Multi-scale forecasting of photovoltaic power based on monitoring data for air quality

FENG Jian; NIU Haiming

doi:10.19666/j.rlfd.202002029

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Multi-scale forecasting of photovoltaic power based on monitoring data for air quality

更新时间：2025-09-28

- Multi-scale forecasting of photovoltaic power based on monitoring data for air quality
- Thermal Power Generation Vol. 49, Issue 6, Pages: 69-76(2020)
- 作者机构：
  
  北京国电智深控制技术有限公司(北京市电站自动化工程技术研究中心)
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202002029
  CLC： TM464
- Published Online：24 May 2020，
  
  Published：2020
- 稿件说明：
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FENG Jian, NIU Haiming. Multi-scale forecasting of photovoltaic power based on monitoring data for air quality[J]. Thermal power generation, 2020, 49(6): 69-76.
DOI：

FENG Jian, NIU Haiming. Multi-scale forecasting of photovoltaic power based on monitoring data for air quality[J]. Thermal power generation, 2020, 49(6): 69-76. DOI： 10.19666/j.rlfd.202002029.

摘要

近年来频繁出现的污染天气使光伏发电中太阳辐照度随空气质量出现较大变化

对光伏发电功率预测产生较大影响。对此

本文基于空气质量监测数据与气象数据

建立了气溶胶光学厚度(AOT)的光伏发电功率预测软测量模型

采用双波段大气辐射传输模型计算太阳辐照度

以日前与日内的空气质量预报信息为驱动数据

提出了一种多时间尺度的光伏发电功率预测方法

并基于此开发了光伏发电功率预测软件进行试验验证。结果表明

本文方法能够有效反映污染天气对辐照度的影响

实现对光伏发电功率的准确预测

该光伏发电功率预测软件具有较好的工程应用价值。

Abstract

In recent years

frequent pollution weather has a significant effect on transmission process of solar radiation in the atmosphere

which makes photovoltaic power forecasting face severe challenges.To solve this problem

a soft sensor model of aerosol optical thickness(AOT) is established based on air quality monitoring data and meteorological data.Dual-band atmospheric radiative transfer model is used to calculate the irradiance

and a multi-time-scale photovoltaic power forecasting method is proposed

which is driven by day-ahead and intra-day air quality forecast information.On this basis

the power prediction software of photovoltaic power generation is developed and experimental verification is performed.The results show that

the proposed method can effectively reflect the influence of pollution weather on irradiance and realize accurate prediction of photovoltaic power

and the forecasting software has good engineering application value.

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