Abstract

The land use limitations, especially for onshore applications, have led modern Wind Turbines (WTs) to be aggregated in wind parks under the scope of minimizing the necessary area required. Within this framework, the trustworthy prediction of the wind speed deficiency downstream the WTs' hub (known also as the “wake effect”) and the meticulous wind park micrositing are of uppermost importance for the optimized WTs siting across the available land area. In this context, substantial effort has been made by the academic and research community, contributing to the deployment of several analytical, numerical and semi-empirical wake models, attempting to estimate the wind speed values at different locations downstream a WT. The accuracy of several semi-empirical and analytical wake models, serving also as the basis for pertinent commercial software development, is investigated in the present work, by comparing their outcome with experimental data from a past research work that concerns the wake flow. The dimensionless streamwise distance (known also with the term “downstream distance”) from the WT's hub is used as benchmark in order to categorize and evaluate the calculation results. A dedicated comparison between the wind speed cases investigated is conducted, striving to properly assess the wake models' prediction accuracy. The notable findings obtained for the wake models examined designate the requirement for subsequent research to enlighten the wake effect dynamic behavior.

Highlights

  • The constant environmental degradation along with the imminent carbon containing fuel reserves depletion underline the need to deploy more environmentally friendly energy resources [1] to deal with the constantly growing energy demand of the planet [2]

  • Wind Farm Layout Optimization (WFLO) or wind farm micrositing is crucial as it defines the wind farm’s performance, both in terms of energy yield and cost. This can be considered as a quest for the optimized Wind Turbines’ (WTs) allocation across the available territory and is mainly carried out as a compromise between the optimal exploitation of the available wind energy potential of the area considered for the project implementation and the mechanical loading on downstream WTs [4,5]

  • The wake models’ performance percentage deviation from the relevant data is used as the basis for the assessment procedure conducted, with the downstream distance being used as the comparison parameter

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Summary

Introduction

The constant environmental degradation along with the imminent carbon containing fuel reserves depletion underline the need to deploy more environmentally friendly energy resources [1] to deal with the constantly growing energy demand of the planet [2]. WTs are on rare occasions being positioned in downstream distances greater than ten “Â/D” due to local topography, ground morphology and land availability issues It is mainly the mid-wake sub-region that captivates the interest of both project developers and academic researchers. The WTs’ downstream distance and the upstream wind speed variation are considered of paramount importance for the wake effect development [24,25,26,27,28,29] In this framework, the current work conducts a comparative assessment of eight prominent semi-empirical and analytical wake models, many of which are utilized till date as the basis for pertinent commercial software deployment. The useful conclusions drawn set the groundwork for future research activity that could be conducted in the specific scientific domain

Wake effect models classification
Comparison basis
Percentage deviation calculation
Calculation results for characteristic wind speeds
Prediction performance evaluation for the entire wind speed value range
Conclusions
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