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Identification method of power object model in steam turbine regulating system

A technology for adjusting the system and object model, which is applied in the field of system identification, can solve problems such as easy to fall into local optimum, premature beetle whisker search algorithm, etc., and achieve good practicability, high degree of curve fitting, and good identification effect

Active Publication Date: 2020-05-19
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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  • Application Information

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Problems solved by technology

Since it was proposed, it has been widely used in workshop scheduling, optimization problems, power grid planning, etc., but the beetle whisker search algorithm is prone to premature maturity and easy to fall into local optimum

Method used

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  • Identification method of power object model in steam turbine regulating system
  • Identification method of power object model in steam turbine regulating system
  • Identification method of power object model in steam turbine regulating system

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Embodiment

[0045] With reference to the accompanying drawings, it is the first embodiment of the present invention, which provides a method for identifying the power object model of a steam turbine regulating system. The identification algorithm includes: improving the beetle whisker search algorithm, introducing an adaptive Factor and simulated annealing's Monte Carlo rule improves the local search strategy, and obtains an improved longhorn beetle search algorithm; collects sample data, and collects the actual operation data of the steam turbine regulation system of the thermal power plant as sample data; identifies the power object model, and uses the improved The beetle whisker search algorithm identifies the power object model through the sample data, and obtains the identification result.

[0046] Specifically, input the parameters of the steam turbine regulating system into the database, and initialize the parameters of the beetle beetle search algorithm including the step factor para...

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Abstract

The invention discloses an identification method of a power object model in a steam turbine regulating system. The method comprises the following steps of introducing an adaptive factor and a simulated annealing Monte Carlo rule into a basic beetle antennae search algorithm to improve a local searching strategy to obtain an improved beetle antennae search algorithm; collecting actual operation data of the steam turbine regulating system of a thermal power plant, and selecting a section with obvious power change of data sections as sample data; and identifying the power object model through thesample data by using the improved beetle antennae search algorithm to obtain an identification result. Compared with the prior art, according to the method, the simulated annealing Monte Carlo rule is introduced to improve the basic beetle antennae search algorithm, so that the local search speed is higher, the local optimization can be effectively avoided, the global convergence speed is higher,the stability is better, the overall identification effect is better, and the method has important practical significance for improving the automatic control level of a thermal power unit.

Description

technical field [0001] The invention relates to the technical field of system identification technology, in particular to an identification method for a power object model of a steam turbine regulating system. Background technique [0002] With the continuous development of today's science and technology, the composition of supercritical units and ultra-supercritical thermal power plants has become the main development trend. Whether the thermal automatic control of large thermal power units can operate safely has become particularly important. How to design the control system of the controlled object model and Parameter tuning becomes the core issue. Since the accuracy of the step response curve parameter identification method is not too high, it is difficult to complete the model parameter identification of large-capacity units with higher accuracy requirements. In recent years, various intelligent optimization algorithms such as ant colony algorithm, leapfrog algorithm, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F01D17/10G06F17/18
CPCF01D17/105G06F17/18F05D2270/70
Inventor 孙宇贞李帅彭道刚赵慧荣李芹唐毅伟
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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