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Multi-machine power system adaptive dynamic surface controller based on composite learning and DOB

A technology for electromechanical power systems and power systems, applied in the field of adaptive dynamic surface controllers for multi-machine power systems, can solve problems such as ignoring the working principle of NNs/FLSs, approximation accuracy, and only focusing on system asymptotic tracking stability

Active Publication Date: 2020-10-13
NORTHEAST DIANLI UNIVERSITY +2
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these works usually only focus on the asymptotic tracking stability of the system, while ignoring the working principle of NNs / FLSs as approximators and the accuracy of the approximators

Method used

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  • Multi-machine power system adaptive dynamic surface controller based on composite learning and DOB
  • Multi-machine power system adaptive dynamic surface controller based on composite learning and DOB
  • Multi-machine power system adaptive dynamic surface controller based on composite learning and DOB

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Embodiment Construction

[0152] Multi-machine power system adaptive dynamic surface controller based on compound learning and DOB, the controller is realized based on the following steps:

[0153] 1) Construct a mathematical model of a large-scale power system with SVC devices;

[0154] The mathematical model of the described large-scale power system with SVC device is as shown in formula (1):

[0155]

[0156] h i (δ,ω) represents the coupling term:

[0157]

[0158] h i (δ,ω) ranges from:

[0159]

[0160] in,

[0161]

[0162] and p 1ij ,p 2ij A constant of 0 or 1.

[0163] To normalize the system model, let x i1 = δ i -δ i0 , x i2 = ω i -ω i0 , x i3 =P ei -P mi0 , x i4 =V mi -V refi , where V mi is the access point voltage, V refi is the reference voltage, formula (1) can be expressed by the following two subsystems:

[0164]

[0165]

[0166] in is the state vector, y i1 and y i2 It is the output of large power system and SVC equipment,

[0167]

[...

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Abstract

The invention discloses a multi-machine power system adaptive dynamic surface controller based on composite learning and DOB. The controller is realized based on the following steps: 1) constructing amathematical model of a large-scale power system with an SVC device; 2) designing a fuzzy logic system approximator of the multi-machine power system to approximate to obtain an unknown function in the multi-machine power system model in the step 1); and 3) designing a state predictor, adding a prediction error in the update law design, introducing a compensation signal, and combining the disturbance observer with the fuzzy logic system to design the multi-machine power system adaptive fuzzy dynamic surface controller based on composite learning and the disturbance observer. According to theinvention, a prediction error is added into the updating law design of the controller; a disturbance observer and a fuzzy logic system are combined to estimate generalized disturbance of the system, so that the approximation precision is improved, a compensation signal is introduced into the design of a control law, and a filtering error generated by using a filter in a dynamic surface method is eliminated.

Description

technical field [0001] The invention belongs to the field of power system control, in particular to an adaptive dynamic surface controller for multi-machine power systems based on compound learning and DOB. Background technique [0002] With the continuous expansion of the grid scale, the modern power system has gradually formed a multi-machine parallel power generation system with strong coupling dynamic nonlinear characteristics. Due to the complexity and strong coupling characteristics of the multi-machine power system, the power system is prone to oscillation, short circuit and other faults, making safe and stable operation difficult. In order to ensure the safety of the power system, it is necessary to propose a more effective control strategy and design a controller with excellent performance. For nonlinear power systems with uncertainties, combined with the actual control needs, the design of the multi-machine system excitation controller should meet the following re...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042Y02E40/10
Inventor 祝国强朱琳非张秀宇聂琳琳孙灵芳李燕王松寒王建国
Owner NORTHEAST DIANLI UNIVERSITY
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