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  • Open Access

    ARTICLE

    GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization

    Yingchao Li1,*, Jianbin Wang1, Haibin Wang2

    Energy Engineering, Vol.121, No.4, pp. 1049-1065, 2024, DOI:10.32604/ee.2023.045228 - 26 March 2024

    Abstract With the increasing demand for electrical services, wind farm layout optimization has been one of the biggest challenges that we have to deal with. Despite the promising performance of the heuristic algorithm on the route network design problem, the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored. In this paper, the wind farm layout optimization problem is defined. Then, a multi-objective algorithm based on Graph Neural Network (GNN) and Variable Neighborhood Search (VNS) algorithm is proposed. GNN provides the basis representations for the following search algorithm so that the expressiveness… More >

  • Open Access

    ARTICLE

    Optimization for Variable Height Wind Farm Layout Model

    Bin Xu1,2,3,*, Jianming Zhu1, Junzhe Wen1, Shanshan Lin1, Yunkai Zhao1, Jin Qi1,2, Yu Xue4, Sichong Qin5

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 525-537, 2021, DOI:10.32604/iasc.2021.018338 - 16 June 2021

    Abstract The optimization of wind farm layouts is very important for the effective utilization of wind resources. A fixed wind turbine hub height in the layout of wind farms leads to a low wind energy utilization and a higher LCOE (levelized cost of electricity). WOMH (Wind Farm Layout Optimization Model Considering Multiple Hub Heights) is proposed in this paper to tackle the above problem. This model is different from the traditional fixed hub height model, as it uses a variable height wind turbine. In WOMH, the Jensen wake and Weibull distribution are used to describe the wake effect… More >

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