On Aerodynamic Optimization of Wind Farm Layout

Rašuo, Boško; Bengin, Aleksandar; Veg, Aleksandar

doi:10.1002/pamm.201010262

Cited by 48 publications

(41 citation statements)

References 2 publications

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“…In discrete models [4,5,26], the wind farm domain is divided into a number of possible turbine locations, while for continuous models [27][28][29][30][31][32][33], the turbine location is represented by two-dimensional continuous coordinates. Continuous models are typically solved using evolutionary metaheuristic algorithms [31,[34][35][36][37]32,[38][39][40] and nonlinear optimization methods [41,42]. A discrete model can be solved by using mathematical programming approaches, which have the significant advantage of providing optimality bounds [3,20,24,25,6].…”

Section: Optimization Modelsmentioning

confidence: 99%

Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming

et al. 2016

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Section: Optimization Modelsmentioning

confidence: 99%

Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming

et al. 2016

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“…Most methods for optimizing turbine placement consider expansions and contractions of standard layouts. Some models test several standard configurations and compare the optimal spacing for each configuration . Classical mixed‐integer programming has been employed to solve this problem up to optimality .…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated offshore wind farm design: Optimizing micro‐siting and cable layout simultaneously

et al. 2019

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Electrical layout and turbine placement are key design decisions in offshore wind farm projects. Increased turbine spacing minimizes the energy losses caused by wake interactions between turbines but requires costlier cables with higher rates of failure. Simultaneous micro‐siting and electrical layout optimization are required to realize all possible savings. The problem is complex, because electrical layout optimization is a combinatorial problem and the computational fluid‐dynamics calculations to approximate wake effects are impossible to integrate into classical optimization. This means that state‐of‐the‐art methods do not generally consider simultaneous optimization and resort to approximations instead. We extend an existing model that successfully optimizes cable design to simultaneously consider micro‐siting. We use Jensen's equations to approximate the wake effect in an efficient manner, calibrating it with years of mast data. The wake effects are precalculated and introduced into the optimization problem. We solve simultaneously for turbine spacing and cable layout, exploiting the tradeoffs between these wind farm features. We use the Barrow Offshore Wind Farm as a case study to demonstrate realizable savings up to 6 MEUR over the lifetime of the plant, although it is possible that unforeseen design constraints have implications for whether the savings seen in our model are fully realizable in the real world. In addition, the model provides insights on the effects of turbine spacing that can be used to simplify the design process or to support negotiations for surface concession at the earlier stages of a project.

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“…Obviously, aerodynamic loads are a major source of dynamic structural behavior, and ought to be accurately determined. In addition, the blade geometry parameters are required for dynamic load analysis of wind turbine rotors [4][5][6][7].…”

Section: Fme Transactions Figure 2 Main Elements Of Hawtsmentioning

confidence: 99%

Aerodynamic design of horizontal axis wind turbine blades

Mulugeta¹,

Gerawork²

2017

FME Transaction

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On Aerodynamic Optimization of Wind Farm Layout

Abstract: This paper presents a method for determination of optimum positions of single wind turbines within the wind farms installed on arbitrary configured terrains, in order to achieve their maximum production effectiveness.

Cited by 48 publications

References 2 publications

Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming

Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming

Integrated offshore wind farm design: Optimizing micro‐siting and cable layout simultaneously

Aerodynamic design of horizontal axis wind turbine blades

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