CN110930263A - Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm - Google Patents

Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm Download PDF

Info

Publication number
CN110930263A
CN110930263A CN201911116954.8A CN201911116954A CN110930263A CN 110930263 A CN110930263 A CN 110930263A CN 201911116954 A CN201911116954 A CN 201911116954A CN 110930263 A CN110930263 A CN 110930263A
Authority
CN
China
Prior art keywords
power supply
induction motor
current
photovoltaic power
particle
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
CN201911116954.8A
Other languages
Chinese (zh)
Other versions
CN110930263B (en
Inventor
黄华颖
黄辉
王庆斌
叶锦坤
饶苏敏
叶烜荣
刘雄光
黄荣鲜
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.)
Guangdong Power Grid Co Ltd
Yunfu Power Supply Bureau of Guangdong Power Grid Co Ltd
Original Assignee
Guangdong Power Grid Co Ltd
Yunfu Power Supply Bureau of Guangdong Power Grid Co Ltd
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 Guangdong Power Grid Co Ltd, Yunfu Power Supply Bureau of Guangdong Power Grid Co Ltd filed Critical Guangdong Power Grid Co Ltd
Priority to CN201911116954.8A priority Critical patent/CN110930263B/en
Publication of CN110930263A publication Critical patent/CN110930263A/en
Application granted granted Critical
Publication of CN110930263B publication Critical patent/CN110930263B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Economics (AREA)
  • General Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Biophysics (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Water Supply & Treatment (AREA)
  • Public Health (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Biomedical Technology (AREA)
  • Primary Health Care (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Control Of Electrical Variables (AREA)

Abstract

The invention discloses a method for calculating short-circuit current of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor, which comprises the following steps: 1: initializing network parameters, black hole radius, particle speed and particle position, and marking the positions of nodes and short-circuit points where a main power supply, a distributed photovoltaic power supply and an induction motor are located; 2: performing one iteration; 3: judging whether an iteration end condition is met, if so, executing 4, and otherwise, executing 6; 4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state; 5: finishing; 6: judging whether the induction motor is in a power generation state, if so, executing step 7, otherwise, executing step 10; 7: calculating the injection current and the node voltage of a main power supply, a photovoltaic power supply and an induction motor; 8: updating the particle speed and position; 9: after iteration, returning to 3; 10: and (4) calculating the injection current of the main power supply and the photovoltaic power supply, and executing 8 after calculating the node voltage.

Description

Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm
Technical Field
The invention relates to the technical field of distribution networks, in particular to a method for calculating short-circuit current of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm.
Background
With the exhaustion of fossil energy and the increasing aggravation of problems of environmental pollution, greenhouse effect and the like, a power system increasingly absorbs renewable clean energy, and for a medium-voltage distribution network, more and more distributed photovoltaic power sources and distributed wind power generation are added. With the addition of distributed power supplies and the increase of loads of induction motors, a medium-voltage power distribution network is changed into a multi-power-supply mesh structure from a radiation type network, the original trend is changed correspondingly, and the stability and other aspects of the power distribution network are greatly influenced. When a short-circuit fault occurs, the distributed photovoltaic power supply can provide a certain fault current for a short-circuit point, and the induction motor load can also feed back a certain current to the fault point due to the characteristics of the induction motor load, so that the short-circuit current level of the medium-voltage distribution network can be changed to a certain extent, and the setting and calculation of relay protection are influenced. Therefore, when a distributed photovoltaic power supply and an induction motor load are added into a medium-voltage distribution network, a key problem to be solved is to accurately and efficiently calculate the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor.
Disclosure of Invention
The invention provides a method for calculating the short-circuit current of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm, aiming at solving the problems that in the prior art, when a short-circuit fault occurs, a distributed photovoltaic power supply can provide a certain fault current to a short-circuit point, and the induction motor load can also feed back a certain current to the fault point due to the characteristics of the induction motor load, so that the short-circuit current level of the medium-voltage distribution network can change to a certain degree, and the setting and calculation of relay protection are influenced.
In order to solve the technical problems, the invention adopts the technical scheme that: a method for calculating short-circuit current of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm comprises the following steps:
s1: initializing network parameters, and marking nodes where a main power supply, a distributed photovoltaic power supply and an induction motor are located; marking the position of a short-circuit point, and initializing the radius of a black hole, the particle speed and the particle position;
s2: iterating the radius of the black hole, the particle speed and the particle position;
s3: judging whether the black hole radius, the particle speed and the particle position meet the iteration end condition, if so, executing S4, and if not, executing S6:
s4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state;
s5: finishing;
s6: judging whether the induction motor is in a power generation state, if so, executing S7, otherwise, executing S10;
s7: calculating main power supply injection current, photovoltaic power supply injection current and induction motor injection current; calculating the node voltage according to a node voltage equation;
s8: updating the particle speed and the particle position;
s9: iterating the radius of the black hole, the particle speed and the particle position again, and returning to S3;
s10: and calculating the main power supply injection current and the photovoltaic power supply injection current, and executing S8 after calculating the node voltage according to the node voltage equation.
In step S3, the iteration end condition is the maximum number of iterations.
Preferably, the node voltage equation
Figure BDA0002274328920000021
Wherein the content of the first and second substances,
Figure BDA0002274328920000022
injecting a current matrix into the node, wherein Y is a node admittance matrix of the power distribution network system; it should be noted that Y includes not only the admittance value of the load, but also the short-circuit ground admittance.
Figure BDA0002274328920000023
Is a system node voltage matrix; if the total number of n nodes in the power grid is set, the main power supply is connected to the node k, the distributed photovoltaic power supply is connected to the node m, and the induction motor is connected to the node f, the node voltage equation can be expressed as follows:
Figure BDA0002274328920000024
in the formula:
Figure BDA0002274328920000025
injection current of the main power supply at node k;
Figure BDA0002274328920000026
the injection current of the distributed photovoltaic power supply at the node m;
Figure BDA0002274328920000027
is the injection current of the induction motor in the generator running state at the f node.
Preferably, the main power supply injects a current
Figure BDA0002274328920000028
The calculation of (2): main power supply at node k, main power supply injection current
Figure BDA0002274328920000029
Is the ratio of the main power supply voltage to the system impedance;
injection current for distributed photovoltaic power supply
Figure BDA00022743289200000210
The calculation of (2): distributed photovoltaic power supply with node m out, with current injected
Figure BDA00022743289200000211
The solution can be made according to the following equation:
Figure BDA0002274328920000031
in the formula, PDGmCapacity of the photovoltaic power source;
Figure BDA0002274328920000032
is the grid connection point voltage rating;
Figure BDA0002274328920000033
is the phase angle of the grid-connected point voltage, α is the reactive current vector
Figure BDA0002274328920000034
And active current vector
Figure BDA0002274328920000035
The included angle of (A);
injection current in induction motor generator regime
Figure BDA0002274328920000036
The calculation of (2):
Figure BDA0002274328920000037
in the formula
Figure BDA0002274328920000038
And
Figure BDA0002274328920000039
respectively the induced electromotive force and the terminal voltage of the induction motor; zMfIs the external equivalent impedance of the induction motor.
Preferably, in S6, it is determined whether the induction motor is in a motor state or a generator state according to the distance between the induction motor and the short-circuit point, and if the induction motor is far from the short-circuit point, it is determined that the voltage of the node where the induction motor is located does not change much, and the induced electromotive force of the motor is smaller than the terminal voltage, and therefore, the induction motor is in the motor state and still treated as a load; when the induction motor is close to the short-circuit point, the voltage of the node where the induction motor is located drops more, the induced electromotive force of the motor is larger than the end voltage, and the motor is in a generator state, and at the moment, the motor is regarded as a power supply and is a current source.
Preferably, the black hole particle swarm optimization algorithm can be expressed by the following formula:
Figure BDA00022743289200000310
the method comprises the following steps:
Figure BDA00022743289200000311
Figure BDA00022743289200000312
Figure BDA00022743289200000313
the method comprises the following steps:
Figure BDA00022743289200000314
Figure BDA00022743289200000315
in the formula:
Figure BDA00022743289200000316
is a probability value corresponding to the d variable of the particle i at the h iteration of [0, 1%]Random numbers obeying uniform distribution;
p is the probability threshold of the particle entering the black hole, a constant over [0,1 ];
Figure BDA00022743289200000317
respectively representing the search speed of the d variable of the particle i in the h +1 th iteration and the h iteration;
omega is an inertia weight and is used for balancing the local searching capacity and the global searching capacity;
c1、c2is a learning factor;
r1、r2and r3Is [0,1]]Random numbers obeying uniform distribution;
Figure BDA00022743289200000318
respectively representing the current value, the individual extreme value and the global extreme value of the d variable position of the h iterative particle i;
r is a constant and represents the radius of the black hole;
Figure BDA00022743289200000319
is [ -R, R]Obeying uniformly distributed random numbers. It should be noted that the black hole particle swarm optimization algorithm can be replaced by other conventional algorithms or other intelligent optimization algorithms, such as a genetic algorithm, a common particle swarm algorithm, a differential evolution algorithm, and the like.
Preferably, in step S2, Y includes not only the admittance value of the load but also the short-circuit ground admittance.
The invention also provides a system for calculating the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm, which comprises a memory and a processor, wherein the memory comprises a program of a method for calculating the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm, and when the program of the method for calculating the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm is executed by the processor, the following steps are realized:
s1: initializing network parameters, and marking nodes where a main power supply, a distributed photovoltaic power supply and an induction motor are located; marking the position of a short-circuit point, and initializing the radius of a black hole, the particle speed and the particle position;
s2: iterating the radius of the black hole, the particle speed and the particle position;
s3: judging whether the black hole radius, the particle speed and the particle position meet the iteration end condition, if so, executing S4, and if not, executing S6:
s4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state;
s5: finishing;
s6: judging whether the induction motor is in a power generation state, if so, executing S7, otherwise, executing S10;
s7: calculating main power supply injection current, photovoltaic power supply injection current and induction motor injection current; calculating the node voltage according to a node voltage equation;
s8: updating the particle speed and the particle position;
s9: iterating the radius of the black hole, the particle speed and the particle position again, and returning to S3;
s10: and calculating the main power supply injection current and the photovoltaic power supply injection current, and executing S8 after calculating the node voltage according to the node voltage equation.
The invention also provides a computer readable storage medium, which comprises a short-circuit current calculation method program of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm.
Preferably, the computer-readable storage medium includes a program for calculating the short-circuit current of the medium-voltage distribution network including the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm, and when the program is executed by a processor, the steps of the method for calculating the short-circuit current of the medium-voltage distribution network including the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm are realized.
Compared with the prior art, the beneficial effects are:
according to the invention, the voltage of each node, the current of each branch, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state can be accurately calculated through a black hole particle swarm optimization algorithm.
Drawings
Fig. 1 is a flowchart of a method for establishing a short-circuit current calculation model of a voltage distribution network according to the present invention;
FIG. 2 is a block diagram of the low voltage ride through control of the present invention.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent; for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted. The positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the present patent.
The same or similar reference numerals in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "long", "short", etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the drawings, it is only for convenience of description and simplicity of description, but does not indicate or imply that the device or element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and therefore, the terms describing the positional relationships in the drawings are only used for illustrative purposes and are not to be construed as limitations of the present patent, and specific meanings of the terms may be understood by those skilled in the art according to specific situations.
The technical scheme of the invention is further described in detail by the following specific embodiments in combination with the attached drawings:
example 1
As shown in fig. 1, a method for calculating short-circuit current of a medium voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm includes the following steps:
s1: initializing network parameters, and marking nodes where a main power supply, a distributed photovoltaic power supply and an induction motor are located; marking the position of a short-circuit point, and initializing the radius of a black hole, the particle speed and the particle position;
s2: iterating the radius of the black hole, the particle speed and the particle position;
s3: judging whether the black hole radius, the particle speed and the particle position meet the iteration end condition, if so, executing S4, and if not, executing S6:
s4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state;
s5: finishing;
s6: judging whether the induction motor is in a power generation state, if so, executing S7, otherwise, executing S10;
s7: calculating main power supply injection current, photovoltaic power supply injection current and induction motor injection current; calculating the node voltage according to a node voltage equation;
s8: updating the particle speed and the particle position;
s9: iterating the radius of the black hole, the particle speed and the particle position again, and returning to S3;
s10: and calculating the main power supply injection current and the photovoltaic power supply injection current, and executing S8 after calculating the node voltage according to the node voltage equation.
Wherein the node voltage equation
Figure BDA0002274328920000061
Wherein the content of the first and second substances,
Figure BDA0002274328920000062
injecting a current matrix into the node, wherein Y is a node admittance matrix of the power distribution network system; it should be noted that Y includes not only the admittance value of the load, but also the short-circuit ground admittance.
Figure BDA0002274328920000063
Is a system node voltage matrix; if the total number of n nodes in the power grid is set, the main power supply is connected to the node k, the distributed photovoltaic power supply is connected to the node m, and the induction motor is connected to the node f, the node voltage equation can be expressed as follows:
Figure BDA0002274328920000064
in the formula:
Figure BDA0002274328920000065
injection current of the main power supply at node k;
Figure BDA0002274328920000066
the injection current of the distributed photovoltaic power supply at the node m;
Figure BDA0002274328920000067
is the injection current of the induction motor in the generator running state at the f node.
In addition, the main power supply injects current
Figure BDA0002274328920000068
The calculation of (2): main power supply at node k, main power supply injection current
Figure BDA0002274328920000069
Is the ratio of the main power supply voltage to the system impedance;
injection current for distributed photovoltaic power supply
Figure BDA00022743289200000610
The calculation of (2): distributed photovoltaic power supply with node m out, with current injected
Figure BDA00022743289200000611
The solution can be made according to the following equation:
Figure BDA00022743289200000612
in the formula, PDGmCapacity of the photovoltaic power source;
Figure BDA00022743289200000613
is the grid connection point voltage rating;
Figure BDA00022743289200000614
is the phase angle of the grid-connected point voltage, α is the reactive current vector
Figure BDA00022743289200000615
And active current vector
Figure BDA00022743289200000616
The included angle of (A);
injection current in induction motor generator regime
Figure BDA00022743289200000617
The calculation of (2):
Figure BDA00022743289200000618
in the formula
Figure BDA0002274328920000071
And
Figure BDA0002274328920000072
respectively the induced electromotive force and the terminal voltage of the induction motor; zMfIs the external equivalent impedance of the induction motor.
It should be noted that, in this embodiment, the low voltage ride through control strategy for reactive current control is divided into three stages as follows:
Figure BDA0002274328920000073
as shown in fig. 2, it can be seen that when the grid-connected voltage drops to a low level, the drop is within 10%, and the reactive current I isqIs 0, i.e.No reactive current is provided, the photovoltaic power supply still operates at unity power factor; when the drop degree of the power grid is larger and the drop degree is more than 80%, the photovoltaic power supply only provides reactive current and keeps the maximum allowable output current, and the output current of the inverter cannot exceed the rated current I in general engineering requirementsN1.1 times, so the current times here are also chosen to be 1.1); when the falling degree is within 10-80%, the reactive current IqReal-time tracking grid-connected point voltage UpccDynamic output, corresponding active current IdThe output is shown in the following equation (8):
Figure BDA0002274328920000074
in S6, it is determined whether the induction motor is in a motor state or a generator state according to the distance between the induction motor and the short-circuit point, and if the induction motor is far from the short-circuit point, it is determined that the change of the node voltage of the induction motor is not large, and the induced electromotive force of the motor is smaller than the terminal voltage, and thus the induction motor is in the motor state and still treated as a load; when the induction motor is close to the short-circuit point, the voltage of the node where the induction motor is located drops more, the induced electromotive force of the motor is larger than the end voltage, and the motor is in a generator state, and at the moment, the motor is regarded as a power supply and is a current source.
In addition, the black hole particle swarm optimization algorithm can be expressed by the following formula:
Figure BDA0002274328920000075
the method comprises the following steps:
Figure BDA0002274328920000076
Figure BDA0002274328920000077
Figure BDA0002274328920000078
the method comprises the following steps:
Figure BDA0002274328920000079
Figure BDA00022743289200000710
in the formula:
Figure BDA00022743289200000711
is a probability value corresponding to the d variable of the particle i at the h iteration of [0, 1%]Random numbers obeying uniform distribution;
p is the probability threshold of the particle entering the black hole, a constant over [0,1 ];
Figure BDA00022743289200000712
respectively representing the search speed of the d variable of the particle i in the h +1 th iteration and the h iteration;
omega is an inertia weight and is used for balancing the local searching capacity and the global searching capacity;
c1、c2is a learning factor;
r1、r2and r3Is [0,1]]Random numbers obeying uniform distribution;
Figure BDA0002274328920000081
respectively representing the current value, the individual extreme value and the global extreme value of the d variable position of the h iterative particle i;
r is a constant and represents the radius of the black hole;
Figure BDA0002274328920000082
is [ -R, R]Obeying uniformly distributed random numbers.
In step S2, Y includes not only the admittance value of the load but also the short-circuit ground admittance.
Example 2
A short-circuit current calculation system of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm comprises a memory and a processor, wherein the memory comprises a program of a short-circuit current calculation method of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm, and when the program of the short-circuit current calculation method of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm is executed by the processor, the following steps are realized:
s1: initializing network parameters, and marking nodes where a main power supply, a distributed photovoltaic power supply and an induction motor are located; marking the position of a short-circuit point, and initializing the radius of a black hole, the particle speed and the particle position;
s2: iterating the radius of the black hole, the particle speed and the particle position;
s3: judging whether the black hole radius, the particle speed and the particle position meet the iteration end condition, if so, executing S4, and if not, executing S6:
s4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state;
s5: finishing;
s6: judging whether the induction motor is in a power generation state, if so, executing S7, otherwise, executing S10;
s7: calculating main power supply injection current, photovoltaic power supply injection current and induction motor injection current; calculating the node voltage according to a node voltage equation;
s8: updating the particle speed and the particle position;
s9: iterating the radius of the black hole, the particle speed and the particle position again, and returning to S3;
s10: and calculating the main power supply injection current and the photovoltaic power supply injection current, and executing S8 after calculating the node voltage according to the node voltage equation.
Example 3
A computer-readable storage medium comprises a program of a method for calculating short-circuit current of a medium-voltage distribution network comprising a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm.
The computer-readable storage medium comprises a program for realizing the method for calculating the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm when the program is executed by a processor.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

Claims (10)

1. A method for calculating short-circuit current of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm is characterized by comprising the following steps of:
s1: initializing network parameters, and marking nodes where a main power supply, a distributed photovoltaic power supply and an induction motor are located; marking the position of a short-circuit point, and initializing the radius of a black hole, the particle speed and the particle position;
s2: iterating the radius of the black hole, the particle speed and the particle position;
s3: judging whether the black hole radius, the particle speed and the particle position meet the iteration end condition, if so, executing S4, and if not, executing S6:
s4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state;
s5: finishing;
s6: judging whether the induction motor is in a power generation state, if so, executing S7, otherwise, executing S10;
s7: calculating main power supply injection current, photovoltaic power supply injection current and induction motor injection current; calculating the node voltage according to a node voltage equation;
s8: updating the particle speed and the particle position;
s9: iterating the radius of the black hole, the particle speed and the particle position again, and returning to S3;
s10: and calculating the main power supply injection current and the photovoltaic power supply injection current, and executing S8 after calculating the node voltage according to the node voltage equation.
2. The method for calculating the short-circuit current of the medium-voltage distribution network comprising the photovoltaic power supply and the induction motor based on the black hole particle swarm optimization algorithm according to claim 1, wherein a node voltage equation
Figure FDA0002274328910000011
Wherein the content of the first and second substances,
Figure FDA0002274328910000012
injecting a current matrix into the node, wherein Y is a node admittance matrix of the power distribution network system;
Figure FDA0002274328910000013
is a system node voltage matrix; if the total number of n nodes in the power grid is set, the main power supply is connected to the node k, the distributed photovoltaic power supply is connected to the node m, and the induction motor is connected to the node f, the node voltage equation can be expressed as follows:
Figure FDA0002274328910000014
in the formula:
Figure FDA0002274328910000015
injection current of the main power supply at node k;
Figure FDA0002274328910000016
the injection current of the distributed photovoltaic power supply at the node m;
Figure FDA0002274328910000021
is the injection current of the induction motor in the generator running state at the f node.
3. The method for calculating the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm according to claim 1, is characterized in that:
main power supply injected current
Figure FDA0002274328910000022
The calculation of (2): main power supply at node k, main power supply injection current
Figure FDA0002274328910000023
Is the ratio of the main power supply voltage to the system impedance;
injection current for distributed photovoltaic power supply
Figure FDA0002274328910000024
The calculation of (2): distributed photovoltaic power supply with node m out, with current injected
Figure FDA0002274328910000025
The solution can be made according to the following equation:
Figure FDA0002274328910000026
in the formula, PDGmCapacity of the photovoltaic power source;
Figure FDA0002274328910000027
is the grid connection point voltage rating;
Figure FDA0002274328910000028
is the phase angle of the grid-connected point voltage, α is the reactive current vector
Figure FDA0002274328910000029
And active current vector
Figure FDA00022743289100000210
The included angle of (A);
injection current in induction motor generator regime
Figure FDA00022743289100000211
The calculation of (2):
Figure FDA00022743289100000212
in the formula
Figure FDA00022743289100000213
And
Figure FDA00022743289100000214
respectively the induced electromotive force and the terminal voltage of the induction motor; zMfIs the external equivalent impedance of the induction motor.
4. The method for calculating the short-circuit current of the medium voltage distribution network comprising the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm as claimed in claim 1, wherein in S6, whether the induction motor is in a motor state or a generator state is judged according to the proximity of the induction motor to the short-circuit point.
5. The method for calculating the short-circuit current of the medium-voltage distribution network comprising the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm according to claim 4, wherein the state of the induction motor is judged according to the distance between the induction motor and the short-circuit point, and specifically comprises the following steps: if the position of the induction motor is far away from the position of the short-circuit point, the change of the voltage of the node where the induction motor is located is not large, and the induced electromotive force of the motor is smaller than the terminal voltage, so that the motor is in a motor state and still treated as a load; when the induction motor is close to the short-circuit point, the voltage of the node where the induction motor is located drops more, the induced electromotive force of the motor is larger than the end voltage, and the motor is in a generator state, and at the moment, the motor is regarded as a power supply and is a current source.
6. The method for calculating the short-circuit current of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm optimization algorithm according to claim 1, wherein the black hole particle swarm optimization algorithm can be expressed by the following formula:
Figure FDA00022743289100000215
the method comprises the following steps:
Figure FDA0002274328910000031
Figure FDA0002274328910000032
Figure FDA0002274328910000033
the method comprises the following steps:
Figure FDA0002274328910000034
Figure FDA0002274328910000035
in the formula:
Figure FDA0002274328910000036
is a probability value corresponding to the d variable of the particle i at the h iteration of [0, 1%]Random numbers obeying uniform distribution;
p is the probability threshold of the particle entering the black hole, a constant over [0,1 ];
Figure FDA0002274328910000037
respectively representing the search speed of the d variable of the particle i in the h +1 th iteration and the h iteration;
omega is an inertia weight and is used for balancing the local searching capacity and the global searching capacity;
c1、c2is a learning factor;
r1、r2and r3Is [0,1]]Random numbers obeying uniform distribution;
Figure FDA0002274328910000038
respectively representing the current value, the individual extreme value and the global extreme value of the d variable position of the h iterative particle i;
r is a constant and represents the radius of the black hole;
Figure FDA0002274328910000039
is [ -R, R]Obeying uniformly distributed random numbers.
7. The method for calculating the short-circuit current of the medium voltage distribution network including the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm as claimed in claim 2, wherein in the step S2, Y comprises not only the admittance value of the load but also the short-circuit grounding admittance.
8. A short-circuit current calculation system of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm is characterized by comprising a memory and a processor, wherein the memory comprises a short-circuit current calculation method program of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm, and when the short-circuit current calculation method program of the medium-voltage distribution network containing the photovoltaic power supply and the induction motor based on the black hole particle swarm algorithm is executed by the processor, the following steps are realized:
s1: initializing network parameters, and marking nodes where a main power supply, a distributed photovoltaic power supply and an induction motor are located; marking the position of a short-circuit point, and initializing the radius of a black hole, the particle speed and the particle position;
s2: iterating the radius of the black hole, the particle speed and the particle position;
s3: judging whether the black hole radius, the particle speed and the particle position meet the iteration end condition, if so, executing S4, and if not, executing S6:
s4: outputting each node voltage, each branch current, the output current of the photovoltaic power supply, the state of the induction motor and the output current in the power generation state;
s5: finishing;
s6: judging whether the induction motor is in a power generation state, if so, executing S7, otherwise, executing S10;
s7: calculating main power supply injection current, photovoltaic power supply injection current and induction motor injection current; calculating the node voltage according to a node voltage equation;
s8: updating the particle speed and the particle position;
s9: iterating the radius of the black hole, the particle speed and the particle position again, and returning to S3;
s10: and calculating the main power supply injection current and the photovoltaic power supply injection current, and executing S8 after calculating the node voltage according to the node voltage equation.
9. A computer-readable storage medium is characterized in that the computer-readable storage medium comprises a program of a method for calculating short-circuit current of a medium-voltage distribution network containing a photovoltaic power supply and an induction motor based on a black hole particle swarm algorithm.
10. The computer-readable storage medium according to claim 8, wherein said computer-readable storage medium comprises the steps of implementing the method for calculating the short-circuit current of the medium voltage distribution network comprising photovoltaic power sources and induction motors based on the blackhole particle swarm optimization as claimed in any one of claims 1 to 7 when the program is executed by the processor.
CN201911116954.8A 2019-11-15 2019-11-15 Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm Active CN110930263B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911116954.8A CN110930263B (en) 2019-11-15 2019-11-15 Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911116954.8A CN110930263B (en) 2019-11-15 2019-11-15 Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm

Publications (2)

Publication Number Publication Date
CN110930263A true CN110930263A (en) 2020-03-27
CN110930263B CN110930263B (en) 2020-12-29

Family

ID=69853084

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911116954.8A Active CN110930263B (en) 2019-11-15 2019-11-15 Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm

Country Status (1)

Country Link
CN (1) CN110930263B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117691609A (en) * 2024-02-02 2024-03-12 江苏华凌机电科技有限公司 Compensation control method and control system for voltage drop of photovoltaic micro-grid
CN117691609B (en) * 2024-02-02 2024-06-07 江苏华凌机电科技有限公司 Compensation control method and control system for voltage drop of photovoltaic micro-grid

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103199526A (en) * 2013-04-02 2013-07-10 重庆大学 Short circuit power frequency electrical quantity calculating method for power system comprising doubly-fed induction generator
US20130175867A1 (en) * 2009-12-03 2013-07-11 Samsung Sdi Co., Ltd. Grid-connected power storage system and method for controlling grid-connected power storage system
CN104332995A (en) * 2014-11-14 2015-02-04 南京工程学院 Improved particle swarm optimization based power distribution reconstruction optimization method
CN105183999A (en) * 2015-09-17 2015-12-23 国家电网公司 Method for calculating maximum short circuit current of electric power system with photovoltaic power station
CN105243516A (en) * 2015-11-11 2016-01-13 国网青海省电力公司 Distributed photovoltaic power generation maximum consumption capability calculation system based on active power distribution network
CN106330095A (en) * 2016-09-27 2017-01-11 华北电力大学 Large-scale photovoltaic power station's collection system fault location method
CN110311386A (en) * 2019-07-26 2019-10-08 国网江苏省电力有限公司淮安供电分公司 A kind of capacity configuration optimizing method based on the spontaneous idle and SVG reactive compensation of PSO new energy power station
CN110445127A (en) * 2019-06-25 2019-11-12 中国电力科学研究院有限公司 A kind of var Optimization Method in Network Distribution and system towards multiple stochastic uncertainty

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130175867A1 (en) * 2009-12-03 2013-07-11 Samsung Sdi Co., Ltd. Grid-connected power storage system and method for controlling grid-connected power storage system
CN103199526A (en) * 2013-04-02 2013-07-10 重庆大学 Short circuit power frequency electrical quantity calculating method for power system comprising doubly-fed induction generator
CN104332995A (en) * 2014-11-14 2015-02-04 南京工程学院 Improved particle swarm optimization based power distribution reconstruction optimization method
CN105183999A (en) * 2015-09-17 2015-12-23 国家电网公司 Method for calculating maximum short circuit current of electric power system with photovoltaic power station
CN105243516A (en) * 2015-11-11 2016-01-13 国网青海省电力公司 Distributed photovoltaic power generation maximum consumption capability calculation system based on active power distribution network
CN106330095A (en) * 2016-09-27 2017-01-11 华北电力大学 Large-scale photovoltaic power station's collection system fault location method
CN110445127A (en) * 2019-06-25 2019-11-12 中国电力科学研究院有限公司 A kind of var Optimization Method in Network Distribution and system towards multiple stochastic uncertainty
CN110311386A (en) * 2019-07-26 2019-10-08 国网江苏省电力有限公司淮安供电分公司 A kind of capacity configuration optimizing method based on the spontaneous idle and SVG reactive compensation of PSO new energy power station

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
宋云东 等: ""基于随机潮流的分布式电源多目标优化配置"", 《水电能源科学》 *
尹项根 等: ""分布式电源短路计算模型及电网故障计算方法研究"", 《电力系统保护与控制》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117691609A (en) * 2024-02-02 2024-03-12 江苏华凌机电科技有限公司 Compensation control method and control system for voltage drop of photovoltaic micro-grid
CN117691609B (en) * 2024-02-02 2024-06-07 江苏华凌机电科技有限公司 Compensation control method and control system for voltage drop of photovoltaic micro-grid

Also Published As

Publication number Publication date
CN110930263B (en) 2020-12-29

Similar Documents

Publication Publication Date Title
CN107887903B (en) Micro-grid robust optimization scheduling method considering element frequency characteristics
Belal et al. Adaptive droop control for balancing SOC of distributed batteries in DC microgrids
Zhao et al. Reactive power control of wind farm made up with doubly fed induction generators in distribution system
CN107392418B (en) Urban power distribution network reconstruction method and system
CN107681664A (en) A kind of grid-connected Optimal Power Flow computational methods of distributed power source based on interior point method
CN103368186A (en) Reactive optimization method of wind power system
Nguyen et al. Performance Comparison between PSO and GA in Improving Dynamic Voltage Stability in ANFIS Controllers for STATCOM.
CN108923461B (en) Distributed inverter power supply network access optimization method considering relay protection constraint
Phuangpornpitak et al. Optimal photovoltaic placement by self-organizing hierarchical binary particle swarm optimization in distribution systems
CN114024338B (en) Large-scale wind power collection grid split-phase power flow optimization method and system
Sekhar et al. RETRACTED: Low-voltage ride-through capability enhancement of wind energy conversion system using an ant-lion recurrent neural network controller
Gao et al. Distributed multi‐agent control for combined AC/DC grids with wind power plant clusters
CN109617079A (en) A kind of existence and method for analyzing stability of direct-flow distribution system flow solution
CN110930263B (en) Medium-voltage distribution network short-circuit current calculation method containing photovoltaic power supply and induction motor based on black hole particle swarm algorithm
Hongfei et al. Optimal control virtual inertia of optical storage microgrid based on improved sailfish algorithm
Ethmane et al. Statcom integration in a power grid to enhance voltage stability
Liu et al. Optimization of emergency load shedding following HVDC blocking of receiving-end power systems based on PSO
Hong et al. Enhanced Particle Swarm Optimization‐Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands
Doagou-Mojarrad et al. Probabilistic interactive fuzzy satisfying generation and transmission expansion planning using fuzzy adaptive chaotic binary PSO algorithm
Nasir et al. VSI improvement using SVC with aid of a modified lightning search algorithm
Zhang et al. Decentralised control strategy for hybrid battery energy storage system with considering dynamical state‐of‐charge regulation
Kan et al. Optimal configuration of the hybrid energy storage system for reducing the amount of discarded photovoltaic
CN107562971B (en) Alternating current/direct current power grid power flow calculation method based on PSS/E
CN114239252B (en) Method and system for generating operation mode of power system, computer and storage medium
CN108667057A (en) One kind accessing power distribution network multiple target electric energy administering method for high power density distributed photovoltaic

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