Swarm-Inspired Artificial Bee Colony Algorithm for Solving Optimal Power Flow with Wind Farm

Raj, M. Devesh; Muthuselvan, N.B.; Somasundaram, P.

doi:10.1007/s13369-014-1084-9

Cited by 8 publications

(2 citation statements)

References 24 publications

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“…The genetic algorithm, NSGA-II and PSO are some of the commonly used algorithms (Lanting, 2012). Algorithms provide realistic solutions for optimum design, especially given the many design requirements (Raj et al , 2014). Figure 16 shows the flowchart of the optimization study used in this study.…”

Section: Optimization Modelmentioning

confidence: 99%

Multi-objective structural optimization of a wind turbine blade using NSGA-II algorithm and FSI

Özkan

Genç

2021

AEAT

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Purpose Wind turbines are one of the best candidates to solve the problem of increasing energy demand in the world. The aim of this paper is to apply a multi-objective structural optimization study to a Phase II wind turbine blade produced by the National Renewable Energy Laboratory to obtain a more efficient small-scale wind turbine. Design/methodology/approach To solve this structural optimization problem, a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) was performed. In the optimization study, the objective function was on minimization of mass and cost of the blade, and design parameters were composite material type and spar cap layer number. Design constraints were deformation, strain, stress, natural frequency and failure criteria. ANSYS Composite PrepPost (ACP) module was used to model the composite materials of the blade. Moreover, fluid–structure interaction (FSI) model in ANSYS was used to carry out flow and structural analysis on the blade. Findings As a result, a new original blade was designed using the multi-objective structural optimization study which has been adapted for aerodynamic optimization, the NSGA-II algorithm and FSI. The mass of three selected optimized blades using carbon composite decreased as much as 6.6%, 11.9% and 14.3%, respectively, while their costs increased by 23.1%, 29.9% and 38.3%. This multi-objective structural optimization-based study indicates that the composite configuration of the blade could be altered to reach the desired weight and cost for production. Originality/value ACP module is a novel and advanced composite modeling technique. This study is a novel study to present the NSGA-II algorithm, which has been adapted for aerodynamic optimization, together with the FSI. Unlike other studies, complex composite layup, fiber directions and layer orientations were defined by using the ACP module, and the composite blade analyzed both aerodynamic pressure and structural design using ACP and FSI modules together.

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Section: Optimization Modelmentioning

confidence: 99%

Multi-objective structural optimization of a wind turbine blade using NSGA-II algorithm and FSI

Özkan

Genç

2021

AEAT

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“…refs. [7][8][9][10][11][12][13] ). Wind turbines are installed in a configuration known as a ''wind farm,'' which functions and is linked to the power grid as a single electricity power plant.…”

Section: Introductionmentioning

confidence: 99%

Wind farm control and power curve optimization using induction-based wake model

Jahantigh

Esmailifar

Sina

2023

Measurement and Control

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This paper proposes a control strategy to achieve minimum wake-induced power losses in a wind farm. At first, the axial-induction-based wake model is developed to consider the aerodynamic wake interactions among wind turbines. To optimize the generated power of the whole wind farm, the axial induction factor of each wind turbine is calculated by the genetic algorithm. As a supervisory controller, each wind turbine’s optimal axial induction factor calculated by the genetic algorithm is implemented as a setpoint of each wind turbine’s internal controller. In the internal control loop, a comprehensive controller is designed to track the commanded axial induction factor. In the partial load region, the commanded axial induction factor was attained by tuning the generator torque. In the transient and full load regions, the blade pitch angle is tuned to keep the generator speed and torque at the rated values. The performance of the proposed control strategy is investigated through case studies, including three different wind speeds and a time-varying wind speed case in a 3 × 3 wind-farm layout. The simulation results show the satisfactory performance of the proposed approach.

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Smooth Integration of Gansu Wind Farm into the Grid Using the Stator Flux-Oriented Vector Method and Fuzzy Logic Control

2017

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Swarm-Inspired Artificial Bee Colony Algorithm for Solving Optimal Power Flow with Wind Farm

Cited by 8 publications

References 24 publications

Multi-objective structural optimization of a wind turbine blade using NSGA-II algorithm and FSI

Multi-objective structural optimization of a wind turbine blade using NSGA-II algorithm and FSI

Wind farm control and power curve optimization using induction-based wake model

Smooth Integration of Gansu Wind Farm into the Grid Using the Stator Flux-Oriented Vector Method and Fuzzy Logic Control

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