generator output power smoothing is the choice of the reference output power, because it corresponds to energy storage capacity. The storage capacity of SMES that is sufficient for the smoothing control but as small as possible is very important, considering cost effectiveness. In this paper, a fuzzy logic controlled STATCOM/SMES system is proposed, in which both SMA (Simple Moving Average) and EMA (Exponential Moving Average) are used to generate output power reference. Real wind speed data are used in the simulation analyses, which validate the effectiveness of the proposed control strategy. Simulation results clearly show that the proposed STATCOM/SMES system can smooth well the wind generator output power and also maintain the terminal voltage at rated level in both cases when SMA or EMA is used to generate output reference power. Finally, it is shown that reference output power generated by EMA provides better performance with reduced SMES storage capacity than that of output power generated by SMA. Keywords: Minimization of fluctuations, fixed speed wind generator, STATCOM/SMES, simple moving average (SMA) and exponential moving average (EMA), and wind farm (WF). DOI: http://dx.doi.org/10.11591/ijece.v1i2.181