contributor author | Yang, Puyi | |
contributor author | Najafi, Hamidreza | |
date accessioned | 2022-05-08T09:38:26Z | |
date available | 2022-05-08T09:38:26Z | |
date copyright | 11/9/2021 12:00:00 AM | |
date issued | 2021 | |
identifier issn | 0195-0738 | |
identifier other | jert_144_7_070904.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4285391 | |
description abstract | The accuracy of analytical wake models applied in wind farm layout optimization (WFLO) problems is of great significance as the high-fidelity methods such as large eddy simulation (LES) and Reynolds-averaged Navier–Stokes (RANS) are still not able to handle an optimization problem for large wind farms. Based on a variety of analytical wake models developed in the past decades, Flow Redirection and Induction in Steady State (FLORIS) have been published as a tool that integrated several widely used wake models and their expansions. This paper compares four wake models selected from FLORIS by applying three classical WFLO scenarios. The results illustrate that the Jensen wake model is the fastest, but the issue of underestimating the velocity deficit is obvious. The multi-zone model needs additional tuning on the parameters inside the model to fit specific wind turbines. The Gaussian-curl hybrid (GCH) wake model, as an advanced expansion of the Gaussian wake model, does not provide a significant improvement in the current study, where the yaw control is not included. The Gaussian wake model is recommended for the WFLO projects implemented under the FLORIS framework and has similar wind conditions with the present work. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | The Effect of Using Different Wake Models on Wind Farm Layout Optimization: A Comparative Study | |
type | Journal Paper | |
journal volume | 144 | |
journal issue | 7 | |
journal title | Journal of Energy Resources Technology | |
identifier doi | 10.1115/1.4052775 | |
journal fristpage | 70904-1 | |
journal lastpage | 70904-9 | |
page | 9 | |
tree | Journal of Energy Resources Technology:;2021:;volume( 144 ):;issue: 007 | |
contenttype | Fulltext | |