Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation

2012 ◽  
Vol 38 (1) ◽  
pp. 16-30 ◽  
Author(s):  
Souma Chowdhury ◽  
Jie Zhang ◽  
Achille Messac ◽  
Luciano Castillo
Keyword(s):  
Power Generation ◽  
Wind Farm ◽  
Layout Optimization ◽  
Maximum Power ◽  
Key Factors ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Factors Influencing

scholarly journals Comparisons of the accuracy of different wake models in wind farm layout optimization

2020 ◽  
Vol 38 (5) ◽  
pp. 1725-1741 ◽  
Author(s):  
Xiaoxia Gao ◽  
Yue Li ◽  
Fei Zhao ◽  
Haiying Sun
Keyword(s):  
Power Generation ◽  
Wind Farm ◽  
Layout Optimization ◽  
Wind Condition ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Cost Of Energy ◽  
Generation Cost ◽  
Wake Model ◽  
Population Genetic Algorithm

Accurate wake model in wind farm layout optimization can help extracting maximum power generation, minimizing cost of energy and prolonging wind turbines’ lifetime as well. With the development of different wake models, the wind farm layout optimization results based on the models should be updated. This paper investigates the performances of four wake models in wind farm layout optimization using multi-population genetic algorithm (MPGA) with the wind farm power generation, COST/AEP and wind farm efficiency been reported. Comparison of results between typical wake models’ performance shows that Jensen’s wake model reported a higher wind farm power generation and efficiency because it underestimates the velocity deficit in the wake, and to the contrary, in the Frandsen wake model, the velocity in the wake is underestimated, resulting in a deceased power generation. The expression of 2D_k model shall be out of work in complicated wind condition. The 2D Jensen–Gaussian wake model performed better in the wind farm layout optimization using the MPGA program which can be promoted in real-world wind farm micrositing.

A Comparative Study of the Influence of Different Wake Models on Wind Farm Layout Optimization

2021 ◽  
Author(s):  
Puyi Yang ◽  
Hamidreza Najafi
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Vital Role ◽  
Layout Optimization ◽  
Zone Model ◽  
Wind Farm Layout ◽  
Yaw Control ◽  
Wind Farm Layout Optimization ◽  
Wake Model ◽  
Large Wind

Abstract The accuracy of analytical wake models applied in wind farm layout optimization (WFLO) problems plays a vital role in the present era that the high-fidelity methods such as LES and RANS are still not able to handle an optimization problem for large wind farms. Based on a verity of analytical wake models developed in the past decades, FLOw Redirection and Induction in Steady State (FLORIS) has been published as a tool integrated several widely used wake models and the expansions for them. 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 one but the defect of underestimation of velocity deficit is obvious. The Multi Zone model needs to be applied additional tunning on the parameters inside the model to fit specific wind turbines. The Gaussian-Curl wake model as an advanced expansion of the Gaussian wake model does not perform an observable improvement in the current study that the yaw control is not included. The default Gaussian wake model is recommended to be used in the WFLO projects which implemented under the FLROIS framework and has similar wind conditions with the present work.

Two Stage Mini-Max Algorithm for Grid-Based Wind Farm Layout Optimization

2017 ◽  
Author(s):  
Ning Quan ◽  
Harrison Kim
Keyword(s):  
Power Output ◽  
Wind Farm ◽  
Optimization Problem ◽  
Layout Optimization ◽  
Discrete Optimization Problem ◽  
Real World Data ◽  
Two Stage ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Grid Based

The power maximizing grid-based wind farm layout optimization problem seeks to determine the layout of a given number of turbines from a grid of possible locations such that wind farm power output is maximized. The problem in general is a nonlinear discrete optimization problem which cannot be solved to optimality, so heuristics must be used. This article proposes a new two stage heuristic that first finds a layout that minimizes the maximum pairwise power loss between any pair of turbines. The initial layout is then changed one turbine at a time to decrease sum of pairwise power losses. The proposed heuristic is compared to the greedy algorithm using real world data collected from a site in Iowa. The results suggest that the proposed heuristic produces layouts with slightly higher power output, but are less robust to changes in the dominant wind direction.

scholarly journals Multi-rotor Wind Farm Layout Optimization

2020 ◽  
Vol 1618 ◽  
pp. 032014
Author(s):  
Nicolas Kirchner-Bossi ◽  
Fernando Porté-Agel
Keyword(s):  
Wind Farm ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization
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