CN113346482A - Method for predicting frequency space-time distribution of wide area power system based on SFR model - Google Patents

Method for predicting frequency space-time distribution of wide area power system based on SFR model Download PDF

Info

Publication number
CN113346482A
CN113346482A CN202110545737.1A CN202110545737A CN113346482A CN 113346482 A CN113346482 A CN 113346482A CN 202110545737 A CN202110545737 A CN 202110545737A CN 113346482 A CN113346482 A CN 113346482A
Authority
CN
China
Prior art keywords
power system
wide area
area power
frequency
time
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110545737.1A
Other languages
Chinese (zh)
Other versions
CN113346482B (en
Inventor
易建波
黄琦
井实
张真源
李坚
胡维昊
樊益凤
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Electronic Science and Technology of China
Original Assignee
University of Electronic Science and Technology of China
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University of Electronic Science and Technology of China filed Critical University of Electronic Science and Technology of China
Priority to CN202110545737.1A priority Critical patent/CN113346482B/en
Publication of CN113346482A publication Critical patent/CN113346482A/en
Application granted granted Critical
Publication of CN113346482B publication Critical patent/CN113346482B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/067—Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Physics & Mathematics (AREA)
  • Marketing (AREA)
  • Tourism & Hospitality (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Health & Medical Sciences (AREA)
  • Educational Administration (AREA)
  • Power Engineering (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses a method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model, which comprises the steps of establishing the high-order SFR model and predicting the inertia center frequency of the wide area power system by expanding the traditional simplified SFR model; then, a distance matrix and a path matrix between the nodes of the wide area power system are constructed and assigned with initial values, and the shortest electrical distance between any two nodes of the wide area power system, the path where the nodes are located and an inertia time constant on each line are calculated by updating the distance matrix and the path matrix iteratively; then marking the fault node, and calculating the shortest electrical distance and inertia between the per unit fault node and each test node; and finally, calculating frequency space-time distribution factors, constructing a high-order frequency space-time distribution model of the wide area power system and predicting the frequency space-time dynamic distribution of the wide area power system in real time.

Description

Method for predicting frequency space-time distribution of wide area power system based on SFR model
Technical Field
The invention belongs to the technical field of electric power safety stability, and particularly relates to a method for predicting frequency space-time dynamic distribution of a wide area electric power system based on a high-order SFR model.
Background
At present, electric power systems in China are in complex forms of high voltage level, wide interconnection area, large system scale, high structural complexity and alternating current-direct current hybrid connection. The frequency is used as a key index for monitoring and controlling the power quality and the running state of the power system and is a key object for judging and controlling the stability of the power system, and the power grid frequency data of wide-area measurement shows that the frequency of each measuring point has obvious dynamic space-time distribution phenomenon. The establishment of the wide area system frequency space-time distribution model has great significance for improving the stability control level of the wide area interconnected power grid. When a wide area power system fails, the accurate frequency space-time dynamics not only can help to determine wind power permeability, reasonable configuration of a frequency modulation unit, spare capacity and Automatic Generation Control (AGC) parameter configuration, but also the accurate frequency space-time distribution characteristics are helpful to setting a low-frequency load shedding scheme, and frequency collapse accidents are avoided.
The frequency response of each monitoring point of the wide-area power system has space-time distribution characteristics. And a high-order frequency response model is established, the prediction precision of the system inertia center frequency is improved, and powerful theoretical support is provided for the space-time distribution characteristics of the follow-up frequency research. The uneven distribution of the units and the difference of the inertia thereof are important factors influencing the frequency space-time distribution. Since inertia is an inherent property of the power system, it represents an impedance effect of the system on external disturbances causing energy fluctuations. Therefore, when the power system is disturbed, the difference of inertia of each node in the system and the difference of the speed regulator parameters thereof cause the difference of the frequency of each node, and the space-time distribution characteristic of the frequency is presented. The mapping relation between the inertia center frequency and the frequency dynamics of each monitoring point of the wide area system is mastered, the time-space dynamics of the frequency of the wide area system can be accurately predicted, a more accurate frequency switching control strategy can be formulated, and the safety and stability of the power system are improved.
In the prior art, the patent with the patent application number of "CN 202010573418.7" entitled "a power system frequency space-time dynamic prediction method" can only predict and judge the disturbed space-time sequence of the power system, but cannot accurately predict the frequency dynamic process of each measuring point of the system.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for predicting the frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model, wherein the mapping relation between the inertia center frequency of the high-order SFR model and the frequency dynamics of each measuring point of the wide area power system is determined by constructing a frequency space-time distribution factor, so that the frequency space-time model of the wide area power system is constructed, the frequency dynamic process of each monitoring point after the wide area power system is disturbed can be accurately predicted through the model, the space-time distribution characteristic of the frequency of the wide area power system is accurately disclosed, powerful theoretical support is provided for establishing an accurate frequency switching and controlling strategy, and the safe and stable operation of the power system is further ensured.
In order to achieve the above object, the present invention provides a method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model, which is characterized by comprising the following steps:
(1) the method for predicting the frequency space-time dynamic distribution of the wide area power system based on the high-order SFR model is characterized by comprising the following steps of:
(1) establishing a high-order SFR model;
(1.1) expanding mechanical gain K in the traditional simplified SFR modelmA first-order inertia link k/A + Ts is adopted, wherein k, A and T are all mechanical gain coefficients, and S represents an S domain; increasing excitation system damping
Figure BDA0003073434570000021
And wide area power system load effect damping DLTo simulateDamping of the wide area power system;
(1.2) setting parameters of the high-order SFR model;
Figure BDA0003073434570000022
Figure BDA0003073434570000023
Figure BDA0003073434570000024
Figure BDA0003073434570000025
wherein R is the equivalent difference adjustment coefficient of the wide area power system; t isRThe time constant is the equivalent reheating time constant of the wide area power system; h is the equivalent inertia time constant of the wide area power system, FHThe working proportion of the equivalent high-pressure cylinder of the wide-area power system is obtained; m is the number of generators in the wide area power system; hqRated capacity of the q generator in the wide area power system; rqThe difference adjustment coefficient of the q-th generator in the wide area power system is obtained; fHqWorking proportion of a high-pressure cylinder of a qth generator in a wide-area power system; t isRqA reheating time constant of a q-th generator in the wide area power system; mbase,qRated capacity of the q-th generator; sbaseA reference capacity for a wide area power system;
(2) constructing a distance matrix B and a path matrix L between nodes of the wide area power system and assigning initial values to the distance matrix B and the path matrix L;
(3) and calculating the shortest electrical distance Z between any two nodes i and j of the wide area power system by iteratively updating the distance matrix B and the path matrix Li-j-minAnd its path Li-j-min；
(4) Calculating each line l in the wide area power systemi-jTime constant of inertia of
Figure BDA0003073434570000031
(5) Marking any fault node v in wide area power systemfaultPer-unit fault node to each test node
Figure BDA0003073434570000032
The shortest electrical distance between
Figure BDA0003073434570000033
And inertia thereof
Figure BDA0003073434570000034
(6) Introducing frequency space-time distribution factors to part of key parameters of the high-order SFR model;
(6.1) for each test node, calculating the frequency space-time distribution factor of the equivalent inertia time constant in the high-order SFR model as follows:
Figure BDA0003073434570000035
wherein the content of the first and second substances,
Figure BDA0003073434570000036
for the ith test node
Figure BDA0003073434570000037
The inertia space-time distribution factor of;
(6.2) for each test node, calculating the frequency space-time distribution factor of the equivalent reheating time constant in the high-order SFR model as follows:
Figure BDA0003073434570000038
wherein the content of the first and second substances,
Figure BDA0003073434570000039
for the ith test node
Figure BDA00030734345700000310
The reheat time constant spatial-temporal distribution factor;
(6.3) for each test node, calculating a frequency space-time distribution factor of the work proportion of the medium-value high-pressure cylinder in the high-order SFR model as follows:
Figure BDA00030734345700000311
wherein the content of the first and second substances,
Figure BDA00030734345700000312
for the ith test node
Figure BDA00030734345700000313
The working proportion space-time distribution factor of the high-pressure cylinder;
(7) taking the high-order SFR model after the frequency space-time distribution factor is introduced as a frequency space-time distribution model of the wide area power system;
(8) predicting the time-space dynamic distribution of the frequency by utilizing a frequency time-space distribution model of the wide area power system;
(8.1) calculating each test node after the wide area power system is disturbed
Figure BDA0003073434570000041
The amount of frequency variation of (a);
Figure BDA0003073434570000042
wherein D isgIndicating the damping of the generator and the excitation system,
Figure BDA0003073434570000043
Figure BDA0003073434570000044
representing the damping of the generator; dLRepresenting the load effect coefficient; pdIs a power deficit of the wide area power system; Δ ωiRepresenting the ith test node
Figure BDA0003073434570000045
The amount of frequency variation of (a); wiIs variable and satisfies:
Figure BDA0003073434570000046
ζiis variable and satisfies:
Figure BDA0003073434570000047
(8.2) calculating each test node after disturbance of the wide area power system
Figure BDA0003073434570000048
Dynamic distribution of frequencies of (3);
fi＝50+Δωi
wherein f isiFor the ith test node
Figure BDA0003073434570000049
The frequency dynamics of (2).
The invention aims to realize the following steps:
the invention discloses a method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model, which comprises the steps of establishing the high-order SFR model and predicting the inertia center frequency of the wide area power system by expanding the traditional simplified SFR model; then, a distance matrix and a path matrix between the nodes of the wide area power system are constructed and assigned with initial values, and the shortest electrical distance between any two nodes of the wide area power system, the path where the nodes are located and an inertia time constant on each line are calculated by updating the distance matrix and the path matrix iteratively; then marking the fault node, and calculating the shortest electrical distance and inertia between the per unit fault node and each test node; and finally, calculating frequency space-time distribution factors, constructing a high-order frequency space-time distribution model of the wide area power system and predicting the frequency space-time dynamic distribution of the wide area power system in real time.
Meanwhile, the method for predicting the frequency space-time dynamic distribution of the wide area power system based on the high-order SFR model also has the following beneficial effects:
(1) and a high-order frequency response model is established to predict the disturbed inertia center frequency of the system, so that the model prediction precision is improved, and a powerful theoretical support is provided for the research of the subsequent frequency space-time distribution.
(2) Aiming at the distribution of system inertia, a new distribution method is provided: the inertia of each generator in the system is uniformly distributed on the path of the shortest electrical distance with other generators in the system, so that the process is favorable for simulating the characteristics of an actual disturbed power grid, and a powerful theoretical support is provided for the time-space distribution prediction research of the system frequency.
(3) The mapping relation between the inertia center frequency and the frequency dynamics of each measuring point of the wide area system is determined, the frequency space-time distribution factor is constructed, the frequency space-time distribution model of the wide area system is built, the frequency dynamics process of each measuring point of the wide area system can be rapidly and accurately predicted, and the space-time distribution characteristics of the frequency of the wide area system are accurately disclosed.
Drawings
FIG. 1 is a flow chart of a method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model according to the present invention;
FIG. 2 is a block diagram of a high-order SFR model;
FIG. 3 is a wide area complex test system topology;
FIG. 4 is an updated distance matrix visualization;
FIG. 5 is an updated path matrix visualization;
FIG. 6 is a time-space dynamic diagram of the actual system frequency under the fault of the generator tripping;
FIG. 7 is a frequency spatiotemporal dynamics diagram of wide area system frequency spatiotemporal distribution model prediction tripping failure;
FIG. 8 is a plot of the actual system frequency space-time profile under a line break fault;
FIG. 9 is a frequency space-time dynamic diagram under wide area system frequency space-time distribution model prediction disconnection fault.
Detailed Description
The following description of the embodiments of the present invention is provided in order to better understand the present invention for those skilled in the art with reference to the accompanying drawings. It is to be expressly noted that in the following description, a detailed description of known functions and designs will be omitted when it may obscure the subject matter of the present invention.
Examples
FIG. 1 is a flow chart of a method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model.
In the present embodiment, the fault of the wide area power system is described as follows in conjunction with fig. 3: when t is 5s, the generator G9 cuts the generator by 41 percent due to faults, the simulation time is 50s, the simulation step length is 0.0001s, and the time difference of the maximum frequency offset between two monitoring points in the wide-area power system is 0.001 s, which is considered as the occurrence of the space-time distribution phenomenon.
In this embodiment, the influence of the transformer on the frequency space-time distribution is not taken into account, that is, when the shortest electrical distance between two generators and the path where the generator is located are calculated, the monitoring node is selected as the bus node after the generator passes through the transformer without considering the influence of the transformer. The selected monitoring nodes in this example are bus 39 (generator G1), bus 19 (generator G4), bus 23 (generator G7), bus 25 (generator G8), and bus 2 (generator G10).
With reference to fig. 1, the method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model according to the present invention is described in detail below, and as shown in fig. 1, the method specifically includes the following steps:
s1, establishing a high-order SFR model;
s1.1, expanding mechanical gain K in traditional simplified SFR modelmA first-order inertia link k/A + Ts is adopted, wherein k, A and T are all mechanical gain coefficients, and S represents an S domain; increasing excitation system damping
Figure BDA0003073434570000061
And wide area power system load effect damping DLTo simulate damping of a wide area power system; after the expansion is completed, it is highThe structure of the order SFR model is shown in FIG. 2.
S1.2, setting parameters of a high-order SFR model;
Figure BDA0003073434570000062
Figure BDA0003073434570000063
Figure BDA0003073434570000064
Figure BDA0003073434570000065
wherein R is the equivalent difference adjustment coefficient of the wide area power system; t isRThe time constant is the equivalent reheating time constant of the wide area power system; h is the equivalent inertia time constant of the wide area power system, FHThe working proportion of the equivalent high-pressure cylinder of the wide-area power system is obtained; m is the number of generators in the wide area power system; hqRated capacity of the q generator in the wide area power system; rqThe difference adjustment coefficient of the q-th generator in the wide area power system is obtained; fHqWorking proportion of a high-pressure cylinder of a qth generator in a wide-area power system; t isRqA reheating time constant of a q-th generator in the wide area power system; mbase,qRated capacity of the q-th generator; sbaseA reference capacity for a wide area power system;
in the embodiment, parameter setting is performed on a high-order SFR model of a wide area power system, and the setting result is shown in table 1;
TABLE 1 high order SFR model parameter values
Parameter(s) High order SFR parameters Parameter(s) High order SFR parameters
FH 0.4 Dg 0.17
TR 16 DL 0.5
T 0.11 k 0.008
A 0.48 H 1
R 0.0555
TABLE 1
S2, constructing a distance matrix B and a path matrix L between the nodes of the wide area power system;
each bus in the wide area power system is taken as a node, and a distance matrix between the nodes of the wide area power system is constructed to be B ═ B [, B [ ]ij]n×n，bijThe admittance value from the node i to the node j is represented, n is the number of the nodes in the wide area power system, and the value is 39; constructing a path matrix of L ═ Lij]n×n，lijRepresenting intermediate nodes on the shortest path from node i to node j in the wide area power system;
s3, assigning initial values to the distance matrix B and the path matrix L;
the distance matrix B is given an initial value:
Figure BDA0003073434570000071
wherein the content of the first and second substances,
Figure BDA0003073434570000072
the path matrix L is given an initial value of:
Figure BDA0003073434570000073
wherein the content of the first and second substances,
Figure BDA0003073434570000074
s4, iteratively updating the distance matrix B and the path matrix L;
let k be [1, n ], initializing k to 1;
the updated distance matrix B is:
Figure BDA0003073434570000075
the update path matrix L is:
Figure BDA0003073434570000076
when k is equal to n, obtaining an updated distance matrix B(n)Sum path matrix L(n)(ii) a In the present embodiment, the updated distance matrix B(n)As shown in fig. 4; updated path matrix L(n)Is shown in fig. 5Shown in the specification;
s5, calculating the shortest electrical distance between any two nodes of the wide area power system and the path where the shortest electrical distance is located;
according to the distance matrix B(n)Sum path matrix L(n)Calculating the shortest electrical distance Z from the node i to the node ji-j-min：
Figure BDA0003073434570000081
The corresponding shortest electrical distance path is marked as Li-j-min；
In this embodiment, the path along which the shortest electrical distance between the generator G9 node 29 and the measurement point nodes 39, 19, 23, 25, and 2 in the wide area power system is calculated is shown in fig. 5, and is:
L29-39-min＝{29→26→25→2→1→39}
L29-19-min＝{29→26→27→17→16→19}
L29-23-min＝{29→26→17→17→16→24→23}
L29-25-min＝{29→26→25}
L29-2-min＝{29→26→25→2}
s6, calculating an inertia time constant of each line in the wide area power system;
s6.1, in the embodiment, inertia is measured by an inertia time constant of the generator, so that all bus nodes connected with the generator are marked in the wide area power system, and the total number of the bus nodes is m; then, in the m bus nodes, one bus node is marked as a starting end node arbitrarily, and the rest bus nodes are terminal nodes;
s6.2, calculating the shortest path from each initial end node to each terminal end node and the line l on the shortest path according to the method of the step S5i-jThe inertial time constant of (c);
Figure BDA0003073434570000082
Figure BDA0003073434570000083
Figure BDA0003073434570000084
wherein the content of the first and second substances,
Figure BDA0003073434570000085
is the qth start node
Figure BDA0003073434570000086
To the p-th generator terminal node
Figure BDA0003073434570000087
The shortest electrical distance between the two lines is 1,2, …, m, p is 1,2, …, m-1;
Figure BDA0003073434570000088
for the q-th starting generator distributed on line li-jAn inertial time constant of (c);
Figure BDA0003073434570000089
represents a line li-jAn admittance value of (a);
Figure BDA00030734345700000810
representing the qth generator start node
Figure BDA00030734345700000811
To the p-th generator terminal node
Figure BDA00030734345700000812
The shortest electrical distance between the two;
Figure BDA00030734345700000813
represents the inertia time constant of the qth start generator;
Figure BDA00030734345700000814
represents a distance matrix B(n)Middle start end node
Figure BDA0003073434570000091
To the terminal node
Figure BDA0003073434570000092
An admittance value of (1);
for example: calculating the line set l between the generator starting node 29 and the generator terminal node 39i-j；
L29-39-min＝{29→26→25→2→1→39}
li-j＝L29-39-min＝{l29-26,l26-25,l25-2,l2-1,l1-39}
Figure BDA0003073434570000093
Calculating the distribution of the generator start node 29 on the path li-jThe time constant of inertia on all lines;
Figure BDA0003073434570000096
s6.3, calculating each line l in the wide area power systemi-jTime constant of inertia of
Figure BDA0003073434570000097
Figure BDA0003073434570000098
In this embodiment, the line l29-26For the purpose of example only,
Figure BDA0003073434570000099
in this embodiment, taking m as 10, the inertia distribution on each line in the wide area power system is calculated as shown in table 2.
Table 2 shows the distribution of inertia of each line in the wide area power system.
Line Inertia Per unit value Line Inertia Per unit value
l29-26 18.99 0.4498 l29-26 11.31 0.2693
l26-25 18.99 0.4498 l5-6 15.20 0.3619
l25-2 21.48 0.5114 l26-27 14.85 0.3536
l2-1 14.64 0.3486 l27-17 14.85 0.3536
l1-39 14.64 0.3486 l17-16 26.70 0.6357
l2-3 20.10 0.4786 l16-15 13.78 0.3281
l3-4 8.2600 0.1967 l15-14 13.78 0.3281
l14-13 9.570 0.2279 l21-22 14.94 0.3558
l13-10 9.570 0.2279 l16-24 14.94 0.3558
l16-19 33.15 0.7893 l24-23 14.94 0.3558
TABLE 2
S7, determining the shortest electrical distance and inertia between the per unit fault node and each test node;
s7.1, calculating an impedance reference value ZbaseWith a reference value of inertia Tbase：
Figure BDA0003073434570000101
Figure BDA0003073434570000102
Wherein N is the number of lines in the wide area power system;
in this example, m is 10 and N is 21, and the following is calculated: zbase＝0.0005+j0.0125，Tbase＝42；
S7.2, marking any node in the wide area power system as a fault node, and remaining nodes as test nodes;
in this embodiment, the test node may also select the remaining part of nodes as the test node, for example: generator node 29 is the fault node, 39, 19, 23, 25 and 2 are the test nodes;
s7.3, the shortest electrical distance and inertia between the per unit fault node and each test node;
Figure BDA0003073434570000103
Figure BDA0003073434570000104
Figure BDA0003073434570000105
wherein the content of the first and second substances,
Figure BDA0003073434570000106
for failed node vfaultTo the ith test node
Figure BDA0003073434570000107
The shortest electrical distance between i ═ 1,2, …, n-1;
Figure BDA0003073434570000108
for failed node vfaultTo the ith test node
Figure BDA0003073434570000109
Per unit value of the shortest electrical distance therebetween;
Figure BDA00030734345700001010
for failed node vfaultTo the ith test node
Figure BDA00030734345700001011
The per unit value of inertia between; per unit value of;
Figure BDA00030734345700001012
for failed node vfaultTo the ith test node
Figure BDA00030734345700001013
The per unit value of inertia between;
in the present embodiment, taking the fault node 29 and the test node 39 as an example:
Figure BDA00030734345700001014
Figure BDA00030734345700001015
in the present embodiment, the shortest electrical distance and the inertia result between the per-unit fault node 39 and the test nodes 39, 19, 23, 25 and 2 are shown in table 3.
Table 3 is the per unit value of the shortest electrical distance and inertia between the failed node and the test point.
29-39 29-19 29-23 29-25 29-2
Z*/pu 5 5 6 2 3
T*/pu 2.1129 2.5843 2.5064 0.9019 1.4157
TABLE 3
S8, introducing frequency space-time distribution factors to part of key parameters of the high-order SFR model;
s8.1, for each test node, calculating a frequency space-time distribution factor of an equivalent inertia time constant in the high-order SFR model as follows:
Figure BDA0003073434570000111
wherein the content of the first and second substances,
Figure BDA0003073434570000112
for the ith test node
Figure BDA0003073434570000113
The inertia space-time distribution factor of;
s8.2, for each test node, calculating a frequency space-time distribution factor of the equivalent reheating time constant in the high-order SFR model as follows:
Figure BDA0003073434570000114
wherein the content of the first and second substances,
Figure BDA0003073434570000115
for the ith test node
Figure BDA0003073434570000116
The reheat time constant spatial-temporal distribution factor;
s8.3, for each test node, calculating a frequency space-time distribution factor of the work proportion of the medium-value high-pressure cylinder in the high-order SFR model as follows:
Figure BDA0003073434570000117
wherein the content of the first and second substances,
Figure BDA0003073434570000118
for the ith test node
Figure BDA0003073434570000119
The working proportion space-time distribution factor of the high-pressure cylinder;
s9, taking the high-order SFR model after the frequency space-time distribution factor is introduced as a frequency space-time distribution model of the wide area power system;
in this embodiment, the parameters of the high-order frequency space-time distribution model of the wide area power system calculated under the generator tripping fault are shown in table 4.
And table 4 shows the parameters of the wide area system space-time distribution model under the generator tripping fault.
Parameter(s) G1 G4 G7 G8 G10
FH 0.4 0.4 0.4 0.4 0.4
TR 10.7728 9.3904 9.1024 25.7392 16.5824
H 0.7025 0.8592 1 0.1206 0.2824
TABLE 4
Therefore, frequency space-time distribution factors are introduced into partial coupling parameters of the high-order SFR model, and the high-order frequency space-time distribution model of the wide area power system is constructed;
s10, predicting the space-time dynamic distribution of the frequency by using a frequency space-time distribution model of the wide area power system;
s10.1, when the wide area power system is disturbed,calculating each test node
Figure BDA0003073434570000121
Frequency change amount Δ ω ofi；
Figure BDA0003073434570000122
Wherein D isgIndicating the damping of the generator and the excitation system,
Figure BDA0003073434570000123
Figure BDA0003073434570000124
representing the damping of the generator; dLRepresenting the load effect coefficient; pdFor the power shortage of the wide area power system, in the present embodiment, as shown in fig. 2, PspFor incremental power set points, only for P during many studiesdOf interest, therefore P is the embodimentsp＝0；ΔωiRepresenting the ith test node
Figure BDA0003073434570000125
The amount of frequency variation of (a); wiIs variable and satisfies:
Figure BDA0003073434570000126
ζiis variable and satisfies:
Figure BDA0003073434570000127
s10.2, calculating each test node after disturbance of the wide area power system
Figure BDA0003073434570000128
Dynamic distribution of frequencies of (3);
fi＝50+Δωi
wherein f isiFor the ith test node
Figure BDA0003073434570000129
The frequency dynamics of (2).
In this embodiment, the wide area power system frequency space-time distribution model can accurately predict the frequency dynamics of each measurement point of the system, and accurately reveal the space-time distribution characteristics of the wide area system frequency.
In the present embodiment, the frequency dynamics of the nodes 39, 19, 23, 25 and 2 can be predicted by the parameters of the wide area power system high-order frequency space-time distribution model shown in table 4, and the space-time distribution characteristics of the wide area system frequencies are revealed.
In this embodiment, a PSASP software is used to perform a refinement simulation to obtain a phenomenon that the frequency of each measurement point has a significant spatial-temporal distribution, and the simulation result is shown in fig. 6, where G8 → G10 → G1 → G4 → G7. Thus, it can be seen that the frequencies of the measured points predicted by the present invention are completely consistent with those of the actual system, and the error is extremely small, the predicted result is shown in fig. 7, and the error analysis table is shown in table 5.
Table 5 is an error analysis table of frequency dynamics under the cutter failure;
G1 G4 G7 G8 G10
actual system frequency maximum offset time/s 7.6474 9.020 9.0653 7.4946 7.5738
Time/s of maximum offset of frequency of space-time distribution model 8.6615 9.2457 9.8046 5.6304 6.6487
Absolute error/s 1.0141 0.2257 0.7397 1.8642 0.9251
Actual system frequency steady state value/Hz 49.9273 49.9273 49.9273 49.9273 49.9273
Frequency steady state value/s of space-time distribution model 49.9432 49.9433 49.9433 49.9418 49.9428
Absolute error/Hz 0.0159 0.016 0.016 0.0145 0.0155
Relative error/%) 0.0318 0.032 0.032 0.029 0.031
TABLE 5
In addition, the present example provides another fault condition, line l, when t is 5s15-16When a three-phase disconnection fault occurs at the node 15, the simulation time is 50s, the simulation step length is 0.0001s, and monitoring points are selected as a bus 19 (a generator G4), a bus 25 (a generator G8), a bus 29 (a generator G9) and a bus 2 (a generator G10).
The model built according to the invention can calculate the shortest electrical distance from the node 15 to each of the measurement points 19, 25, 29 and 2 as:
L15-19-min＝{15→16→19}
L15-25-min＝{15→14→4→3→2→25}
L15-29-min＝{15→16→17→27→26→29}
L15-2-min＝{15→14→4→3→2}
the shortest electrical distance from the per-unit fault point 15 to each of the measuring points 19, 25, 29 and 2 and its inertia are shown in table 6.
Table 6 shows the shortest electrical distance between the fault point and the measurement point and its inertia.
15-19 15-25 15-29 15-2
Z*/pu 2 5 5 4
T*/pu 1.1173 1.7171 2.1230 1.2057
TABLE 6
In the present embodiment, the parameters of the wide area system spatio-temporal distribution model are calculated as shown in table 7.
Table 7 shows the parameters of the wide area system spatio-temporal distribution model under the disconnection fault.
Parameter(s) G4 G8 G9 G10
FH 0.4 0.4 0.4 0.4
TR 22.32 12.5184 10.736 17.2704
H 0.9336 1.0824 1.1653 0.9856
TABLE 7
The PSASP software is used for carrying out refinement simulation to obtain a space-time distribution phenomenon of each measuring point frequency, G4 → G10 → G8 → G9, and the simulation result is shown in FIG. 8. The frequency of each measuring point obtained by the wide area system frequency space-time distribution model is completely consistent with that of an actual system, the error is extremely small, the prediction result is shown in a figure 9, and an error analysis table is shown in a table 8.
Table 8 is an error analysis table of frequency dynamics under the disconnection fault;
G4 G8 G9 G10
actual system frequency maximum offset time/s 5.3243 5.5463 5.8242 5.4562
Time/s of maximum offset of frequency of space-time distribution model 5.3352 5.4446 5.6355 5.3338
Absolute error/s 0.0109 0.1017 0.1887 0.1224
Actual system frequency steady state value/Hz 49.8756 49.8756 49.8756 49.8756
Frequency steady state value/s of space-time distribution model 49.8743 49.8760 49.8762 49.8754
Absolute error/Hz 0.0013 0.0004 0.0006 0.0002
Relative error/%) 0.0026 0.0008 0.0012 0.0004
TABLE 8
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, and various changes may be made apparent to those skilled in the art as long as they are within the spirit and scope of the present invention as defined and defined by the appended claims, and all matters of the invention which utilize the inventive concepts are protected.

Claims (1)

1. A method for predicting frequency space-time dynamic distribution of a wide area power system based on a high-order SFR model is characterized by comprising the following steps:
(1) establishing a high-order SFR model;
(1.1) expanding mechanical gain K in the traditional simplified SFR modelmIs a first-order inertia linkk/A + Ts, wherein k, A and T are all mechanical gain coefficients; increasing excitation system damping
Figure FDA0003073434560000015
And wide area power system load effect damping DLTo simulate damping of a wide area power system;
(1.2) setting parameters of the high-order SFR model;
Figure FDA0003073434560000011
Figure FDA0003073434560000012
Figure FDA0003073434560000013
Figure FDA0003073434560000014
wherein R is the equivalent difference adjustment coefficient of the wide area power system; t isRThe time constant is the equivalent reheating time constant of the wide area power system; h is the equivalent inertia time constant of the wide area power system, FHThe working proportion of the equivalent high-pressure cylinder of the wide-area power system is obtained; m is the number of generators in the wide area power system; hqRated capacity of the q generator in the wide area power system; rqThe difference adjustment coefficient of the q-th generator in the wide area power system is obtained; fHqWorking proportion of a high-pressure cylinder of a qth generator in a wide-area power system; t isRqA reheating time constant of a q-th generator in the wide area power system; mbase,qRated capacity of the q-th generator; sbaseA reference capacity for a wide area power system;
(2) constructing a distance matrix B and a path matrix L between nodes of the wide area power system and assigning initial values to the distance matrix B and the path matrix L;
(3) and calculating the shortest electrical distance Z between any two nodes i and j of the wide area power system by iteratively updating the distance matrix B and the path matrix Li-j-minAnd its path Li-j-min；
(4) Calculating each line l in the wide area power systemi-jUpper time constant of inertia Tli-j；
(5) Marking any fault node v in wide area power systemfaultPer-unit fault node to each test node
Figure FDA0003073434560000021
The shortest electrical distance between
Figure FDA0003073434560000022
And inertia thereof
Figure FDA0003073434560000023
(6) Introducing frequency space-time distribution factors to part of key parameters of the high-order SFR model;
(6.1) for each test node, calculating the frequency space-time distribution factor of the equivalent inertia time constant in the high-order SFR model as follows:
Figure FDA0003073434560000024
wherein the content of the first and second substances,
Figure FDA0003073434560000025
for the ith test node
Figure FDA0003073434560000026
The inertia space-time distribution factor of;
(6.2) for each test node, calculating the frequency space-time distribution factor of the equivalent reheating time constant in the high-order SFR model as follows:
Figure FDA0003073434560000027
wherein the content of the first and second substances,
Figure FDA0003073434560000028
for the ith test node
Figure FDA0003073434560000029
The reheat time constant spatial-temporal distribution factor;
(6.3) for each test node, calculating a frequency space-time distribution factor of the work proportion of the medium-value high-pressure cylinder in the high-order SFR model as follows:
Figure FDA00030734345600000210
wherein the content of the first and second substances,
Figure FDA00030734345600000211
for the ith test node
Figure FDA00030734345600000212
The working proportion space-time distribution factor of the high-pressure cylinder;
(7) taking the high-order SFR model after the frequency space-time distribution factor is introduced as a frequency space-time distribution model of the wide area power system;
(8) predicting the time-space dynamic distribution of the frequency by utilizing a frequency time-space distribution model of the wide area power system;
(8.1) calculating each test node after the wide area power system is disturbed
Figure FDA00030734345600000213
The amount of frequency variation of (a);
Figure FDA00030734345600000214
wherein D isgIndicating the damping of the generator and the excitation system,
Figure FDA00030734345600000215
DLrepresenting the load effect coefficient; pdIs a power deficit of the wide area power system; Δ ωiRepresenting the ith test node
Figure FDA00030734345600000216
The amount of frequency variation of (a); wiIs variable and satisfies:
Figure FDA0003073434560000031
ζiis variable and satisfies:
Figure FDA0003073434560000032
(8.2) calculating each test node after disturbance of the wide area power system
Figure FDA0003073434560000033
Dynamic distribution of frequencies of (3);
fi＝50+Δωi
wherein f isiFor the ith test node
Figure FDA0003073434560000034
The frequency dynamics of (2).
CN202110545737.1A 2021-05-19 2021-05-19 Method for predicting wide area power system frequency space-time distribution based on SFR model Active CN113346482B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110545737.1A CN113346482B (en) 2021-05-19 2021-05-19 Method for predicting wide area power system frequency space-time distribution based on SFR model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110545737.1A CN113346482B (en) 2021-05-19 2021-05-19 Method for predicting wide area power system frequency space-time distribution based on SFR model

Publications (2)

Publication Number Publication Date
CN113346482A true CN113346482A (en) 2021-09-03
CN113346482B CN113346482B (en) 2022-10-18

Family

ID=77469471

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110545737.1A Active CN113346482B (en) 2021-05-19 2021-05-19 Method for predicting wide area power system frequency space-time distribution based on SFR model

Country Status (1)

Country Link
CN (1) CN113346482B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114243805A (en) * 2021-12-20 2022-03-25 华北电力大学 Synchronous machine system frequency response analysis calculation method considering speed regulator amplitude limiting

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108808701A (en) * 2018-07-10 2018-11-13 福州大学 A kind of system inertia real-time computing technique based on response
CN108879688A (en) * 2017-05-12 2018-11-23 南京理工大学 A kind of mains frequency response Equivalent Model method for building up considering wind-powered electricity generation fluctuation
CN110829487A (en) * 2019-10-22 2020-02-21 电子科技大学 Dynamic frequency prediction method for power system
CN110875600A (en) * 2019-11-27 2020-03-10 大连理工大学 Approximate analysis model for dynamic frequency response of two-machine equivalent power system
CN111740410A (en) * 2020-06-22 2020-10-02 电子科技大学 Power system frequency space-time dynamic prediction method
US20210057912A1 (en) * 2018-03-16 2021-02-25 Hongwei DENG Electromechanical transient simulation method for power system based on direct linear algorithm

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108879688A (en) * 2017-05-12 2018-11-23 南京理工大学 A kind of mains frequency response Equivalent Model method for building up considering wind-powered electricity generation fluctuation
US20210057912A1 (en) * 2018-03-16 2021-02-25 Hongwei DENG Electromechanical transient simulation method for power system based on direct linear algorithm
CN108808701A (en) * 2018-07-10 2018-11-13 福州大学 A kind of system inertia real-time computing technique based on response
CN110829487A (en) * 2019-10-22 2020-02-21 电子科技大学 Dynamic frequency prediction method for power system
CN110875600A (en) * 2019-11-27 2020-03-10 大连理工大学 Approximate analysis model for dynamic frequency response of two-machine equivalent power system
CN111740410A (en) * 2020-06-22 2020-10-02 电子科技大学 Power system frequency space-time dynamic prediction method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
YIFENG FAN等: "An Improved Higher-order SFR Model of Large-scale Distributed Hybrid Power System", 《2020 5TH ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE)》 *
刘克天等: "基于广域量测数据的电力系统动态频率分析方法", 《电网技术》 *
古丽扎提·海拉提等: "基于多机模型的电力系统频率时域仿真", 《电力科学与技术学报》 *
张国洲等: "多运行方式下多机PSS的协调优化方法", 《电网技术》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114243805A (en) * 2021-12-20 2022-03-25 华北电力大学 Synchronous machine system frequency response analysis calculation method considering speed regulator amplitude limiting
CN114243805B (en) * 2021-12-20 2023-01-10 华北电力大学 Synchronous machine system frequency response analysis calculation method considering speed regulator amplitude limiting

Also Published As

Publication number Publication date
CN113346482B (en) 2022-10-18

Similar Documents

Publication Publication Date Title
CN104281979B (en) Distribution transformer platform area low voltage failure type detection method and system
CN107016489A (en) A kind of electric power system robust state estimation method and device
CN106058876B (en) Consider the dynamic reactive Site Selection analysis method and system of Enhancement of Transient Voltage Stability
CN108448635B (en) Photovoltaic power generation system asymmetric voltage drop fault ride-through overall process modeling method
CN108075470A (en) A kind of power grid transient frequency feature Forecasting Methodology based on SFR and ELM
CN104716646B (en) A kind of node Coupling Degrees method based on Injection Current
CN113346482B (en) Method for predicting wide area power system frequency space-time distribution based on SFR model
CN114184876A (en) DC magnetic bias monitoring, evaluation and earth model correction platform
CN115236457A (en) Method, system, equipment and storage medium for positioning short-circuit fault section of oil field distribution network
CN108896852B (en) Online measurement method and system for short circuit capacity of public access point
CN109638871B (en) Main network dividing method of large-scale alternating current-direct current hybrid system considering wind power access
CN111740410B (en) Power system frequency space-time dynamic prediction method
CN110994621B (en) Power grid active power flow adjusting method and device based on improved direct current power flow algorithm
CN112684290A (en) Efficient calculation method for interelectrode short-circuit fault current of flexible direct-current power grid
JP3350265B2 (en) Power system stabilizer
Pompodakis et al. Modelling the steady-state of secondary control in islanded AC microgrids
CN113589099B (en) Method for realizing fault location in power distribution system with multi-branch transmission line
CN107436995B (en) Equivalent three-phase short circuit calculation method considering external network to ground branch and sensitivity information
CN111211581B (en) Method and device for determining new energy acceptance capacity in power system
CN114928068A (en) Point distribution and volume determination method and device for receiving-end power grid synchronous phase modulator
CN110838718B (en) Power system frequency stability adjusting method and system
CN114421531A (en) Active power distribution network distributed voltage control method considering global sensitivity
CN111999562A (en) Method for measuring system impedance by using generator phase-in operation
Racewicz et al. Non linear half-order modeling of synchronous machine
CN112701684B (en) Transformer substation equivalent motor load proportion determining method and short-circuit current calculating method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant