Method for forecasting ultra-short term bus load based on load trend changes

Abstract

The invention relates to a method for forecasting an ultra-short term bus load based on load trend changes. The method comprises the following steps of: firstly, modeling a bus load; secondly, acquiring and processing bus load sample data; thirdly, selecting similar historical days; and fourthly, forecasting and calculating the ultra-short term bus load. According to the method, the obtaining of the forecasting result of the ultra-short term bus load is accelerated; and compared with the traditional methods, the method has the advantages of simpleness, practicality, high calculation speed, and accurate forecasting result meeting the requirements on real-time scheduling and real-time safe check.

Description

technical field [0001] The invention relates to the technical field of power system bus load forecasting, in particular to an ultra-short-term bus load forecasting method based on load trend changes. Background technique [0002] Ultra-short-term bus load forecasting is an important part of power system bus load forecasting. Ultra-short-term bus load forecasting plays an important and fundamental role in the formulation and arrangement of real-time and intraday power generation plans. At present, the safety check work in many network provinces can no longer fully meet the real-time safety check requirements under the real-time power generation plan and maintenance mode. The security loopholes in the real-time power generation plan and grid mode arrangement of some power grids have been reflected in the actual operation, and can only be compensated by temporarily adjusting the power generation plan or grid operation mode, which brings security risks to the power grid operati...

AI Technical Summary

Problems solved by technology

Similar to the analysis process of the ultra-short-term system bus load, the bus load itself has a specific change law, and some methods of ultra-short-term system bus load forecasting can be considered for ultra-short-term bus load forecasting, but the characteristics of the bus load forecast determine the It belongs to the problem of incomplete and inaccurate information, and it is difficult to directly apply the idea of ​​ultra-short-term system bus load forecasting to solve it. For example, inaccurate historical data and relatively many bad data will destroy most of the existing methods sexual influence

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