Research on Power Equipment Rainstorm Warning Combined with Weather Forecast Data Interpolation and Regional Assessment

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CIRED 2019 - 896.pdf (451.05 KB)

Paper number

896

Working Group Number

Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

CUI, YIPING, Guangzhou Power Supply Co. Ltd., China
LUAN, LE, Guangzhou Power Supply Co. Ltd., China
LIU, YUQUAN, Guangzhou Power Supply Co. Ltd., China
MO, WENXIONG, Guangzhou Power Supply Co. Ltd., China
Li, Xin, Guangzhou Power Supply Co. Ltd., China
WANG, HONGBIN, Guangzhou Power Supply Co. Ltd., China

Abstract

This paper analyzes the early warning of urban power grid equipment under heavy rain, especially for the prediction and early warning of power equipment safety hazards caused by short-term large-scale rainfall. The historical data is used to analyze the specific impact form of heavy rain on power equipment. The algorithm of rainfall data interpolation based on inverse distance weighting method is proposed. The granularity of meteorological data is refined from 5km×5km to 500m×500m. Through the dynamic adjustment of the power parameters, the interpolation data of the black point rainfall in the city is optimized, and the monitoring and statistics of the meteorological forecast data of specific power equipment or station are realized. At the same time, combined with the meteorological warning of the meteorological department, the prediction and early warning of the flooding risk of power equipment is realized. As an example, this paper uses the weather data of a certain city in southern China to carry out calculations. The result shows that the comprehensive optimization results can not only effectively improve the accuracy of the rainstorm warning of specific power equipment, but also avoid the data error caused by the traditional inverse distance weighting algorithm, and effectively improve the practical application value.

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Keywords

Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/189
http://dx.doi.org/10.34890/369

ISSN

2032-9644

ISBN

978-2-9602415-0-1