Energy Production Of Wind Farm Research Articles

Probable power production in optimally matched wind turbine generators

Abstract The windmill design can be optimally matched to the site meteorological characteristics for maximization of the turbine performance-index. This paper focuses on the performance of optimally matched wind turbine generators (WTGs) as affected by the WTG operating concept and the statistical behavior of wind speeds. Pitch regulated fixed-speed (FS) and variable-speed (VS) operating concepts are considered. Improved models are developed for representing the turbine power coefficient and estimating the probable power production. The work in this paper is beneficial in estimating the expected power and energy production in wind farms with multiple technologies of different operating concepts. In addition, this work is beneficial in the techno-economic analysis for wind farm design and upgrade. For the selected sites in Egypt, it is found that it is possible for variable-speed systems to produce about 9% increase in the average probable power in comparison with fixed-speed systems.

Errors and uncertainties associated with missing wind data and short records

ABSTRACTA near‐complete 4 year data set of 10 min average 80 m wind speeds is used to examine the impact of missing data on monthly and yearly estimates of mean wind speed and energy production from a generic wind turbine. Missing data is a source of uncertainty in wind energy resource assessment studies. Quantifying that uncertainty can improve the reliability of P90 and related wind farm energy production estimates. An empirical relationship between missing data percentage and relative uncertainty in monthly mean wind speed is derived. Relationships between uncertainties in monthly average wind speed and uncertainties in monthly energy production are also explored. In many cases with monthly data losses of 10% or less the contribution to the overall uncertainty in annual energy production will be small (<1%), but with substantial losses in cold winters, typically caused by icing; the uncertainties can become more significant. The data set is also used to indicate uncertainties associated with short data periods. Annual average wind speed estimates based on less than a complete year's data also add significant uncertainty to wind resource assessments. Copyright © 2013 John Wiley & Sons, Ltd.

복잡지형에 위치한 풍력발전단지의 연간발전량 예측 비교 연구

The annual energy production of Gangwon wind farm was predicted for three consecutive years of 2007, 2008 and 2009 using commercial programs, WindPRO and WindSim which are known to be used the most for wind resource prediction in the world. The predictions from the linear code, WindPRO, were compared with both the actual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm and also the predictions from the CFD code, WindSim. The results from WindPRO were close to the actual energy productions and the errors were within 11.8% unlike the expectation. The reason for the low prediction errors was found to be due to the fact that although the wind farm is located in highly complex terrain, the terrain steepness was smaller than a critical angle() in front of the wind farm in the main wind direction. Therefore no flow separation was found to occur within the wind farm. The flow separation of the main wind was found to occur mostly behind the wind farm.

Assessment of Extremum Seeking Control for Wind Farm Energy Production

Aerodynamic interaction among turbines grouped together in wind farms causes a decrease in the total energy extracted from the wind when compared to an equal number of widely dispersed turbines operating under the same wind input conditions as the wind farm. Extremum seeking control (ESC) is one strategy that holds promise for reducing this impact under certain wind input conditions. In this paper, we evaluate the effectiveness of ESC under different turbulence conditions, describing methods for addressing the complexities caused by the turbulent wind input and time-varying delay of the wind between turbines, where these two elements are the most important contributions compared to other wind farm control research. The results show that energy capture can be increased in low turbulence intensity conditions, but perhaps not in high turbulence conditions.

상용 CFD 프로그램을 이용한 복잡지형에서의 풍속 예측

Investigations on modeling methods of a CFD wind resource prediction program, WindSim for accurate predictions of wind speeds were performed with the field measurements. Meteorological Masts having heights of 40m and 50m were installed at two different sites in complex terrain. The wind speeds and direction were monitored from sensors installed on the masts and recorded for one year. Modeling parameters of WindSim input variables for accurate predictions of wind speeds were investigated by performing cross predictions of wind speeds at the masts using the measured data. Four parameters that most affect the wind speed prediction in WindSim including the size of a topographical map, cell sizes in x and y direction, height distribution factors, and the roughness lengths were studied to find out more suitable input parameters for better wind speed predictions. The parameters were then applied to WindSim to predict the wind speed of another location in complex terrain in Korea for validation. The predicted annual wind speeds were compared with the averaged measured data for one year from meteorological masts installed for this study, and the errors were within 6.9%. The results of the proposed practical study are believed to be very useful to give guidelines to wind engineers for more accurate prediction results and time-saving in predicting wind speed of complex terrain that will be used to predict annual energy production of a virtual wind farm in complex terrain.

Energy production assessment of small wind farms

The present work investigates the performance and the energy production of a grid-connected wind farm during six years of operation. The layout and the single line diagram of this wind farm are shown. A complete record of operational data for five turbines is analysed to study the performance of the wind farm. The study illustrates the variation of the energy and wind speed on annual and monthly basis for the whole examined period. On the other hand, the annual growth in the local consumption of the wind farm is shown. As an important indicator, the capacity factor is analysed for single turbines and for the whole wind farm. Finally, the study attempts to correlate the results to the external and internal factors affecting the performance of these turbines using the available database.

Characterization of Wind Farm Energy Production in a Zone by Artificial Neuronal Networks

Characterization of Wind Farm Energy Production in a Zone by Artificial Neuronal Networks