面向光热发电的太阳能短期预报技术

ZHANG Yue

您当前的位置：

首页 >

文章列表页 >

面向光热发电的太阳能短期预报技术

更新时间：2025-08-13

- 面向光热发电的太阳能短期预报技术
- Automation of Electric Power Systems Vol. 40, Issue 19, Pages: 158-167(2016)
- 作者机构：
  
  中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京市,100029
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
移动端阅览
ZHANG Yue. [J]. Automation of electric power systems, 2016, 40(19): 158-167.
DOI：

ZHANG Yue. [J]. Automation of electric power systems, 2016, 40(19): 158-167. DOI：

摘要

随着全球太阳能行业的迅猛发展

越来越多的太阳能以光热发电的形式被电网吸纳

准确地预报未来几天的法向直接辐射已成为光热项目并网和现场运行维护的基础。文中介绍了法向直接辐射的定义、国内电力工业标准、法向直接辐射短期预报方法、影响短期预报精度的要素和提高短期预报精度的方法

回顾了国内最新的研究进展

提出了当前研究中存在的问题

并对未来的研究趋势做了展望

以期对“十三五”期间太阳能热发电行业的发展提供参考。

Abstract

Along with the rapid development of solar energy industry

more and more solar energy is integrated into electricity grid in the form of concentrating solar power(CSP). Forecasting direct normal irradiance(DNI)accurately several days ahead has become the foundation for solar energy integration as well as operation and maintenance of a CSP power plant. Treated in the paper are the definition of DNI

the electric power industry standards in China

methodology of short-term DNI forecasting

influence factors of forecast accuracy

approaches to accuracy improvement

and most recent advances of research in the nation. Meanwhile

problems in current researches are presented and future research and trends are envisioned for reference by the development of CSP in the “13th five-year plan” period. This work is supported by State Key Program of National Natural Science Foundation of China(No. 41130104)and Major Program of National Natural Science Foundation of China(No. 41590875).

关键词

Keywords

references

Views

10768

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Error Tracing Method for Photovoltaic Power Prediction Considering Causality Verification of Numerical Weather Prediction Transfer Entropy

组合数值天气预报与地基云图的光伏超短期功率预测模型

基于数值天气预报的母线负荷预测

Related Author

WANG Chuanqi

YU Yixiao

LIU Chun

WANG Bo

LI Menglin

YANG Ming

PEI Ming

SHA Licheng

Related Institution

Key Laboratory of Power System Intelligent Dispatch and Control (Shandong University)

State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems (China Electric Power Research Institute)

School of Information and Electrical Engineering, China Agricultural University

China Electric Power Research Institute

State Grid Beijing Electric Power Company

⁰