Load prediction system of regional power grid and method thereof

Abstract

The invention discloses a load prediction system of a regional power grid and a method thereof, wherein the load prediction system comprises a reverse isolation device, a data processing module, a load classification module, a load prediction module and a database; the data processing module is used for preliminarily processing load data collected by the reverse isolation device into load sample data; the load classification module is used for utilizing FCM fuzzy clustering to carry out classification on the load sample data and selecting mean values of all kinds of load curves as a typical daily load curve; and the load prediction module is used for using the typical daily load curve as an input variable of a BP nerve network, carrying out prediction, and obtaining a load predicted value of the regional power grid. With comprehensively considering influences of season and weather factors on loads, the pre-processing module is improved, the loads are classified based on the FCM fuzzy clustering, the typical daily load curve is accurately found, the load predicted value of the regional power grid is obtained by the BP nerve network, and the inherent law of history load data is fully extracted, so that the prediction precision is greatly improved.

Description

technical field [0001] The invention relates to the field of power grid load forecasting, in particular to a load classification and forecasting system and method for a regional power grid. Background technique [0002] In recent years, with the development of the electricity market, electricity users have higher and higher requirements on the quality of electricity delivered by the power system. In order to ensure the quality of electric energy transmitted by the power system, it is necessary to maintain a stable dynamic balance between the power generation output of electric energy and the electric load. Since the electric load is fluctuated by seasons and weather factors, a power load forecasting system with high prediction accuracy is required. The current power load forecasting system has a single function, no load classification processing module, and the forecasting accuracy obtained according to the traditional forecasting method can no longer meet the quality requir...

AI Technical Summary

Problems solved by technology

The current power load forecasting system has a single function, no load classification processing module, and the forecasting accuracy obtained according to the traditional forecasting method can no longer meet the quality requirements of the current power system to transmit electric energy

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