Spatio-temporal correlation day-ahead plan load flow analysis method with uncertainty being taken into consideration

Abstract

The invention provides a spatio-temporal correlation day-ahead plan load flow analysis method with uncertainty being taken into consideration. The spatio-temporal correlation day-ahead plan load flow analysis method comprises the following steps: obtaining next-day forecast wind speed of wind power plants in 96 time period within 24 hours; obtaining next-day output of the wind power plants; obtaining forecast error distribution of the next-day output of the wind power plants; carrying out independence conversion on random variables having spatio-temporal correlation; calculating semi-invariant of a load flow in each line; and determining relevant information for dispatching. The method carries out engineering algorithm processing on the forecast error distribution having correlation, thereby solving the problem that probability distribution having correlation cannot be obtained by utilizing a series expansion method directly. Analysis is carried out on the next-day load flow of each line in each time period through a Gram-Charlier series expansion method ; through such analysis method, probabilistic load flow problem can be solved conveniently and effectively; the method has a practical value; and the present series expansion method commonly used in medium/ long-term probabilistic load flow analysis is expanded to short-term plan load flow analysis, thereby providing more data support for economic dispatching.

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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