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首页> 外文期刊>Journal of Cleaner Production >Hybrid wind energy forecasting and analysis system based on divide and conquer scheme: A case study in China
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Hybrid wind energy forecasting and analysis system based on divide and conquer scheme: A case study in China

机译：基于划分和征服计划的混合风能预测和分析系统 - 以中国为例

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摘要

Wind energy, acknowledged as a promising form of renewable energy and the fastest-growing clean method for electricity generation, has attracted considerable attention from many scientists and researchers in recent decades. However, wind energy forecasting is still a challenging task owing to its inherent features of non-linearity and randomness. Therefore, this study develops a hybrid wind energy forecasting and analysis system including a deterministic forecasting module and an uncertainty analysis module to mitigate the challenges in existing studies. In particular, these challenges are as follows: (1) It is difficult to guarantee that the data characteristics underlying the time series are effectively extracted; (2) in the modeling of each subseries, i.e., when the original data is decomposed into some time series, forecasting accuracy and stability are not simultaneously considered, and thus, they are not properly modeled; and (3) the best function to perform a deterministic forecasting and uncertainty analysis based on the forecaster of each subseries is unknown. The developed hybrid system consists of three steps: First, data preprocessing is conducted to capture and mine the main feature of the wind energy time series and weaken the noises' negative effects; second, multi-objective optimization is proposed to achieve the forecasting of each subseries with improvements in accuracy and stability; finally, search for the best function, which obtains the deterministic forecasting and uncertainty analysis results using an optimized extreme learning machine based on different modeling objectives, is conducted. Experimental simulations are performed using data from three sites in a real wind farm, which indicate that the developed system has a better performance in engineering applications than that of other methods. Furthermore, this system could not only be used as an effective tool for wind energy deterministic forecasting and uncertainty analysis, but also for other engineering application areas in the future. (C) 2019 Elsevier Ltd. All rights reserved.
机译：风能，承认是一种有希望的可再生能源形式和最快的发电方法，近几十年来吸引了许多科学家和研究人员的相当大的关注。然而，由于其非线性和随机性的固有特征，风能预测仍然是一个具有挑战性的任务。因此，本研究开发了一种混合风能预测和分析系统，包括确定性预测模块和不确定性分析模块，以减轻现有研究中的挑战。特别是，这些挑战如下：（1）难以保证时间序列的数据特征有效提取; （2）在每个子系的建模中，即，当原始数据被分解成某个时间序列时，未同时考虑预测精度和稳定性，因此它们没有正确建模; （3）基于每个子系列的预测驾驶员执行确定性预测和不确定性分析的最佳功能是未知的。开发的混合系统由三个步骤组成：首先，进行数据预处理以捕获并挖掘风能时间序列的主要特征，削弱噪音的负面影响;其次，提出了多目标优化，以实现每种子百合的预测，提高准确性和稳定性;最后，搜索最佳功能，从而获得了基于不同建模目标的优化的极限学习机的确定性预测和不确定性分析结果。使用来自真正的风电场的三个站点的数据进行实验模拟，这表明开发系统在工程应用中具有比其他方法更好的性能。此外，该系统不仅可以用作风能确定性预测和不确定性分析的有效工具，而且还用于将来其他工程应用领域。 （c）2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Journal of Cleaner Production》 |2019年第10期|942-959|共18页
  • 作者

    Yang Wendong; Wang Jianzhou; Lu Haiyan; Niu Tong; Du Pei;

  • 作者单位

    Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Liaoning Peoples R China|Univ Technol Fac Engn & Informat Technol Sch Software Sydney NSW Australia;

    Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Liaoning Peoples R China|Univ Technol Fac Engn & Informat Technol Sch Software Sydney NSW Australia;

    Univ Technol Fac Engn & Informat Technol Sch Software Sydney NSW Australia;

    Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Liaoning Peoples R China|Univ Technol Fac Engn & Informat Technol Sch Software Sydney NSW Australia;

    Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Liaoning Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hybrid system; Deterministic forecasting; Uncertainty analysis; Optimization; Wind energy;

    机译：混合系统;确定性预测;不确定性分析;优化;风能;

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