Extreme weather turning power characteristics and risk assessment method of shaguo base group

By integrating a multidimensional meteorological factor matrix and a new energy output factor matrix, and combining a spatial weight matrix and a temporal autocorrelation function, the problem of accuracy in output characteristics and risk assessment under extreme transitional weather conditions for new energy base clusters was solved, enabling risk classification, early warning, and prevention and control under extreme transitional weather conditions.

CN121637292BActive Publication Date: 2026-07-21BAIYIN POWER SUPPLY COMPANY STATE GRID GANSU ELECTRIC POWER
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BAIYIN POWER SUPPLY COMPANY STATE GRID GANSU ELECTRIC POWER
Filing Date
2026-02-05
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing technologies are insufficient to accurately quantify the output characteristics and risk assessment of new energy base clusters under extreme weather conditions, cannot effectively reflect the spatiotemporal internal mechanisms, and have a single risk assessment dimension, failing to explore the spatiotemporal heterogeneity of the base cluster's output.

Method used

By fusing multi-source data, a multi-dimensional meteorological factor matrix and a new energy output factor matrix are constructed. Combined with a spatial weight matrix and a temporal autocorrelation function, the abnormal output characteristics and risks under extreme weather transitions are quantified, and a multi-dimensional risk indicator system is constructed for graded early warning.

Benefits of technology

It enables accurate identification and risk assessment of renewable energy output under extreme weather conditions, deeply characterizes the spatiotemporal evolution mechanism, provides scientific risk prevention and control measures, and ensures the stable operation of the power system.

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Abstract

The present application relates to the technical field of power system, disclose the extreme turning weather output characteristics and risk assessment method of Shaguo desert base group, including, multi-source data fusion and extreme scene identification criterion system construction, construct multidimensional meteorological factor matrix;Establish a plurality of extreme weather scene criterion;Construction output factor matrix, set low output coefficient threshold and climbing rate threshold, establish output anomaly criterion;Identify a plurality of predefined extreme turning weather scene;Construct a spatial weight matrix;Using the spatial weight matrix and the output factor matrix, the occurrence sequence of each base under each extreme weather scene is analyzed by time autocorrelation function and partial autocorrelation function, and a multidimensional risk index system is constructed.The advantage of the present application is to construct a meteorological criterion-output response-spatiotemporal analysis-risk assessment framework, which solves the problems of inaccurate extreme weather output characteristics capture, insufficient depth of spatiotemporal correlation description and single dimension of risk assessment.
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Citation Information

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