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Device and method for short-term load forecasting of electric power system based on combined forecasting model

A short-term load forecasting and combined forecasting technology, applied in forecasting, electrical digital data processing, special data processing applications, etc., can solve problems such as unsatisfactory forecasting effect and need to be improved, and achieve the effect of improving accuracy and stability and high precision

Inactive Publication Date: 2016-06-29
HARBIN ENG UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the accuracy and stability of the above methods need to be improved, and the forecasting effect is not ideal.

Method used

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  • Device and method for short-term load forecasting of electric power system based on combined forecasting model
  • Device and method for short-term load forecasting of electric power system based on combined forecasting model
  • Device and method for short-term load forecasting of electric power system based on combined forecasting model

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Experimental program
Comparison scheme
Effect test

Embodiment approach

[0027] (1) Collect and properly process the load data of the power grid to form a usable load time series;

[0028] (2) Using the least squares method, Kalman filter method, and chaotic Kalman filter method to establish three single forecast models to calculate the forecast results f 1t , f 2t , f 3t ;

[0029]The least squares method has been introduced in references, so I won’t go into details here. The following is a detailed introduction to the use of Kalman filter method for short-term power system load forecasting. This method uses the Kalman filter recursive formula to establish an adaptive AR model, and the AR model autoregressive parameters As the Kalman filter state vector, the derivation process of the Kalman filter method will not be repeated here, and the variables in the Kalman filter equation are compared with the variables in the AR model equation, as shown in Table 1:

[0030] Table 1 Variable comparison of the corresponding equations in the stationary stat...

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Abstract

The invention provides a short-term load forecasting device and method of a power system based on a combination forecasting model. It includes a data acquisition module, an input module, a single model prediction module, a determination weight coefficient module, a combined prediction module, a prediction result evaluation module, a prediction effect simulation analysis module and an output module. The present invention proposes an AR model based on a Kalman filtering algorithm and a chaotic Kalman filtering algorithm when selecting a single forecasting model; and proposes an improved variable weight coefficient method when calculating a combined model weight coefficient. The accuracy and stability of load forecasting are further improved, and the modular structure of the device facilitates device upgrades and maintenance, providing decision support for the economical, safe and reliable operation of the power system.

Description

technical field [0001] The invention relates to a short-term load forecasting device of an electric power system, and also relates to a short-term load forecasting method of an electric power system. Background technique [0002] In power system operation, control and planning management, load forecasting determines the reasonable arrangement of power generation, transmission and distribution, and is an important part of power system planning. Among them, the most important application of short-term load forecasting is to provide data for the power generation planning program to determine the operation plan that meets the safety requirements, operation constraints, and natural environment and equipment restrictions, which plays a role in the safety, reliability and economy of power grid operation. play an important role. How to improve the prediction accuracy is the center and focus of the research on the theory and method of short-term load forecasting. Accurate short-term...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00G06Q10/04G06Q50/06
Inventor 彭秀艳崔艳青闫金山
Owner HARBIN ENG UNIV