Double-fed fan parameter identification method based on improved sparrow algorithm

By improving the Sparrow Algorithm to build a double-feed fan control system model in PSCAD, analyzing parameter sensitivity and building an error function, the problems of low parameter recognition accuracy and poor adaptability to extreme working conditions are solved, and high-precision control parameter recognition and improved global search capabilities are achieved.

CN119726908APending Publication Date: 2025-03-28QINGHAI DEHONG ELECTRIC POWER TECH CO LTD
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Patent Information

Application Number
CN202411841253.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-13
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

The prior art is difficult to accurately identify the key control parameters of double-feeding fans, resulting in low recognition accuracy, poor adaptability to extreme working conditions and low consistency of multiple identification results.

Method used

The double-feed fan parameter identification method based on the improved sparrow algorithm is adopted to divide the control parameters into key and non-key parameters. Through the improved sparrow algorithm, the double-feed fan control system model is built in PSCAD, the parameter sensitivity is analyzed, the error function is constructed and the optimization is carried out to obtain the identification result.

Benefits of technology

It realizes accurate identification of key control parameters of double-feed fan, improves identification accuracy and adaptability to extreme working conditions, avoids local optimal problems, and enhances global search capabilities and convergence speed.

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Abstract

The invention discloses a doubly-fed fan parameter identification method based on an improved sparrow algorithm, and the method comprises the steps: analyzing the sensitivity of doubly-fed fan parameters, selecting key control parameters, building a doubly-fed fan low-voltage ride-through transient model in a PSCAD (Power System Computer Aided Design), obtaining a plurality of groups of output data through adjusting the key control parameters, and carrying out the identification of the doubly-fed fan parameters. Constructing a multi-target error function of the original model and the identification model; the improved sparrow algorithm is adopted to optimize and solve the established multi-target error function based on the key control parameters and the output data, the identification result of the to-be-identified control parameters of the doubly-fed fan is obtained, an identification model obtained through identification and an original model are compared and verified, the key control parameters in the transient model of the doubly-fed fan can be accurately and reliably identified, and the identification accuracy of the to-be-identified control parameters of the doubly-fed fan is improved. The problems that a traditional doubly-fed fan parameter identification method is low in identification precision, poor in adaptability to extreme working conditions and low in consistency of multiple identification results are effectively solved.
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