Calculation and prediction method of agc performance evaluation index of thermal power unit based on system identification

Abstract

The invention discloses a thermal power generating unit AGC performance evaluation index calculation and prediction method based on system identification. The thermal power generating unit AGC performance evaluation index calculation and prediction method comprises the steps of: establishing a first-order delay inertia model with a load command as an input and actual power generation power as an output based on actual operation data of a unit, and calculating unit AGC performance evaluation indexes by adopting parameters of the established model; and establishing a non-linear regression modelbetween different unit AGC index values and the corresponding unit AGC performance evaluation indexes K1, K2 and K3, and utilizing the established nonlinear regression model to realize predictive analysis on a unit AGC evaluation result. Through establishing the non-linear regression model between the unit AGC evaluation indexes and the unit AGC instructions, the function of predicting the unit AGC evaluation indexes is realized, and the defect that the unit AGC performance cannot be predicted at present is overcome.

Description

technical field [0001] The invention relates to the technical field of thermal power unit index calculation and prediction, in particular to a system identification-based calculation and prediction method for thermal power unit AGC performance assessment indicators. Background technique [0002] Automatic Generation Control (AGC) technology is an important technical means to maintain the real-time balance between power grid generation and load, and to ensure the stable and safe operation of the power system. Automatic generation control realizes the readjustment and distribution of generator power in the control area through the automatic control program, so as to cope with the dynamic changes of the load in the control area, maintain the dynamic balance of the exchange power, and realize the stable operation of the power grid. [0003] In the current power market environment where power plants and grids are separated, each power generation company that can provide AGC servi...

AI Technical Summary

Problems solved by technology

[0006] 1) The existing AGC evaluation index calculation method is adjusted in the computer group to adjust the rate K 1 , it will lead to the adjustment rate K of the same system corresponding to input signals of different amplitudes under the same conditions 1 problem with different values

Therefore, in the AGC assessment index of the existing unit, K 1 The calculation method is difficult to correctly reflect the adjustment rate of the unit, which will lead to deviations in the AGC assessment results of the unit

[0007] 2) The existing AGC evaluation index calculation method is adjusted in the computer group to adjust the precision K 2 When , only a few data points in the steady state of the unit are selected for calculation and analysis, and all the points of the actual power line are not considered, resulting in the adjustment accuracy K 2 Computing poor ability to resist random interference

[0008] 3) Existing AGC evaluation index calculation method is in computer group response time K 3 In this case, the time taken by the unit to reliably step out of the adjustment dead zone consistent with the adjustment direction according to the AGC command is used. The selection of this time is greatly disturbed by noise, and the judgment process is greatly affected by human subjectivity. There is no obvious reference standard. Resulting in crew response time K 3 Calculation accuracy is poor

[0009] 4) The existing AGC evaluation index calculation method cannot realize the prediction of the AGC performance of the unit, and it is difficult to provide theoretical support and data support for the power grid dispatching and the AGC performance optimization of the unit

[0010] In short, the existing calculation methods have defects such as inaccurate calculation results, greater influence by external interference, and greater subjective influence, which affect the scientific rationality of the AGC assessment results of the unit, hinder the active participation of power generation enterprises in AGC assessment, and improve the AGC of the unit. Enthusiasm for performance restricts grid construction and development in certain factors

[0011] To sum up, in the prior art, there is still a lack of effective solutions to the problem of inaccurate calculation and prediction of AGC performance evaluation indicators for thermal power units

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