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A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

机译:葡萄牙的PSO-ANFIS混合方法用于短期风电预测

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摘要

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.
机译:如今在葡萄牙,风能越来越多地集成到电网中,由于其间歇性和波动性,带来了新的挑战。风能预测在应对这些挑战中起着关键作用。本文的目的是提出一种结合了粒子群算法和基于自适应网络的模糊推理系统的混合方法,用于葡萄牙的短期风电预测。与通过其他五种方法获得的结果相比,使用所提出的方法可以实现有关预测准确性的重大改进。

著录项

  • 来源
    《Energy Conversion & Management》 |2011年第1期|p.397-402|共6页
  • 作者单位

    Department of Electromechanical Engineering, University ofBeira Interior, R. Fonte do Lameiro, 6201-001 Covilha, Portugal;

    Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon, Portugal;

    Department of Electromechanical Engineering, University ofBeira Interior, R. Fonte do Lameiro, 6201-001 Covilha, Portugal,Center for Innovation in Electrical and Energy Engineering, Instituto Superior Ttcnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    wind power; prediction; swarm optimization; neuro-fuzzy;

    机译:风力;预测;群优化;神经模糊;

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