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首页> 外文期刊>Solar Energy >Data-driven upscaling methods for regional photovoltaic power estimation and forecast using satellite and numerical weather prediction data
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Data-driven upscaling methods for regional photovoltaic power estimation and forecast using satellite and numerical weather prediction data

机译:基于卫星和数值天气预报数据的区域光伏发电量估算和预测的数据驱动放大方法

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摘要

The growing photovoltaic generation results in a stochastic variability of the electric demand that could compromise the stability of the grid, increase the amount of energy reserve and the energy imbalance cost. On regional scale, the estimation of the solar power generation from the real time environmental conditions and the solar power forecast is essential for Distribution System Operators, Transmission System Operator, energy traders, and Aggregators.
机译:不断增长的光伏发电量导致电力需求的随机变化,这可能会损害电网的稳定性,增加能源储备量和能源失衡成本。在区域范围内,根据实时环境条件估算太阳能发电量和预测太阳能发电量对配电系统运营商,传输系统运营商,能源贸易商和集合商至关重要。

著录项

  • 来源
    《Solar Energy》 |2017年第12期|1026-1038|共13页
  • 作者单位

    Univ Roma Tor Vergata, Dept Enterprise Engn, Via Politecn 1, I-00133 Rome, Italy|EURAC Res, Viale Druso 1, I-39100 Bolzono, Italy;

    ENEA, Climate Modelling Lab, Bologna, Italy;

    Ideam Srl, Via Frova 34, Cinisello Balsamo, Italy;

    EURAC Res, Viale Druso 1, I-39100 Bolzono, Italy;

    Ideam Srl, Via Frova 34, Cinisello Balsamo, Italy;

    Ideam Srl, Via Frova 34, Cinisello Balsamo, Italy;

    Univ Roma Tor Vergata, Dept Enterprise Engn, Via Politecn 1, I-00133 Rome, Italy|Univ Roma Tor Vergata, CHOSE, Via Politecn 1, I-00133 Rome, Italy;

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

    Regional photovoltaic generation; Forecast; Neural networks; Spatial clustering;

    机译:区域光伏发电预报神经网络空间聚类;

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