CN-121995746-A - Collaborative optimization method and device for control parameters of network-structured equipment

CN121995746ACN 121995746 ACN121995746 ACN 121995746ACN-121995746-A

Abstract

The application provides a collaborative optimization method and device for control parameters of network construction type equipment, the method comprises the steps of S1, determining an identification sequence of the control parameters to be identified according to a double-loop control strategy of the network construction type equipment, S2, identifying the control parameters in a collaborative mode of field test and laboratory simulation according to the identification sequence, S3, adjusting the identified control parameters through a plurality of step response tests based on the identified control parameters until the response characteristics of the equipment meet preset requirements, S4, synchronizing the optimized control parameters to a laboratory simulation platform, simulating various preset working conditions in the laboratory simulation platform, and verifying the adaptability of the optimized control parameters under different preset working conditions, and S5, if the verification result of the adaptability shows that the preset requirements are not met under part of preset working conditions, repeatedly executing the steps S3 and S4 until the adaptability verification is passed under all the preset working conditions.

Inventors

LU WENQING
LI CHANGYU
LIANG BEIHUA
XIE HUAN
HUANG TIANXIAO
CAO TIANZHI
HAO JING
LIU YINGLIN
LI SHANYING

Assignees

国网冀北电力有限公司电力科学研究院
国家电网有限公司

Dates

Publication Date: 20260508
Application Date: 20251225

Claims (10)

1. A method for collaborative optimization of control parameters of a networking device, the method comprising: Step S1, determining an identification sequence of control parameters to be identified according to a double-loop control strategy of the network construction equipment, wherein the sequence is to identify limiting parameters firstly and then proportional integral parameters; s2, identifying the control parameters in a field test and laboratory simulation cooperative mode according to the identification sequence; Step S3, based on the identified control parameters, adjusting the identified control parameters on the field device according to the actual strength of the power grid and the requirements of related technical standards by performing a plurality of step response tests until the response characteristics of the device meet the preset requirements, thereby obtaining a set of optimized control parameters; Step S4, synchronizing the optimized control parameters to a laboratory simulation platform, simulating a plurality of preset working conditions in the laboratory simulation platform, and verifying the adaptability of the optimized control parameters under different preset working conditions; and step S5, if the adaptability verification result shows that the preset requirements are not met under part of preset working conditions, repeating the step S3 and the step S4 until the adaptability verification is passed under all the preset working conditions, and obtaining the corresponding optimal control parameters.
2. The collaborative optimization method for control parameters of a network forming device according to claim 1, wherein the identification sequence of limiting parameters is from an outer ring to an inner ring, and the identification sequence of proportional-integral parameters is that active control loops are identified first and reactive control loops are identified later, and is carried out from the inner ring to the outer ring.
3. The collaborative optimization method of control parameters of a web-formed apparatus according to claim 1, wherein identifying the control parameters by a field test and laboratory simulation collaborative manner according to the identification sequence comprises: On a field device, directly identifying a first type of control parameters by applying preset operation, wherein the first type of control parameters comprise a limiting parameter, an inertia time constant, a damping coefficient and a proportionality coefficient; Synchronizing the on-site system intensity information and the identified first type control parameters to a laboratory simulation platform, comparing a simulation response curve with an on-site actual measurement response curve by performing step test on the simulation platform, and determining a second type control parameter which is an integral coefficient by using a parameter value when errors of the two curves are minimum.
4. The method for collaborative optimization of control parameters of a web-forming apparatus according to claim 3 wherein directly identifying clipping parameters by applying a predetermined operation includes gradually increasing an amount of change in input to a corresponding control link until an amount of output from the control link is no longer changed, and taking the amount of output that is no longer changed as a corresponding clipping value.
5. The method of collaborative optimization of control parameters of a web-formed device of claim 3 wherein directly identifying an inertial time constant by applying a predetermined operation includes obtaining the inertial time constant by superimposing a linearly varying angular frequency on the active control output and calculating the inertial time constant based on a quotient of the active power and the rate of change of the angular frequency.
6. The method of collaborative optimization of control parameters of a web-formed device of claim 3 wherein directly identifying a damping coefficient by applying a predetermined operation includes superimposing an active power step amount on an active power reference value and calculating the damping coefficient based on a quotient of the active power change amount and the angular frequency change amount.
7. The method of collaborative optimization of control parameters of a web-formed appliance of claim 3 wherein directly identifying the scaling factor by applying a preset operation includes obtaining the scaling factor by applying a voltage step change and calculating from an instantaneous change in internal potential of the static trim output, a reference instantaneous change in static trim ac voltage, and an instantaneous change in output of the control loop from the difference in static trim ac voltage.
8. The method for collaborative optimization of control parameters of a networking device of claim 1 wherein performing multiple step response tests includes performing reactive power step response tests, alternating voltage step response tests, and active power step response tests.
9. The method for collaborative optimization of control parameters of a networking device of claim 1, wherein the predetermined conditions include short circuit fault conditions of different locations and types, system frequency offset conditions, and conditions at different system strengths.
10. A co-optimizing apparatus for control parameters of a network forming device, the apparatus comprising: the identification sequence determining unit is used for determining the identification sequence of the control parameters to be identified according to the double-loop control strategy of the network construction equipment, wherein the sequence is to identify the limiting parameters firstly and then identify the proportional integral parameters; the cooperative identification unit is used for identifying the control parameters in a cooperative mode of field test and laboratory simulation according to the identification sequence; The parameter adjusting unit is used for adjusting the identified control parameters on the field device according to the actual strength of the power grid and the requirements of related technical standards by performing step response tests for a plurality of times until the response characteristics of the device meet the preset requirements, so as to obtain an optimized set of control parameters; And the simulation verification unit is used for synchronizing the optimized control parameters to a laboratory simulation platform, simulating various preset working conditions in the laboratory simulation platform, comprehensively verifying the adaptability of the optimized control parameters under different preset working conditions, and if the verification result of the adaptability shows that the preset requirements are not met under part of the preset working conditions, sequentially repeating the operation of the parameter adjustment unit and the simulation verification unit until the adaptability verification is passed under all the preset working conditions, so as to obtain the corresponding optimal control parameters.

Description

Collaborative optimization method and device for control parameters of network-structured equipment Technical Field The application relates to the technical field of new energy power generation, in particular to a collaborative optimization method and device for control parameters of network construction equipment. Background At present, a power system taking new energy as a main body increasingly presents the characteristics of low inertia and weak damping. To address these challenges, grid-built devices have become a key technology for improving weak grid stability due to their ability to actively support the superior characteristics of grid voltage and frequency, and are widely used. Before grid-connected operation of the network-structured equipment, the control parameters of the network-structured equipment must be accurately identified and set so as to ensure that the simulation model of the network-structured equipment is consistent with the behavior of the field equipment and ensure that the network-structured equipment can safely and stably operate under various working conditions. The accurate parameters are the fundamental basis for the subsequent power grid mode calculation, operation limit analysis and control strategy formulation. However, the existing network-structured equipment parameter identification and optimization method has the following significant defects: The traditional parameter identification method, such as a method based on frequency domain analysis, needs to inject complex disturbance signals into a power grid on site, and is difficult to implement due to high difficulty and high risk in actual operation. Other identification methods based on the optimal algorithm (such as a particle swarm algorithm) require a large amount of on-site step test data for training, which is also difficult to obtain in on-site network performance tests with tight time and heavy tasks. Therefore, there is a lack of an effective means to efficiently, accurately and safely identify all control parameters under field conditions. After the network construction equipment completes preliminary parameter setting on site, whether the control parameters of the network construction equipment can adapt to the impact of a power grid under different operation modes (such as system strength change) and various unknown faults (such as short circuits of different types and different positions) is a key for ensuring the long-term safe operation of the equipment. However, due to limited field test conditions, it is not possible nor permissible to simulate various types of extreme or fault conditions in the field to verify the suitability of the parameters one by one. In the prior art, no clear mention and effective solution is made on how to perform comprehensive and systematic parameter adaptability verification after on-site parameter setting and ensure the performance under various complex working conditions. In summary, the prior art has the problems of difficult field implementation and insufficient precision in the aspect of network construction equipment parameter identification, and especially lacks a systematic adaptability verification link after parameter optimization, so that the set parameters may not be capable of coping with complex and variable working conditions of a power grid, and hidden danger is left for stable operation of equipment and even the power grid. Disclosure of Invention In view of the above, the present application provides a method and apparatus for collaborative optimization of control parameters of a networking device to solve at least one of the above-mentioned problems. In order to achieve the above purpose, the present application adopts the following scheme: according to a first aspect of the present application, there is provided a collaborative optimization method of control parameters of a network-structured device, the method comprising: Step S1, determining an identification sequence of control parameters to be identified according to a double-loop control strategy of the network construction equipment, wherein the sequence is to identify limiting parameters firstly and then proportional integral parameters; s2, identifying the control parameters in a field test and laboratory simulation cooperative mode according to the identification sequence; Step S3, based on the identified control parameters, adjusting the identified control parameters on the field device according to the actual strength of the power grid and the requirements of related technical standards by performing a plurality of step response tests until the response characteristics of the device meet the preset requirements, thereby obtaining a set of optimized control parameters; step S4, synchronizing the optimized control parameters to a laboratory simulation platform, and simulating various preset working conditions in the laboratory simulation platform to comprehensively verify the adaptability of the op