中国电力 ›› 2020, Vol. 53 ›› Issue (6): 97-106,123.DOI: 10.11930/j.issn.1004-9649.201809009

• 新能源 • 上一篇    下一篇

基于去趋势互相关分析法的光照、温度和风速互相关性分析

吴晓升, 江岳文   

  1. 福州大学 电气工程与自动化学院,福建 福州 350108
  • 收稿日期:2018-09-10 修回日期:2019-01-29 发布日期:2020-06-05
  • 作者简介:吴晓升(1995-),男,硕士研究生,从事风电并网优化运行和电力系统优化运行研究,E-mail:n170127060@fzu.edu.cn;江岳文(1977-),女,通信作者,博士,副教授,从事风电并网优化运行、电力系统优化运行研究,E-mail:jiangyuewen2008@163.com
  • 基金资助:
    国家自然科学基金资助项目(基于源网协调的新建风电场装机容量决策理论研究,51707040);福建省自然科学基金资助项目(片区多风电场汇聚耦合氢储能系统送出规划研究,2018J01482)

A Cross-Correlation Analysis of Irradiation, Temperature and Wind Speed Based on Detrended Cross-Correlation Method

WU Xiaosheng, JIANG Yuewen   

  1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
  • Received:2018-09-10 Revised:2019-01-29 Published:2020-06-05
  • Supported by:
    This work is supported by National Natural Science Foundation of China (Research on Capacity Decision Theory of Newly Built Wind Farm Considering Coordination of "Source-Grid", No.51707040) and Natural Science Foundation of Fujian Province in China(Study on Planning Schemes of Convergent Coupled Hydrogen Storage System for Multiple Wind Farms Area, No.2018J01482)

摘要: 合理利用气象因素之间的互相关特性有利于降低系统运行成本,提高系统稳定性。采用美国3个不同地区的光照、风速、温度的历史实测数据对三者所具有的长程自相关性与互相关性进行探究。首先利用去趋势波动分析法对3个地区的光照、风速、温度的长程自相关性进行分析;其次采用去趋势互相关分析法(detrended cross-correlation analysis method, DCCA)和DCCA互相关系数进一步量化在不同尺度下三者之间的互相关性;最后构建风光互补发电场景并分析风光互补的总体特性和季节特性,验证了相关性分析的有效性和必要性。

关键词: 去趋势波动分析法, 互相关性, 长程自相关性, 风速, 光照, 温度

Abstract: Exploiting the interconnections among meteorological factors properly can reduce the operating costs and enhance the stability of the system. In this paper, the measured data of irradiation, wind velocity and temperature at three different areas in the United States are used to explore the long-range auto correlation and the interactions between these factors. First of all, the detrended fluctuation analysis method (DFA) is adopted to analyze the long-range auto correlation of these meteorological factors at three areas, respectively. Moreover, the detrended cross-correlation analysis method (DCCA) and the coefficient for reciprocity of DCCA is used to quantify the interactions of these three factors at different scales. Finally, several wind-solar hybrid generation scenarios are developed to evaluate the general and seasonal characteristics of the complementarity between wind and solar energy. The results verify the validity and necessity of the proposed model.

Key words: DFA, cross-correlation, long-range auto-correlation, wind speed, irradiation, temperature