Influences of Wind Shear and Tower Shadow on the Power Output of Wind Turbine

Wen, Bin

doi:10.3901/jme.2018.10.124

Cited by 8 publications

(6 citation statements)

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“…With the increase of rotor diameter and tower height, the spatial fluctuation of wind speed in the wind wheel sweeping plane is becoming more and more obvious due to the influence of wind shear and tower shadow effect [16]. Hence, the influence of wind shear and tower shadow effect should be considered in the calculation of MEWPD in which wind shear is the main cause of power loss, while tower shadow effect is the main cause of power fluctuation, so the power loss caused by tower shadow can be ignored [17]. Therefore, the rotor equivalent wind speed considering wind shear effect is used to replace the hub height wind speed to simplify the calculation.…”

Section: Definitions and Calculation Methods Of Indicator 231 The Ind...mentioning

confidence: 99%

Power Generation Performance Indicators of Wind Farms Including the Influence of Wind Energy Resource Differences

et al. 2022

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The accurate evaluation and fair comparison of wind farms power generation performance is of great significance to the technical transformation and operation and maintenance management of wind farms. However, problems exist in the evaluation indicator systems such as confusion, coupling and broadness, and the influence of wind energy resource differences not being able to be effectively eliminated, which makes it difficult to achieve the fair comparison of power generation performance among different wind farms. Thus, the evaluation indicator system and comprehensive evaluation method of wind farm power generation performance, including the influence of wind energy resource differences, are proposed in this paper to address the problems above, to which some new concepts such as resource conditions, ideal performance, reachable performance, actual performance, and performance loss are introduced in the proposed indicator system; the combination of statistical and comparative indicators are adopted to realize the quantitative evaluation, indicator decoupling, fair comparison, and loss attribution of wind farm power generation performance. The proposed comprehensive evaluation method is based on improved CRITIC (Criteria Importance though Intercrieria Correlation) weighting method, in which the uneven situation of different evaluation indicators and the comprehensive comparison of power generation performance among different wind farms shall be overcome and realized. Several sets of data from Chinese wind farms in service are used to validate the effectiveness and applicability of the proposed method by taking the comprehensive evaluation models based on CRITIC weighting method and entropy weighting method as the benchmarks. The results demonstrated that the proposed evaluation indicator system works in the quantitative evaluation and fair comparison of wind farm design, operation, and maintenance and traces the source of power generation performance loss. In addition, the results of the proposed comprehensive evaluation model are more in line with the actual power generation performance of wind farms and can be applied to the comprehensive evaluation and comparison of power generation performance of different wind farms.

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Section: Definitions and Calculation Methods Of Indicator 231 The Ind...mentioning

confidence: 99%

Power Generation Performance Indicators of Wind Farms Including the Influence of Wind Energy Resource Differences

et al. 2022

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“…The parameters of the WTs simulated in this paper are shown in Table 2, and the simulation is carried out at a rated wind speed of 11 m/s. (19) Equation (17) shows that the fluctuation of electromagnetic torque and electromagnetic power caused by blade mass imbalance fault and equivalent wind speed-including wind shear and tower shadow effect-will appear at 1P, 3P, and 6P; The fluctuation at 1P is caused by the blade mass imbalance, and the fluctuations at 3P and 6P are caused by the equivalent wind speed.…”

Section: Simulation Model and Parametersmentioning

confidence: 99%

“…In [18], the existence of the tower shadow effect and its influence on the output power was verified by analyzing the measured data of the wind farm. In [19], the effects of wind shear and tower shadow effects were studied via both power fluctuation and average output power. They concluded that both wind shear and tower response are sources of periodic power fluctuations and average power loss.…”

Section: Introductionmentioning

confidence: 99%

Characteristic Analysis of DFIG Wind Turbine under Blade Mass Imbalance Fault in View of Wind Speed Spatiotemporal Distribution

et al. 2019

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The blade mass imbalance fault is one of the common faults of the DFIG (Doubly-Fed Induction Generator) wind turbines (WTs). In this paper, considering the spatiotemporal distribution of natural wind speed and the influence of wind shear and tower shadow effect, the influence of blade mass imbalance faults on the electrical characteristics of DFIG WTs is analyzed. Firstly, the analytical expressions and variation characteristics of electromagnetic torque and electromagnetic power under blade mass imbalance are derived before and after consideration of the spatiotemporal distribution of wind speed. Then simulations on the MATLAB/Simulink platform were done to verify the theoretical analysis results. The theoretical analysis and simulation results show that, considering the spatiotemporal distribution of wind speed and the influence of wind shear and tower shadow effect, the blade mass imbalance fault will cause fluctuation at the frequency of 1P (P = the frequency of rotor rotation), 3P, and 6P on electromagnetic power. Fluctuation at 1P is caused by mass imbalance while fluctuation at 3P and 6P are caused by wind speed spatiotemporal distribution; the amplitude of fluctuation at 1P is proportional to the degree of the imbalance fault. Since the equivalent wind speed has been used in this paper instead of the average wind speed, the data is more suitable for the actual operation of the WT in the natural world and can be applied for fault diagnosis in field WT operation.

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“…The wind speed spatiotemporal distribution characteristics directly affect the aerodynamic load resulting in load fluctuation of the WT [2][3][4]. Besides, it will also affect the power output of the wind turbine generator system (WTGS) [1,[5][6][7]. The influence of wind shear and tower shadow effects on power in terms of power fluctuation [1], power loss [5], and average output power [6] have been investigated in detail and a frequency domain approach for evaluating the impact of tower shadow and wind shear on the tie-line power oscillations was described in [7].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, it will also affect the power output of the wind turbine generator system (WTGS) [1,[5][6][7]. The influence of wind shear and tower shadow effects on power in terms of power fluctuation [1], power loss [5], and average output power [6] have been investigated in detail and a frequency domain approach for evaluating the impact of tower shadow and wind shear on the tie-line power oscillations was described in [7]. They concluded that both wind shear and tower shadow were sources of periodic power fluctuations and average power loss.…”

Section: Introductionmentioning

confidence: 99%

Research on the Fault Characteristic of Wind Turbine Generator System Considering the Spatiotemporal Distribution of the Actual Wind Speed

et al. 2020

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A reliable fault monitoring system is one of the conditions that must be considered in the design of large wind farms today. The most important factor for the fault monitoring should be the accurate diagnosis criteria with sensitive fault characteristics. Most of the current fault diagnosis criteria are obtained based on the average wind speed at the center of the hub which is not in accord with the actual wind condition in nature. So, this paper utilizes an equivalent wind speed (EWS), which can describe the actual wind speed spatiotemporal distribution on the rotor disk area considering the effects of wind shear and tower shadow, to analyze the common mechanical and electrical faults again. Firstly, the EWS model applicable to the 3-blade wind turbines is introduced; then the new fault characteristics of the wind turbine rotor aerodynamic imbalance and the stator winding asymmetry are theoretically analyzed based on the EWS model; finally, the simulation platform is built in Matlab/Simulink for comparison and the simulation result is well consistent with the theory analysis. The aim of this research is to find more accurate fault characteristics and help promoting the healthy development of wind power industry.

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Influences of Wind Shear and Tower Shadow on the Power Output of Wind Turbine

Cited by 8 publications

References 0 publications

Power Generation Performance Indicators of Wind Farms Including the Influence of Wind Energy Resource Differences

Power Generation Performance Indicators of Wind Farms Including the Influence of Wind Energy Resource Differences

Characteristic Analysis of DFIG Wind Turbine under Blade Mass Imbalance Fault in View of Wind Speed Spatiotemporal Distribution

Research on the Fault Characteristic of Wind Turbine Generator System Considering the Spatiotemporal Distribution of the Actual Wind Speed

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