scholarly journals A Review of Progress and Applications of Pulsed Doppler Wind LiDARs

2019 ◽  
Vol 11 (21) ◽  
pp. 2522 ◽  
Author(s):  
Zhengliang Liu ◽  
Janet F. Barlow ◽  
Pak-Wai Chan ◽  
Jimmy Chi Hung Fung ◽  
Yuguo Li ◽  
...  
Keyword(s):  
Wind Energy ◽  
Numerical Models ◽  
Real Life ◽  
Doppler Lidar ◽  
Promising Alternative ◽  
3 Dimensional ◽  
In Situ Techniques ◽  
Energy Assessment ◽  
Wind Shears ◽  
Wind Profiles

Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.

Data Analytics Methods for Wind Energy Applications

2015 ◽  
Author(s):  
Yu Ding ◽  
Jiong Tang ◽  
Jianhua Z. Huang
Keyword(s):  
Wind Energy ◽  
Real Life ◽  
Design Parameters ◽  
Power Relationship ◽  
Energy Applications ◽  
Response Data ◽  
Wind Power Forecast ◽  
Wind Profiles ◽  
Power Outputs ◽  
Relationship Of

In the wind industry, it is important to assess a turbine systems response under different wind profiles. For instance, a wind-to-power relationship is crucial for wind power forecast, and a wind-to-stress relationship is important for selecting critical design parameters meeting the reliability requirement. Given the complexity involved in a turbine system, it is impossible to write a neat, analytical expression to underlie the above-mentioned relationships. Almost invariably does the wind industry resort to data driven methods for a solution, namely that wind data and the corresponding turbine response data (bending moments or power outputs) are used together to fit empirically the functional relationship of interest. This paper presents a couple of nonparametric data analytic methods relevant to wind energy applications with real life example for demonstration.

scholarly journals Assessment of Probabilistic Wind Forecasts at 100 m Above Ground Level Using Doppler Lidar and Weather Radar Wind Profiles

2019 ◽  
Vol 148 (3) ◽  
pp. 1321-1334 ◽  
Author(s):  
Karoliina Hämäläinen ◽  
Elena Saltikoff ◽  
Otto Hyvärinen ◽  
Ville Vakkari ◽  
Sami Niemelä
Keyword(s):  
Wind Energy ◽  
Surface Wind ◽  
Modern Society ◽  
Ground Level ◽  
Training Data ◽  
Doppler Lidar ◽  
Know How ◽  
Wind Speeds ◽  
Probabilistic Forecasts ◽  
Wind Profiles

Abstract Modern society is very dependent on electricity. In the energy sector, the amount of renewable energy is growing, especially wind energy. To keep the electricity network in balance we need to know how much, when, and where electricity is produced. To support this goal, the need for proper wind forecasts has grown. Compared to traditional deterministic forecasts, ensemble models can better provide the range of variability and uncertainty. However, probabilistic forecasts are often either under- or overdispersive and biased, thus not covering the true and full distribution of probabilities. Hence, statistical postprocessing is needed to increase the value of forecasts. However, traditional closer-to-surface wind observations do not support the verification of wind higher above the surface that is more relevant for wind energy production. Thus, the goal of this study was to test whether new types of observations like radar and lidar winds could be used for verification and statistical calibration of 100-m winds. According to our results, the calibration improved the forecast skill compared to a raw ensemble. The results are better for low and moderate winds, but for higher wind speeds more training data would be needed, either from a larger number of stations or using a longer training period.

scholarly journals Wind Energy Meteorology: Insight into Wind Properties in the Turbine-Rotor Layer of the Atmosphere from High-Resolution Doppler Lidar

2013 ◽  
Vol 94 (6) ◽  
pp. 883-902 ◽  
Author(s):  
Robert M. Banta ◽  
Yelena L. Pichugina ◽  
Neil D. Kelley ◽  
R. Michael Hardesty ◽  
W. Alan Brewer
Keyword(s):  
Wind Energy ◽  
Ground Level ◽  
Turbine Rotor ◽  
Energy Industry ◽  
Doppler Lidar ◽  
Near Surface ◽  
Surface Measurements ◽  
Wind Measurements ◽  
Upper Level ◽  
Insight Into

Addressing the need for high-quality wind information aloft in the layer occupied by turbine rotors (~30–150 m above ground level) is one of many significant challenges facing the wind energy industry. Without wind measurements at heights within the rotor sweep of the turbines, characteristics of the flow in this layer are unknown for wind energy and modeling purposes. Since flow in this layer is often decoupled from the surface, near-surface measurements are prone to errant extrapolation to these heights, and the behavior of the near-surface winds may not reflect that of the upper-level flow.

Efficient data filtering for wind energy assessment

2012 ◽  
Vol 6 (6) ◽  
pp. 446-454 ◽  
Author(s):  
J.J. Melero ◽  
J. Beltrán ◽  
C. Pueyo ◽  
J.J. Guerrero
Keyword(s):  
Wind Energy ◽  
Data Filtering ◽  
Energy Assessment ◽  
Efficient Data

A temporal model for vertical extrapolation of wind speed and wind energy assessment

2021 ◽  
Vol 301 ◽  
pp. 117378
Author(s):  
Paola Crippa ◽  
Mariana Alifa ◽  
Diogo Bolster ◽  
Marc G. Genton ◽  
Stefano Castruccio
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Assessment ◽  
Temporal Model

Computationally Simple and Efficient Method for Solving Real-Life Mixed Intuitionistic Fuzzy 3D Assignment Problems

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Assignment Problem ◽  
Graphical Representation ◽  
Real Life ◽  
Optimal Solution ◽  
Future Research ◽  
Assignment Problems ◽  
3 Dimensional ◽  
Intuitionistic Fuzzy ◽  
Comparison Results ◽  
Future Research Directions

This article addresses the 3-dimensional mixed intuitionistic fuzzy assignment problems (3D-MIFAPs). In this article, firstly, the author formulates an assignment problem (AP) and assumes the parameters are in uncertainty with hesitation. Secondly, based on the nature of the parameter the author defines various types of solid assignment problem (SAP) in uncertain environment. Thirdly, to solve 3D-MIFAP the PSK method for finding an optimal solution of fully intuitionistic fuzzy assignment problem (FIFAP) is extended by the author. Fourthly, the author presents the proofs of the proposed theorems and corollary. Fifthly, the proposed approach is illustrated with three numerical examples and the optimal objective value of 3D-MIFAP is obtained in the form of intuitionistic fuzzy number and the solution is checked with MATLAB and their coding are also given by the author. Sixthly, the author presents the comparison results and their graphical representation, merits and demerits of the proposed and existing methods and finally the author presents conclusion and future research directions.

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