CN111509785A - Method, system and storage medium for multi-source optimal cooperative control of power grid - Google Patents

Method, system and storage medium for multi-source optimal cooperative control of power grid Download PDF

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CN111509785A
CN111509785A CN202010339673.5A CN202010339673A CN111509785A CN 111509785 A CN111509785 A CN 111509785A CN 202010339673 A CN202010339673 A CN 202010339673A CN 111509785 A CN111509785 A CN 111509785A
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generation control
power generation
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杨蕾
向川
何鑫
和鹏
奚鑫泽
李胜男
郭成
姜訸
孟贤
邢超
卢佳
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Electric Power Research Institute of Yunnan Power Grid Co Ltd
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20The dispersed energy generation being of renewable origin
    • H02J2300/22The renewable source being solar energy
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20The dispersed energy generation being of renewable origin
    • H02J2300/28The renewable source being wind energy

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Abstract

The invention discloses a method, a system and a storage medium for multi-source optimal cooperative control of a power grid, wherein the method for multi-source optimal cooperative control of the power grid is based on dynamic response characteristics of different frequency modulation resources, an automatic power generation control multi-source optimal cooperative control model between wind, solar, new energy and water, fire and electricity is established, the overall control effect of a power system is improved, real-time total regulation power △ P is input into each automatic power generation control unit through a cultural gene goblet sea squirt algorithm to obtain real-time regulation power of the automatic power generation control unit, the optimization speed of the algorithm is high, the real-time online regulation and control requirements of the automatic power generation control unit can be met, and the dynamic response characteristics of the power grid in the whole area are improved.

Description

Method, system and storage medium for multi-source optimal cooperative control of power grid
Technical Field
The invention relates to the field of power system control, in particular to a method, a system and a storage medium for multi-source optimal cooperative control of a power grid.
Background
With the rapid consumption of fossil fuels and the growing environmental problems, renewable energy sources such as solar energy and wind energy are gaining wide attention and being developed and utilized. With the access of a large amount of wind and light new energy to a power grid, a large wind power plant and a photovoltaic power station also start to participate in secondary frequency modulation of a regional power grid. The consumption form of new energy is gradually changed from the past passive consumption to the active consumption. The traditional peak-shaving frequency modulation elasticity of water and thermal power plants, especially thermal power plants, is poor, and the high-quality dynamic frequency modulation requirement of a system is difficult to meet.
Therefore, the characteristics of faster response speed, higher climbing rate and the like of the wind turbine generator and the photovoltaic array are required to be effectively utilized to participate in secondary frequency modulation, and in a regional power grid, effective cooperative control between new wind and light energy and other frequency modulation resources, namely Automatic Generation Control (AGC) multi-source optimal cooperative control, is mainly relied on. The problem is a complex nonlinear optimization problem, and the traditional mathematical optimization method (such as an interior point method) has the disadvantages of high solving speed, poor global searching capability and easy falling into a local optimal solution. While intelligent optimization algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have higher application flexibility and stronger global search capability, but the solution speed is slower, and the AGC online control requirement of a large-scale regional power grid cannot be met.
Therefore, a method for power grid multi-source optimal cooperative control, which can rapidly and reliably improve the dynamic response performance of the system, is sought to realize real-time online AGC regulation and control of a power grid containing high-proportion wind and light new energy, and a problem to be solved is urgently needed.
Disclosure of Invention
The invention provides a method, a system and a storage medium for multi-source optimal cooperative control of a power grid, which aim to overcome the defects of the prior art.
In a first aspect, the invention provides a method for optimal collaborative control of multiple sources of a power grid, which comprises the following steps:
the first step is as follows: establishing an automatic power generation control multi-source optimal cooperative control model between wind and solar new energy and water-fire power, wherein the automatic power generation control multi-source optimal cooperative control model adopts a two-region interconnected power grid framework, and the control process of each region comprises the optimal distribution of a controller and power;
secondly, outputting △ P real-time total regulated power of each regional power grid through an automatic power generation control multi-source optimal cooperative control model;
inputting the real-time total regulated power △ P into each automatic power generation control unit through a cultural gene goblet and ascidian algorithm to obtain the real-time regulated power of the automatic power generation control unit;
the fourth step: acquiring frequency deviation and tie line power deviation under real-time regulation power of a current automatic power generation control unit in real time through a real-time operation data acquisition system of a power grid to obtain real-time frequency deviation and real-time tie line power deviation;
the fifth step: converting the real-time frequency deviation and the real-time tie line power deviation into a regional control deviation, and feeding the regional control deviation back to the controller for the next iteration;
and a sixth step: and (4) repeatedly iterating until the cultural gene goblet and ascidian algorithm converges to obtain the optimal power distribution, wherein the optimal power distribution is the minimum power response total deviation.
The method for establishing the automatic power generation control multi-source optimal cooperative control model between the wind and light new energy and the water and fire electricity comprises the following steps:
the first step is as follows: determining an optimized variable, wherein the optimized variable is a total power regulating instruction;
the second step is that: acquiring an input adjusting power instruction and an actual adjusting power output of the ith automatic power generation control unit, and obtaining a target function of the sum of the absolute values of the deviations of the adjusting power instruction values and the power response values of all the units as follows:
Figure BDA0002468109430000011
wherein f (x) is an objective function;
Figure BDA0002468109430000012
and
Figure BDA0002468109430000013
respectively representing the input regulation power instruction and the regulation power actual output of the ith automatic power generation control unit; j represents the jth discrete control period; n is the number of control time periods; n is the number of the self-Odong power generation control units;
the third step: from the total power command, constraints are determined as follows:
Figure BDA0002468109430000021
Figure BDA0002468109430000022
Figure BDA0002468109430000023
Figure BDA0002468109430000024
in the formula,. DELTA.PinA total power adjustment instruction;
Figure BDA0002468109430000025
the maximum climbing speed of the ith automatic power generation control unit is obtained;
the fourth step: and establishing an automatic power generation control multi-source optimal cooperative control model by optimizing variables, objective functions and constraint conditions.
The method for obtaining the real-time regulated power of the automatic power generation control unit by inputting the real-time total regulated power △ P into each automatic power generation control unit through the culture gene goblet sea squirt algorithm comprises the following steps:
the first step is as follows: randomly initializing the population in the feasible region, namely initializing the Hyacanthus gordonii, as shown in the following formula:
Figure BDA0002468109430000026
in the formula (I), the compound is shown in the specification,
Figure BDA0002468109430000027
represents the initial position of the ith goblet ascidian in the mth goblet ascidian chain; r is [0, 1 ]]A random number in between;
the second step is that: carrying out independent optimization processing on the goblet sea squirt chain, wherein the goblet sea squirt chain comprises a leader and a follower, and for the mth goblet sea squirt chain, the leader updates the position according to the following formula:
Figure BDA0002468109430000028
wherein j represents the j-th dimension of the search space;
Figure BDA0002468109430000029
represents the leader in the mth goblet sea squirt chain;
Figure BDA00024681094300000210
represents a food source; ubjAnd lbjThe upper bound and the lower bound of the j-dimension search space respectively;
Figure BDA00024681094300000211
global search and local exploration for a balanced algorithm; k and kmaxRespectively the current iteration times and the maximum iteration times; c. C2And c3Are all [0, 1]A random number in between;
the follower updates the location as follows:
Figure BDA00024681094300000212
in the formula (I), the compound is shown in the specification,
Figure BDA00024681094300000213
represents the ith goblet ascidian in the mth goblet ascidian chain; n represents the number of goblet ascidians in each chain of goblet ascidians; m represents the total number of sea squirts;
the third step: updating the goblet sea squirt chain, the updating of the mth goblet sea squirt chain is as follows:
Ym=[xmi,fmi|xmi=X(m+M(i-1)),fmi=F(m+M(i-1)),i=1,2,…,n],m=1,2,…,M
in the formula, xmiIs the location vector of the ith goblet ascidian in the mth goblet ascidian chain; f. ofmiIs the fitness function of the ith goblet ascidian in the mth goblet ascidian chain; x, F are respectively the position vector and fitness function corresponding to the ordering of all the goblet ascidians from small to large;
and fourthly, inputting the real-time total regulated power △ P into each automatic power generation control unit to obtain the real-time regulated power of the automatic power generation control unit, namely, the Mth goblet sea squirt chain enters the Mth goblet sea squirt chain, and the Mth goblet sea squirt chain inputs the real-time total regulated power △ P into the Mth automatic power generation control unit.
In a second aspect, the present invention provides a system for multi-source optimal cooperative control of a power grid, including an automatic power generation control multi-source optimal cooperative control model building module, a real-time total regulated power △ P output module, an automatic power generation control unit real-time regulated power obtaining module, a frequency power deviation obtaining module, a conversion module, and an optimal power distribution obtaining module, wherein:
the automatic power generation control multi-source optimal collaborative control model building module is used for building an automatic power generation control multi-source optimal collaborative control model, the automatic power generation control multi-source optimal collaborative control model adopts a two-region interconnected power grid framework, and the control process of each region comprises the optimal distribution of a controller and power;
the real-time total regulated power △ P output module is used for outputting real-time total regulated power △ P of each regional power grid through an automatic power generation control multi-source optimal cooperative control model;
the automatic power generation control unit real-time regulation power acquisition module is used for inputting real-time total regulation power △ P into each automatic power generation control unit through a cultural gene goblet sea squirt algorithm to obtain the real-time regulation power of the automatic power generation control unit;
the frequency power deviation acquisition module is used for acquiring the frequency deviation and the tie line power deviation under the real-time regulation power of the current automatic power generation control unit in real time through a real-time operation data acquisition system of the power grid to obtain the real-time frequency deviation and the real-time tie line power deviation;
the conversion module is used for converting the real-time frequency deviation and the real-time tie line power deviation into a regional control deviation and feeding the regional control deviation back to the controller for next iteration;
and the optimal power distribution acquisition module is used for repeatedly iterating until the culture gene goblet and ascidian algorithm converges to obtain optimal power distribution, wherein the optimal power distribution is the minimum power response total deviation.
In a third aspect, the present invention provides a storage medium containing computer executable instructions which, when executed by a computer processor, implement the method of the first aspect for grid multi-source optimal collaborative control.
According to the technical scheme, the invention provides a method, a system and a storage medium for multi-source optimal cooperative control of a power grid, and the method for multi-source optimal cooperative control of the power grid provided by the invention has the following beneficial effects:
(1) based on the dynamic response characteristics of different frequency modulation resources, an automatic power generation control multi-source optimal cooperative control model between wind and light new energy and water and fire electricity is established, and the overall control effect of the power system is improved;
(2) the real-time total regulation power △ P is input into each automatic power generation control unit through the culture gene goblet sea squirt algorithm to obtain the real-time regulation power of the automatic power generation control units, so that the algorithm optimizing speed is high, the real-time online regulation and control requirements of the automatic power generation control units can be met, and the dynamic response characteristic of the whole regional power grid is improved.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any inventive exercise.
FIG. 1 is a flow chart of a method for optimal cooperative multi-source control of a power grid according to the present invention;
fig. 2 is a schematic diagram of a method for multi-source optimal cooperative control of a power grid according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described, and it will be appreciated by those skilled in the art that the present invention may be embodied without departing from the spirit and scope of the invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Referring to fig. 1 and 2, in a first aspect, the present invention provides a method for optimal coordinated control of multiple sources of a power grid, including the following steps:
s1: establishing an automatic power generation control multi-source optimal cooperative control model between wind and solar new energy and water-fire power, wherein the automatic power generation control multi-source optimal cooperative control model adopts a two-region interconnected power grid framework, and the control process of each region comprises the optimal distribution of a controller and power;
the method for establishing the automatic power generation control multi-source optimal cooperative control model between the wind and light new energy and the water and fire electricity comprises the following steps:
the first step is as follows: determining an optimized variable, wherein the optimized variable is a total power regulating instruction;
the second step is that: acquiring an input adjusting power instruction and an actual adjusting power output of the ith automatic power generation control unit, and obtaining a target function of the sum of the absolute values of the deviations of the adjusting power instruction values and the power response values of all the units as follows:
Figure BDA0002468109430000041
wherein f (x) is an objective function;
Figure BDA0002468109430000042
and
Figure BDA0002468109430000043
respectively representing the input regulation power instruction and the regulation power actual output of the ith automatic power generation control unit; j represents the jth discrete control period; n is the number of control time periods; n is the number of the self-Odong power generation control units;
the third step: from the total power command, constraints are determined as follows:
Figure BDA0002468109430000044
Figure BDA0002468109430000045
Figure BDA0002468109430000046
Figure BDA0002468109430000047
in the formula,. DELTA.PinA total power adjustment instruction;
Figure BDA0002468109430000048
the maximum climbing speed of the ith automatic power generation control unit is obtained;
the fourth step: and establishing an automatic power generation control multi-source optimal cooperative control model by optimizing variables, objective functions and constraint conditions.
S2, outputting real-time total regulated power △ P of each regional power grid through an automatic power generation control multi-source optimal cooperative control model;
s3, inputting the real-time total regulated power △ P into each automatic power generation control unit through a cultural gene goblet sea squirt algorithm to obtain the real-time regulated power of the automatic power generation control units;
the method for obtaining the real-time regulated power of the automatic power generation control unit by inputting the real-time total regulated power △ P into each automatic power generation control unit through the culture gene goblet sea squirt algorithm comprises the following steps:
the first step is as follows: randomly initializing the population in the feasible region, namely initializing the Hyacanthus gordonii, as shown in the following formula:
Figure BDA0002468109430000049
in the formula (I), the compound is shown in the specification,
Figure BDA00024681094300000410
represents the initial position of the ith goblet ascidian in the mth goblet ascidian chain; r is [0, 1 ]]A random number in between;
the second step is that: carrying out independent optimization processing on the goblet sea squirt chain, wherein the goblet sea squirt chain comprises a leader and a follower, and for the mth goblet sea squirt chain, the leader updates the position according to the following formula:
Figure BDA00024681094300000411
wherein j represents the j-th dimension of the search space;
Figure BDA0002468109430000051
represents the leader in the mth goblet sea squirt chain;
Figure BDA0002468109430000052
represents a food source; ubjAnd lbjThe upper bound and the lower bound of the j-dimension search space respectively;
Figure BDA0002468109430000053
global search and local exploration for a balanced algorithm; k and kmaxRespectively the current iteration times and the maximum iteration times; c. C2And c3Are all [0, 1]A random number in between;
the follower updates the location as follows:
Figure BDA0002468109430000054
in the formula (I), the compound is shown in the specification,
Figure BDA0002468109430000055
represents the ith goblet ascidian in the mth goblet ascidian chain; n represents the number of goblet ascidians in each chain of goblet ascidians; m represents the total number of sea squirts;
the third step: updating the goblet sea squirt chain, the updating of the mth goblet sea squirt chain is as follows:
Ym=[xmi,fmi|xmi=X(m+M(i-1)),fmi=F(m+M(i-1)),i=1,2,…,n],m=1,2,…,M
in the formula, xmiIs the location vector of the ith goblet ascidian in the mth goblet ascidian chain; f. ofmiIs the fitness function of the ith goblet ascidian in the mth goblet ascidian chain; x, F all the goblet ascidians are arranged from small to largeOrdering the corresponding position vector and fitness function;
and fourthly, inputting the real-time total regulated power △ P into each automatic power generation control unit to obtain the real-time regulated power of the automatic power generation control unit, namely, the Mth goblet sea squirt chain enters the Mth goblet sea squirt chain, and the Mth goblet sea squirt chain inputs the real-time total regulated power △ P into the Mth automatic power generation control unit.
S4: acquiring frequency deviation and tie line power deviation under real-time regulation power of a current automatic power generation control unit in real time through a real-time operation data acquisition system of a power grid to obtain real-time frequency deviation and real-time tie line power deviation;
s5: converting the real-time frequency deviation and the real-time tie line power deviation into a regional control deviation, and feeding the regional control deviation back to the controller for the next iteration;
s6: and (4) repeatedly iterating until the cultural gene goblet and ascidian algorithm converges to obtain the optimal power distribution, wherein the optimal power distribution is the minimum power response total deviation.
In a second aspect, the present invention provides a system for multi-source optimal cooperative control of a power grid, including an automatic power generation control multi-source optimal cooperative control model building module, a real-time total regulated power △ P output module, an automatic power generation control unit real-time regulated power obtaining module, a frequency power deviation obtaining module, a conversion module, and an optimal power distribution obtaining module, wherein:
the automatic power generation control multi-source optimal collaborative control model building module is used for building an automatic power generation control multi-source optimal collaborative control model, the automatic power generation control multi-source optimal collaborative control model adopts a two-region interconnected power grid framework, and the control process of each region comprises the optimal distribution of a controller and power;
the real-time total regulated power △ P output module is used for outputting real-time total regulated power △ P of each regional power grid through an automatic power generation control multi-source optimal cooperative control model;
the automatic power generation control unit real-time regulation power acquisition module is used for inputting real-time total regulation power △ P into each automatic power generation control unit through a cultural gene goblet sea squirt algorithm to obtain the real-time regulation power of the automatic power generation control unit;
the frequency power deviation acquisition module is used for acquiring the frequency deviation and the tie line power deviation under the real-time regulation power of the current automatic power generation control unit in real time through a real-time operation data acquisition system of the power grid to obtain the real-time frequency deviation and the real-time tie line power deviation;
the conversion module is used for converting the real-time frequency deviation and the real-time tie line power deviation into a regional control deviation and feeding the regional control deviation back to the controller for next iteration;
and the optimal power distribution acquisition module is used for repeatedly iterating until the culture gene goblet and ascidian algorithm converges to obtain optimal power distribution, wherein the optimal power distribution is the minimum power response total deviation.
In a third aspect, the present invention provides a storage medium containing computer executable instructions which, when executed by a computer processor, implement the method of the first aspect for grid multi-source optimal collaborative control.
According to the technical scheme, the invention provides a method, a system and a storage medium for multi-source optimal cooperative control of a power grid, and the method for multi-source optimal cooperative control of the power grid provided by the invention has the following beneficial effects:
(1) based on the dynamic response characteristics of different frequency modulation resources, an automatic power generation control multi-source optimal cooperative control model between wind and light new energy and water and fire electricity is established, and the overall control effect of the power system is improved;
(2) the real-time total regulation power △ P is input into each automatic power generation control unit through the culture gene goblet sea squirt algorithm to obtain the real-time regulation power of the automatic power generation control units, so that the algorithm optimizing speed is high, the real-time online regulation and control requirements of the automatic power generation control units can be met, and the dynamic response characteristic of the whole regional power grid is improved.
The foregoing is merely a detailed description of the invention, and it should be noted that modifications and adaptations by those skilled in the art may be made without departing from the principles of the invention, and should be considered as within the scope of the invention.

Claims (5)

1. A method for optimal collaborative control of multiple sources of a power grid, the method comprising the steps of:
the first step is as follows: establishing an automatic power generation control multi-source optimal cooperative control model between wind and solar new energy and water-fire power, wherein the automatic power generation control multi-source optimal cooperative control model adopts a two-region interconnected power grid framework, and the control process of each region comprises the optimal distribution of a controller and power;
secondly, outputting △ P real-time total regulated power of each regional power grid through an automatic power generation control multi-source optimal cooperative control model;
inputting the real-time total regulated power △ P into each automatic power generation control unit through a cultural gene goblet and ascidian algorithm to obtain the real-time regulated power of the automatic power generation control unit;
the fourth step: acquiring frequency deviation and tie line power deviation under real-time regulation power of a current automatic power generation control unit in real time through a real-time operation data acquisition system of a power grid to obtain real-time frequency deviation and real-time tie line power deviation;
the fifth step: converting the real-time frequency deviation and the real-time tie line power deviation into a regional control deviation, and feeding the regional control deviation back to the controller for the next iteration;
and a sixth step: and (4) repeatedly iterating until the cultural gene goblet and ascidian algorithm converges to obtain the optimal power distribution, wherein the optimal power distribution is the minimum power response total deviation.
2. The method for multi-source optimal cooperative control of the power grid according to claim 1, wherein the establishing of the automatic power generation control multi-source optimal cooperative control model between the wind, solar, new energy and the water, fire and electricity comprises the following steps:
the first step is as follows: determining an optimized variable, wherein the optimized variable is a total power regulating instruction;
the second step is that: acquiring an input adjusting power instruction and an actual adjusting power output of the ith automatic power generation control unit, and obtaining a target function of the sum of the absolute values of the deviations of the adjusting power instruction values and the power response values of all the units as follows:
Figure FDA0002468109420000011
wherein f (x) is an objective function; delta Pi inAnd Δ Pi outRespectively representing the input regulation power instruction and the regulation power actual output of the ith automatic power generation control unit; j represents the jth discrete control period; n is the number of control time periods; n is the number of the self-Odong power generation control units;
the third step: from the total power command, constraints are determined as follows:
Figure FDA0002468109420000012
Figure FDA0002468109420000013
Figure FDA0002468109420000014
Figure FDA0002468109420000015
in the formula,. DELTA.PinA total power adjustment instruction; pi rateThe maximum climbing speed of the ith automatic power generation control unit is obtained;
the fourth step: and establishing an automatic power generation control multi-source optimal cooperative control model by optimizing variables, objective functions and constraint conditions.
3. The method for multi-source optimal cooperative control of power grid as claimed in claim 1, wherein the step of inputting the real-time total regulated power △ P into each automatic generation control unit through cultural gene goblet and sea squirt algorithm to obtain the real-time regulated power of the automatic generation control unit comprises the following steps:
the first step is as follows: randomly initializing the population in the feasible region, namely initializing the Hyacanthus gordonii, as shown in the following formula:
Figure FDA0002468109420000016
in the formula (I), the compound is shown in the specification,
Figure FDA0002468109420000021
represents the initial position of the ith goblet ascidian in the mth goblet ascidian chain; r is [0, 1 ]]A random number in between;
the second step is that: carrying out independent optimization processing on the goblet sea squirt chain, wherein the goblet sea squirt chain comprises a leader and a follower, and for the mth goblet sea squirt chain, the leader updates the position according to the following formula:
Figure FDA0002468109420000022
wherein j represents the j-th dimension of the search space;
Figure FDA0002468109420000023
represents the leader in the mth goblet sea squirt chain;
Figure FDA0002468109420000024
represents a food source; ubjAnd lbjThe upper bound and the lower bound of the j-dimension search space respectively;
Figure FDA0002468109420000025
global search and local exploration for a balanced algorithm; k and kmaxRespectively the current iteration times and the maximum iteration times; c. C2And c3Are all [0, 1]A random number in between;
the follower updates the location as follows:
Figure FDA0002468109420000026
in the formula (I), the compound is shown in the specification,
Figure FDA0002468109420000027
represents the ith goblet ascidian in the mth goblet ascidian chain; n represents the number of goblet ascidians in each chain of goblet ascidians; m represents the total number of sea squirts;
the third step: updating the goblet sea squirt chain, the updating of the mth goblet sea squirt chain is as follows:
Ym=[xmi,fmi|xmi=X(m+M(i-1)),fmi=F(m+M(i-1)),i=1,2,…,n],m=1,2,…,M
in the formula, xmiIs the location vector of the ith goblet ascidian in the mth goblet ascidian chain; f. ofmiIs the fitness function of the ith goblet ascidian in the mth goblet ascidian chain; x, F are respectively the position vector and fitness function corresponding to the ordering of all the goblet ascidians from small to large;
and fourthly, inputting the real-time total regulated power △ P into each automatic power generation control unit to obtain the real-time regulated power of the automatic power generation control unit, namely, the Mth goblet sea squirt chain enters the Mth goblet sea squirt chain, and the Mth goblet sea squirt chain inputs the real-time total regulated power △ P into the Mth automatic power generation control unit.
4. The utility model provides a system for electric wire netting multi-source optimal cooperative control, its characterized in that, the system includes automatic power generation control multi-source optimal cooperative control model construction module, real-time total regulated power △ P output module, the real-time regulated power of automatic power generation control unit obtains module, frequency power deviation and obtains module, conversion module and optimal power distribution and obtains the module, wherein:
the automatic power generation control multi-source optimal collaborative control model building module is used for building an automatic power generation control multi-source optimal collaborative control model, the automatic power generation control multi-source optimal collaborative control model adopts a two-region interconnected power grid framework, and the control process of each region comprises the optimal distribution of a controller and power;
the real-time total regulated power △ P output module is used for outputting real-time total regulated power △ P of each regional power grid through an automatic power generation control multi-source optimal cooperative control model;
the automatic power generation control unit real-time regulation power acquisition module is used for inputting real-time total regulation power △ P into each automatic power generation control unit through a cultural gene goblet sea squirt algorithm to obtain the real-time regulation power of the automatic power generation control unit;
the frequency power deviation acquisition module is used for acquiring the frequency deviation and the tie line power deviation under the real-time regulation power of the current automatic power generation control unit in real time through a real-time operation data acquisition system of the power grid to obtain the real-time frequency deviation and the real-time tie line power deviation;
the conversion module is used for converting the real-time frequency deviation and the real-time tie line power deviation into a regional control deviation and feeding the regional control deviation back to the controller for next iteration;
and the optimal power distribution acquisition module is used for repeatedly iterating until the culture gene goblet and ascidian algorithm converges to obtain optimal power distribution, wherein the optimal power distribution is the minimum power response total deviation.
5. A storage medium containing computer executable instructions, which when executed by a computer processor implement the method for grid multi-source optimal coordinated control according to any one of claims 1-4.
CN202010339673.5A 2020-04-26 2020-04-26 Method, system and storage medium for multi-source optimal cooperative control of power grid Withdrawn CN111509785A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113036762A (en) * 2021-05-10 2021-06-25 中国建筑第五工程局有限公司 SSA algorithm-based multi-channel power signal mode rapid identification method
CN113222779A (en) * 2021-05-10 2021-08-06 合肥工业大学 Power distribution network voltage fluctuation suppression method based on improved goblet sea squirt group algorithm
CN113241805A (en) * 2021-06-11 2021-08-10 云南电网有限责任公司电力科学研究院 Secondary frequency modulation method and device for power grid
CN114039366A (en) * 2021-11-11 2022-02-11 云南电网有限责任公司电力科学研究院 Power grid secondary frequency modulation control method and device based on peacock optimization algorithm

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113036762A (en) * 2021-05-10 2021-06-25 中国建筑第五工程局有限公司 SSA algorithm-based multi-channel power signal mode rapid identification method
CN113222779A (en) * 2021-05-10 2021-08-06 合肥工业大学 Power distribution network voltage fluctuation suppression method based on improved goblet sea squirt group algorithm
CN113241805A (en) * 2021-06-11 2021-08-10 云南电网有限责任公司电力科学研究院 Secondary frequency modulation method and device for power grid
CN113241805B (en) * 2021-06-11 2023-01-20 云南电网有限责任公司电力科学研究院 Secondary frequency modulation method and device for power grid
CN114039366A (en) * 2021-11-11 2022-02-11 云南电网有限责任公司电力科学研究院 Power grid secondary frequency modulation control method and device based on peacock optimization algorithm
CN114039366B (en) * 2021-11-11 2023-11-21 云南电网有限责任公司电力科学研究院 Power grid secondary frequency modulation control method and device based on peacock optimization algorithm

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