Interval-taylor-model-based system and method for forecasting short-term load of power system

Abstract

The invention discloses an interval-taylor-model-based system and method for forecasting a short-term load of a power system, and can be used for analyzing the influence of the basic data uncertainty to a forecasting result and saving the computing time greatly. The system comprises a data acquisition module used for leading data into a database module, a data preprocessing module used for describing the uncertainty of basic data via using an interval arithmetic so as to sectioning all the basic data and transmitting the result into the database module, a load forecasting and analyzing module used for forecasting the short-term load via using an interval taylor formula model short-term load forecasting formula, a result management module used for converting and outputting the result and transmitting the analysis result into the database module, and the database module used for storing the data generated by the data acquisition module, the data preprocessing module, the load forecasting and analyzing module and the result management module as well as used for providing data invocation service.

Description

technical field [0001] The invention relates to a short-term load forecasting system of a power system, in particular to a short-term load forecasting system and method of a power system based on an interval Taylor model. The invention belongs to the technical field of power system short-term load forecasting. Background technique [0002] Short-term load forecasting usually refers to predicting the load changes of a certain power system in the next few hours, one day to several days, and the time interval is 15 minutes, 30 minutes or 1 hour. It is used for thermal power generation output distribution, water and thermal power coordination, unit economic combination, Swap power plans, etc. Accurate short-term load forecasting is of great significance for determining power purchase and sale plans, reducing backup, reducing ancillary service costs, and improving system security. [0003] However, short-term load changes are restricted by many factors such as system operating ...

AI Technical Summary

Problems solved by technology

[0007] The historical data used in forecasting are all definite values, but the formation of historical data has certain accidental factors, ignoring the uncertainty of historical data;

[0008] The influence of historical samples on load factors is too dependent on historical samples, but the validity of historical samples has an important impact on the calculation results, which directly leads to the accuracy of calculation results

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