A Power Flow Analysis Method for Day-ahead Planning Considering the Spatio-temporal Correlation of Uncertainty

Abstract

The present invention provides a day-ahead planned power flow analysis method considering the time-space correlation of uncertainty, which includes obtaining the predicted wind speed of wind farms in 24 hours and 96 periods of the next day; obtaining the next day's wind farm output; and obtaining the next day's output prediction error of each wind farm Distribution; independent transformation of random variables with time-space correlation; calculation of semi-invariant variables of power flow on each line; determination of relevant information required for scheduling. The invention processes the correlation prediction error distribution with an engineering algorithm, and solves the disadvantage that the correlation probability distribution cannot be directly applied to the series expansion method. The Gram-Charlier series expansion method is used to analyze the power flow of each line in each time period of the next day. It is convenient and effective to use this analytical method to solve the probabilistic power flow problem, and has practical value. The number expansion method is extended to short-term planning power flow analysis, which provides more data support for economic dispatch.

Description

technical field [0001] The invention belongs to the field of power systems, and in particular relates to a method for analyzing a day-ahead planned power flow considering the time-space correlation of uncertainty. Background technique [0002] In recent years, as the share of wind turbine output in the total power generation continues to increase, how to conduct effective power flow analysis for power grids containing wind farms has always been a hot research issue. In 2014, 13,121 new wind turbines were added across the country, with a new installed capacity of 23,196MW, a year-on-year increase of 44.2%. In this situation, the day-ahead wind power forecast and the power flow analysis of the power system including wind power have very important reference value for ensuring the reliability and economy of the next day dispatch plan. [0003] However, there are still some deficiencies in the data provided by our country for the day-ahead plan (that is, the next day plan) of th...

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Problems solved by technology

[0012] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a day-ahead planning power flow analysis method that considers the time-space correlation of uncertainty, carries out engineering algorithm processing on the forecast error distribution with correlation, and solves the problem of probability with correlation Disadvantages that the distribution cannot be directly applied to the series expansion method

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