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Solar forecasting methods for renewable energy integration

机译:可再生能源整合的太阳预报方法

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摘要

The higher penetration of renewable resources in the energy portfolios of several communities accentuates the need for accurate forecasting of variable resources (solar, wind, tidal) at several different temporal scales in order to achieve power grid balance. Solar generation technologies have experienced strong energy market growth in the past few years, with corresponding increase in local grid penetration rates. As is the case with wind, the solar resource at the ground level is highly variable mostly due to cloud cover variability, atmospheric aerosol levels, and indirectly and to a lesser extent, participating gases in the atmosphere. The inherent variability of solar generation at higher grid penetration levels poses problems associated with the cost of reserves, dispatchable and ancillary generation, and grid reliability in general. As a result, high accuracy forecast systems are required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment. Here we review the theory behind these forecasting methodologies, and a number of successful applications of solar forecasting methods for both the solar resource and the power output of solar plants at the utility scale level.
机译:可再生资源在多个社区的能源投资组合中的渗透率更高,这就要求在几个不同的时间尺度上准确预测可变资源(太阳能,风能,潮汐能),以实现电网平衡。过去几年中,太阳能发电技术经历了强劲的能源市场增长,本地电网普及率也相应提高。与风一样,地面上的太阳能资源变化很大,这主要是由于云量变化,大气气溶胶水平,以及间接(在较小程度上)大气中的参与气体。在较高的电网穿透水平下,太阳能发电的固有可变性带来了与储备成本,可调度和辅助发电成本以及总体电网可靠性相关的问题。结果,对于与调节,调度,调度和机组承诺相关的多个时间范围,需要高精度的预测系统。在这里,我们回顾了这些预测方法论背后的理论,以及在公用事业规模层面上太阳能预测方法在太阳能资源和太阳能发电厂功率输出方面的成功应用。

著录项

  • 来源
    《Progress in Energy and Combustion Science》 |2013年第6期|535-576|共42页
  • 作者单位

    Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center of Excellence in Renewable Energy Integration and Center for Energy Research, University of California, 9500 Gilman Drive, La Jolla, CA 92093, USA;

    Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center of Excellence in Renewable Energy Integration and Center for Energy Research, University of California, 9500 Gilman Drive, La Jolla, CA 92093, USA;

    Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center of Excellence in Renewable Energy Integration and Center for Energy Research, University of California, 9500 Gilman Drive, La Jolla, CA 92093, USA;

  • 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

    Weather-dependent renewable energy; Solar forecasting; Solar meteorology; Solar variability; Solar energy integration; Evolutionary forecasting methods;

    机译:取决于天气的可再生能源;太阳预报;太阳气象;太阳变化;太阳能一体化;进化预测方法;
  • 入库时间 2022-08-18 00:26:22

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