Random scene analysis method considering time sequence autocorrelation and cross correlation

Abstract

The invention relates to the field of random scene analysis methods, in particular to a random scene analysis method considering time sequence self-correlation and cross-correlation. The method comprises the following steps: sampling annual time sequence data of each uncertainty factor of a target area according to a probability model of each uncertainty factor; obtaining an initial uncertainty factor time sequence, performing time sequence reconstruction on the initial uncertainty factor time sequence according to the autocorrelation of the initial uncertainty factor time sequence, generating an uncertainty factor random time sequence considering the time sequence autocorrelation, combining the uncertainty factor random time sequence, and forming a first random scene set considering the time sequence autocorrelation; and obtaining a second random scene set considering time sequence self-correlation and cross-correlation. According to the scene set generated by the method, the characteristics of historical data can be completely represented with a small amount of data, and data support is provided for solving the problem of optimal planning operation of a power system containing renewable energy sources.

Description

technical field [0001] The invention relates to the field of random scene analysis methods, in particular to a random scene analysis method considering time series autocorrelation and mutual correlation. Background technique [0002] With the integration of renewable energy into the grid, due to the access of uncertain energy sources such as photovoltaic or wind power, the problems of long-term planning, medium-term operation and short-term scheduling of the power system become uncertain optimization problems, and scenario analysis is a kind of It is an effective way to solve the problem of optimal planning and operation of the power system containing renewable energy by constructing deterministic scenarios to analyze the uncertainty of the power system. [0003] At present, the research on scene analysis methods at home and abroad is mainly based on the statistical characteristics of the research objects, and adopts certain methods to sample them to obtain scenes that can d...

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Problems solved by technology

[0004] The current research mainly analyzes the uncertainty factors from different perspectives. However, the research on the scenario analysis that comprehensively considers the time series correlation of each uncertainty factor itself and the cross-correlation between each uncertainty factor is still lacking. It is not deep enough and the calculation efficiency is low, which brings certain difficulties to the optimal planning and operation of the power system. For this reason, the present invention proposes a random scene analysis method that considers time series autocorrelation and cross-correlation

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