A New Model for Wind Farm Layout Optimization With Landowner Decisions

2011 ◽  
Author(s):  
Le Chen ◽  
Erin MacDonald
Keyword(s):  
Wind Farm ◽  
Optimization Methods ◽  
Layout Optimization ◽  
Negotiation Process ◽  
Site Location ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Novel Approach ◽  
Local Residents ◽  
A Site

Current wind farm layout optimization research focuses on advancing optimization methods. The research includes the assumption that a continuous piece of land is readily available. In reality, wind farm development projects rely on the permission of landowners for success. When a viable wind farm site location is identified, local residents are approached for permission to build turbines on their land, typically in exchange for monetary compensation. Landowners play a crucial role on the development of a wind farm and some land parcels are more important to the success of the project than others. In order to advance the research on wind farm optimization, this paper relaxes the assumption that a continuous piece of land is available, developing a novel approach that includes landowners’ decisions on whether or not to participate in the project. The optimization results of this new approach show that, for a specific wind farm layout case, we can identify the most crucial landowners and the optimal positions of turbines prior to the negotiation process with landowners. Using this approach, a site developer can spend more resources on persuading these most-important landowners to take part in the project, or approach them in a personalized manner. This will ultimately increase the efficiency of wind farm projects, saving time and money in the development stages.

Considering Landowner Participation in Wind Farm Layout Optimization

2012 ◽  
Vol 134 (8) ◽  
Author(s):  
Le Chen ◽  
Erin MacDonald
Keyword(s):  
Wind Farm ◽  
Participation Rate ◽  
Optimization Methods ◽  
Layout Optimization ◽  
Negotiation Process ◽  
Nonlinear Constrained Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Novel Approach ◽  
Local Residents

Current wind farm layout optimization research assumes a continuous piece of land is readily available and focuses on advancing optimization methods. In reality, projects rely on landowners’ permission for success. When a viable site is identified, local residents are approached for permission to build turbines on their land, typically in exchange for monetary compensation. Landowners play a crucial role in the development process, and some land parcels are more important to the success of project than others. This paper relaxes the assumption that a continuous piece of land is available, developing a novel approach that includes a model of landowner participation rates. A genetic algorithm (GA) is adopted to solve the nonlinear constrained optimization problem, minimizing cost and maximizing power output. The optimization results show that, given a projected participation rate, we can identify the most crucial plots prior to the negotiation process with landowners. This will ultimately increase the efficiency of wind farm development.

scholarly journals Realistic Wind Farm Layout Optimization through Genetic Algorithms Using a Gaussian Wake Model

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3268 ◽  
Author(s):  
Nicolas Kirchner-Bossi ◽  
Fernando Porté-Agel
Keyword(s):  
Genetic Algorithms ◽  
Wind Farm ◽  
Gaussian Model ◽  
Wind Farms ◽  
Optimization Methods ◽  
Layout Optimization ◽  
Power Losses ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Wake Model

Wind Farm Layout Optimization (WFLO) can be useful to minimize power losses associated with turbine wakes in wind farms. This work presents a new evolutionary WFLO methodology integrated with a recently developed and successfully validated Gaussian wake model (Bastankhah and Porté-Agel model). Two different parametrizations of the evolutionary methodology are implemented, depending on if a baseline layout is considered or not. The proposed scheme is applied to two real wind farms, Horns Rev I (Denmark) and Princess Amalia (the Netherlands), and two different turbine models, V80-2MW and NREL-5MW. For comparison purposes, these four study cases are also optimized under the traditionally used top-hat wake model (Jensen model). A systematic overestimation of the wake losses by the Jensen model is confirmed herein. This allows it to attain bigger power output increases with respect to the baseline layouts (between 0.72% and 1.91%) compared to the solutions attained through the more realistic Gaussian model (0.24–0.95%). The proposed methodology is shown to outperform other recently developed layout optimization methods. Moreover, the electricity cable length needed to interconnect the turbines decreases up to 28.6% compared to the baseline layouts.

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.

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