CN113285496B - Micro-grid distributed elastic control method based on confidence factors - Google Patents

Micro-grid distributed elastic control method based on confidence factors Download PDF

Info

Publication number
CN113285496B
CN113285496B CN202110643162.7A CN202110643162A CN113285496B CN 113285496 B CN113285496 B CN 113285496B CN 202110643162 A CN202110643162 A CN 202110643162A CN 113285496 B CN113285496 B CN 113285496B
Authority
CN
China
Prior art keywords
distributed power
representing
distributed
neighbor
local
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.)
Active
Application number
CN202110643162.7A
Other languages
Chinese (zh)
Other versions
CN113285496A (en
Inventor
顾伟
曹戈
楼冠男
袁晓冬
赵景涛
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.)
Southeast University
Original Assignee
Southeast University
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 Southeast University filed Critical Southeast University
Priority to CN202110643162.7A priority Critical patent/CN113285496B/en
Publication of CN113285496A publication Critical patent/CN113285496A/en
Application granted granted Critical
Publication of CN113285496B publication Critical patent/CN113285496B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • H02J3/50Controlling the sharing of the out-of-phase component
    • 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
    • H02J3/12Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/16Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by adjustment of reactive power
    • 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
    • H02J3/24Arrangements for preventing or reducing oscillations of power in networks
    • H02J3/241The oscillation concerning frequency
    • 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
    • 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
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30Reactive power compensation

Abstract

The invention discloses a distributed elastic control method of a micro-grid based on a confidence factor, belonging to the technical field of micro-grid operation control; firstly, updating a local confidence factor through local detection of false data injection attack, and determining the confidence level of local information; secondly, updating a neighbor confidence factor through a neighbor average value, and determining the reliability of neighbor information; and finally, establishing distributed secondary voltage reactive power control of the micro-grid based on the elastic consistency, and realizing the elastic operation of the reactive power average and the average voltage recovery of the system. The control method is based on consistency control of a multi-agent system, gives consideration to a normal communication scene and a network attack scene, provides a basis for the design of a control structure of distributed secondary control, and further improves the operation elasticity of the micro-grid.

Description

Micro-grid distributed elastic control method based on confidence factors
Technical Field
The disclosure belongs to the technical field of microgrid operation control, and particularly relates to a microgrid distributed elastic control method based on a confidence factor.
Background
With the gradual depletion of earth resources and the concern of people on environmental problems, the access of renewable energy resources is more and more emphasized by countries in the world. The microgrid is an emerging energy transmission mode for increasing the permeability of renewable energy sources and distributed energy sources in an energy supply system, and the components of the microgrid comprise different kinds of distributed energy sources (including micro gas turbines, wind generators, photovoltaics, fuel cells, energy storage devices and the like), user terminals of various electric loads and/or thermal loads and related monitoring and protection devices.
The power supply in the micro-grid is mainly used for energy conversion by power electronic devices and provides necessary control; the micro-grid is represented as a single controlled unit relative to an external large grid, and can simultaneously meet the requirements of users on electric energy quality, power supply safety and the like. Energy exchange is carried out between the micro-grid and the large grid through a public connection point, and the micro-grid and the large grid are mutually standby, so that the reliability of power supply is improved. Because the micro-grid is a small-scale decentralized system and is close to the load, the reliability of local power supply can be improved, the grid loss is reduced, the energy utilization efficiency is greatly increased, and the micro-grid is a novel power supply mode which meets the development requirements of the future intelligent power grid.
A large number of sensing measurement and control devices which lack effective safety protection access to the microgrid, and meanwhile third-party application programs in the public communication network can flexibly access an information system of the microgrid to provide auxiliary services, so that more potential network attack access points are brought to the microgrid information system, and the risk that the information system is attacked by a malicious network is increased. The network attack types influencing the safety of the micro-grid network are numerous, and the safety of a power system is seriously threatened by the false data injection attack by taking state variables containing attack signals as measurement and communication information.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a micro-grid distributed elastic control method based on a confidence factor, so that the operation elasticity of a micro-grid is improved, and the safety of a power system is further improved.
The purpose of the disclosure can be realized by the following technical scheme:
a distributed elastic control method for a microgrid based on a confidence factor is characterized by comprising the following steps:
s1: primary droop control of the micro-grid;
s2: local detection of spurious data injection attacks;
s3: updating a local confidence factor based on the local detection;
s4: updating the neighbor confidence factor based on the neighbor mean value;
s5: and establishing a distributed secondary voltage reactive power control rate, and realizing reactive power equalization and average voltage recovery of the microgrid under normal conditions and network attacks.
Further, in the S1, the primary droop control of the microgrid is controlled by the following formula:
Figure BDA0003108802660000021
in the formula, ωiAnd viRespectively representing the angular frequency and amplitude, omega, of the output AC voltage of the ith distributed power supply0And v0Nominal values, m, respectively representing the angular frequency and amplitude of the designed output AC voltageiAnd niRespectively representing the droop coefficients of angular frequency and voltage, PiAnd QiRespectively representing the active power and the reactive power output by the distributed power supply.
Further, the S2 includes: determining a local detection result of the distributed power supply on the virtual data injection attack, and determining according to the following formula:
Figure BDA0003108802660000031
in the formula IiA local detection signal representative of a distributed power source i;
Figure BDA0003108802660000032
and a reference value representing the q-axis current component in the primary control of the distributed power source i is obtained by the inverter double-ring controller. If the distributed power i is not attacked, then l i0, the local information is credible; if the distributed power i is attacked li>0, indicating that the local information is not authentic.
Further, in S3, the local confidence factor of the distributed power source is updated according to the following formula:
Figure BDA0003108802660000033
in the formula (I), the compound is shown in the specification,
Figure BDA0003108802660000034
represents the local confidence factor ciA derivative with respect to time; alpha (alpha) ("alpha")>0 denotes a convergence parameter for adjusting the local confidence factor ciThe update speed of (2); deltaiA detection threshold is indicated for distinguishing attack signals from other perturbations. If no attack occurs in the local detection result, the system reaches a steady stateHour li=0,k i1, thus c i1, normally performing distributed control in the microgrid; if an attack signal is detected locally, then li>0,ki(t)<1, thereby ci<1, gradually reducing local reactive power control deviation depending on the size of an attack signal; if c isiLess than a set threshold cth,iThen c isi=0。
Further, the neighbor confidence factor of the distributed power supply is updated in S4, and the updating is performed according to the following formula;
Figure BDA0003108802660000035
in the formula (I), the compound is shown in the specification,
Figure BDA0003108802660000036
representing neighbor confidence factor TijA derivative with respect to time; beta is a betaj>0 denotes a convergence parameter for adjusting the neighbor confidence factor TijThe update speed of (2); sigmaiRepresenting an update threshold for distinguishing attack signals from other perturbations; | NiL represents the number of neighbors of the distributed power supply i;
Figure BDA0003108802660000037
represents the average of the neighbor reactive power estimates for distributed power source i. If the data of the neighbor distributed power supply j is credible, the system reaches the steady state
Figure BDA0003108802660000041
sij1, thus T ij1, normally performing distributed control in the microgrid; if the data of the neighbor distributed power j is injected into the attack signal, then
Figure BDA0003108802660000042
Thus Tij<1 and is dependent on
Figure BDA0003108802660000043
The larger the value of (A),TijThe smaller the estimated value of the reactive power information of the neighbor distributed power supply is, the less credible the estimated value is, and the influence of the neighbor information on the local reactive power control deviation needs to be gradually reduced; if T isijLess than a set threshold Tth,ijAnd the information of the neighbor distributed power supply j exits the local consistency coordination process to prevent the system from being unstable.
Further, the distributed secondary control in S5 is controlled by the following formula:
Figure BDA0003108802660000044
in the formula uiRepresenting the secondary voltage control quantity of the distributed power supply i;
Figure BDA0003108802660000045
and
Figure BDA0003108802660000046
respectively representing the voltage amplitude and the reactive power control quantity of the distributed power source i; v. ofrefAnd QrefRespectively representing the reference values of the voltage amplitude and the reactive power control deviation of the microgrid; hv=(kPv+kIvS) and HQ=(kPQ+kIQ/s) PI controllers, k) representing the voltage amplitude and reactive power, respectively, of the distributed power supply ipv、kpQ、kivAnd kiQRespectively representing proportional and integral parameters of the PI controller;
Figure BDA0003108802660000047
representing an average voltage estimate of the distributed power source i;
Figure BDA0003108802660000048
representing the reactive power control deviation of the distributed power source i;
Figure BDA0003108802660000049
represents the average voltage control deviation of the distributed power source i; a is aijRepresenting communication coupling gainParameters, if the distributed power source i and the distributed power source j are connected through a communication line, aijNot equal to 0, otherwise, aij=0;
Figure BDA00031088026600000410
Representing an average voltage estimate for distributed power source j; n is a radical ofiA set of neighbors representing the ith agent; c. CiA local confidence factor representing the distributed power source i; t is a unit ofijRepresenting a confidence factor of the distributed power source i to the neighbor distributed power source j;
Figure BDA00031088026600000411
representing an estimate of the reactive power of the distributed power source j.
The beneficial effect of this disclosure: updating a local confidence factor through local detection of false data injection attack, and determining the credibility of local information; updating a neighbor confidence factor through a neighbor average value, and determining the reliability of neighbor information; then establishing distributed secondary voltage reactive power control of the microgrid based on elastic consistency, and realizing elastic operation of reactive power average division and average voltage recovery of the system; the control method is based on consistency control of a multi-agent system, introduces local detection and definition of confidence factors for the first time, gives consideration to a normal communication scene and a network attack scene, provides a basis for the design of a control structure of distributed secondary control, and further improves the operation elasticity of the microgrid.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present disclosure, the drawings used in the embodiments or technical solutions of the present disclosure will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a microgrid simulation system employed in an embodiment of the present invention;
FIG. 3 is a graph of grid-connected voltage and output reactive power of a distributed power supply after a microgrid is subjected to false data injection attack in an embodiment;
fig. 4 is a graph of grid-connected voltage and output reactive power of the distributed power supply by using the method of the present invention after the micro grid is subjected to false data injection attack in the embodiment.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
As shown in fig. 1, a distributed elastic control method for a microgrid based on a confidence factor is used for elastically controlling reactive power and average voltage of an island microgrid under false data injection attack, and in practical application, as shown in fig. 1, the method specifically includes the following steps:
step 1) carrying out primary control according to the formula (1) to maintain the power balance of the microgrid:
Figure BDA0003108802660000061
in the formula, ωiAnd viRespectively representing the angular frequency and amplitude, omega, of the output AC voltage of the ith distributed power supply0And v0Nominal values, m, respectively representing the angular frequency and amplitude of the designed output AC voltageiAnd niRespectively representing the droop coefficients of angular frequency and voltage, PiAnd QiRespectively representing the active power and the reactive power output by the distributed power supply.
Step 2) determining and determining a local detection result of the distributed power supply i on the false data injection attack according to the formula (2):
Figure BDA0003108802660000062
in the formula,liA local detection signal representative of distributed power source i;
Figure BDA0003108802660000063
and a reference value representing the q-axis current component in the primary control of the distributed power source i is obtained by the inverter double-ring controller. If the distributed power i is not attacked, then l i0, the local information is credible; if the distributed power i is attacked li>0, indicating that the local information is not authentic.
Step 3) updating the local confidence factor of the distributed power supply i according to the formula (3):
Figure BDA0003108802660000064
in the formula (I), the compound is shown in the specification,
Figure BDA0003108802660000065
represents the local confidence factor ciA derivative with respect to time; alpha is alpha>0 denotes a convergence parameter for adjusting the local confidence factor ciThe update speed of (2); deltaiA detection threshold is indicated for distinguishing attack signals from other perturbations. If no attack occurs in the local detection result, when the system reaches the steady statei=0,k i1, thus c i1, normally performing distributed control in the microgrid; if an attack signal is detected locally, then li>0,ki(t)<1, thereby ci<1, gradually reducing local reactive power control deviation depending on the size of an attack signal; if c isiLess than a set threshold cth,iThen c isi=0。
Step 4) updating the neighbor confidence factor of the distributed power supply i according to the formula (4):
Figure BDA0003108802660000071
in the formula (I), the compound is shown in the specification,
Figure BDA0003108802660000072
representing neighbor confidence factor TijA derivative with respect to time; beta is aj>0 denotes a convergence parameter for adjusting the neighbor confidence factor TijThe update speed of (2); sigmaiRepresenting an update threshold for distinguishing attack signals from other perturbations; | NiL represents the number of neighbors of the distributed power supply i;
Figure BDA0003108802660000073
represents the average of the neighbor reactive power estimates for distributed power source i. If the data of the neighbor distributed power supply j is credible, the system reaches the steady state
Figure BDA0003108802660000074
sij1, thus T ij1, normally performing distributed control in the microgrid; if the data of the neighbor distributed power j is injected into the attack signal, then
Figure BDA0003108802660000075
sij<1, thus Tij<1 and depend on
Figure BDA0003108802660000076
The larger the value of (A), TijThe smaller the estimated value of the reactive power information of the neighbor distributed power supply is, the less credible the estimated value is, and the influence of the neighbor information on the local reactive power control deviation needs to be gradually reduced; if T isijLess than a set threshold Tth,ijAnd the information of the neighbor distributed power supply j exits the local consistency coordination process to prevent the system from being unstable.
Step 5) distributed secondary control is carried out according to the formula (5) to realize reactive power equalization and average voltage recovery:
Figure BDA0003108802660000077
in the formula uiRepresenting the secondary voltage control quantity of the distributed power supply i;
Figure BDA0003108802660000081
and
Figure BDA0003108802660000082
respectively representing the voltage amplitude and the reactive power control quantity of the distributed power source i; v. ofrefAnd QrefRespectively representing the reference values of the voltage amplitude and the reactive power control deviation of the microgrid; hv=(kPv+kIvS) and HQ=(kPQ+kIQ/s) PI controllers, k) representing the voltage amplitude and the reactive power, respectively, of the distributed generator ipv、kpQ、kivAnd kiQRespectively representing proportional and integral parameters of the PI controller;
Figure BDA0003108802660000083
representing an average voltage estimate of the distributed power source i;
Figure BDA0003108802660000084
representing the reactive power control deviation of the distributed power source i;
Figure BDA0003108802660000085
represents the average voltage control deviation of the distributed power source i; a isijRepresenting a communication coupling gain parameter, if the distributed power source i and the distributed power source j are connected through a communication line, aijNot equal to 0, otherwise, aij=0;
Figure BDA0003108802660000086
Representing an average voltage estimate for distributed power source j; n is a radical of hydrogeniA set of neighbors representing the ith agent; c. CiA local confidence factor representing the distributed power source i; t isijRepresenting a confidence factor of the distributed power source i to the neighbor distributed power source j;
Figure BDA0003108802660000087
representing an estimate of the reactive power of the distributed power source j.
The designed technical scheme is applied to the reality, the simulation system is shown in fig. 2, the microgrid is composed of 5 distributed power supplies, namely, a grid-connected node, wherein the grid-connected node is connected with a DG1, a DG2, a DG3, a DG4 and a DG5 through respective connection impedances, and the DG2 and the DG4 are provided with local loads. The rated active and reactive capacities of the 5 distributed power supplies are equal, each distributed power supply is provided with an agent respectively represented by A1, A2, A3, A4 and A5, and the load in the system adopts an impedance type load. According to the microgrid distributed communication topology design method, communication topology is designed and selected, a simulation microgrid model is built based on an MATLAB/Simulink platform, the control effect of an island operation microgrid under false data injection attack is simulated, and the control effect of the method is verified.
When the simulation is started, the micro-grid operates under primary droop control, and distributed secondary voltage control is started when t is 0.5 s. At t 2s, the Load1 increases by 10kW +5kvar and is cut off at t 4 s. At t 3s, the attacker performs a dummy data injection attack on the reactive power information of information node a1 in fig. 2, and stops the attack at t 5 s. The simulation results without the method of the present invention are shown in fig. 3, and the simulation results with the method of the present invention are shown in fig. 4.
In fig. 3, when t is 3s, a1 is directly attacked by destruction, so that reactive power output by distributed power supply DG1 under attack is sharply reduced, and even reactive power is absorbed, so that reactive power output by other distributed power supplies changes, and grid-connected voltage of the distributed power supplies also continuously decreases, thereby causing system voltage drop.
In FIG. 4, the operating conditions are substantially the same as when not attacked, and the local detection of A1 successfully identifies the spurious data injection attack and updates the local confidence factor c1And (3) the secondary reactive power control of the DG1 is stopped working when the reactive power is 0, so that the network safety of the micro-grid is guaranteed. At this time, a1 is equivalent to a leader in the system, and reactive power output by other distributed power supplies follows DG1, so that all distributed power supplies in the microgrid can output reactive power and can still realize equal division.
It can be seen from this embodiment that, by using the control method of the present invention, the elastic operation of the reactive power average and the average voltage recovery of the system is realized, a normal communication scenario and a network attack scenario are considered, a basis is provided for the control structure design of the distributed secondary control, and further, the operation elasticity of the microgrid is improved. The method provided by the invention has a good control effect.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing shows and describes the general principles, principal features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.

Claims (2)

1. A distributed elastic control method for a microgrid based on a confidence factor is characterized by comprising the following steps:
s1: primary droop control of the micro-grid;
s2: local detection of spurious data injection attacks;
s3: updating a local confidence factor based on the local detection;
s4: updating the neighbor confidence factor based on the neighbor mean value;
s5: establishing a distributed secondary voltage reactive power control rate to realize the reactive power equalization and the average voltage recovery of the microgrid under normal conditions and network attacks;
the S2 includes: determining a local detection result of the distributed power supply on the virtual data injection attack, and determining according to the following formula:
Figure FDA0003570701570000011
in the formula IiA local detection signal representative of a distributed power source i;
Figure FDA0003570701570000012
a reference value representing a q-axis current component in primary control of the distributed power source i is obtained through an inverter double-ring controller; if the distributed power i is not attacked, then li0, the local information is credible; if the distributed power i is attacked li> 0, indicating that the local information is not trusted;
in S3, the local confidence factor of the distributed power supply is updated according to the following formula:
Figure FDA0003570701570000013
in the formula (I), the compound is shown in the specification,
Figure FDA0003570701570000014
represents the local confidence factor ciA derivative with respect to time; alpha > 0 denotes a convergence parameter for adjusting the local confidence factor ciThe update speed of (2); deltaiRepresenting a detection threshold for distinguishing attack signals from other perturbations; if no attack occurs in the local detection result, when the system reaches the steady statei=0,ki1, thus ci1, normally performing distributed control in the microgrid; if an attack signal is detected locally, then li>0,ki(t) < 1, whereby ci< 1 and gradually reducing local reactive power control deviation depending on the size of the attack signal; if c isiLess than a set threshold cth,iThen c isi=0;
Updating the neighbor confidence factor of the distributed power supply in the step S4 according to the following formula;
Figure FDA0003570701570000021
in the formula (I), the compound is shown in the specification,
Figure FDA0003570701570000022
representing an estimate of the reactive power of the distributed power source j,
Figure FDA0003570701570000023
representing neighbor confidence factor TijA derivative with respect to time; beta is aj> 0 denotes a convergence parameter for adjusting the neighbor confidence factor TijThe update speed of (2); sigmaiRepresenting an update threshold for distinguishing attack signals from other perturbations; | NiL represents the number of neighbors of the distributed power supply i;
Figure FDA0003570701570000024
representing an average of the neighbor reactive power estimates for distributed power source i; if the data of the neighbor distributed power supply j is credible, the system reaches the steady state
Figure FDA0003570701570000025
sij1, thus Tij1, normally performing distributed control in the microgrid; if the data of the neighbor distributed power j is injected into the attack signal, then
Figure FDA0003570701570000026
Figure FDA0003570701570000027
sij< 1, thus Tij< 1 and depend on
Figure FDA0003570701570000028
The larger the value of (A), TijThe smaller the estimated value of the reactive power information of the neighbor distributed power supply is, the less credible the estimated value of the reactive power information of the neighbor distributed power supply is, and the need of gradually reducing the local power of the neighbor information isThe effect of reactive power control deviation; if T isijLess than a set threshold Tth,ijIf so, the information of the neighbor distributed power supply j exits the local consistency coordination process to prevent the system from being unstable;
the distributed quadratic control in S5 is controlled by the following formula:
Figure FDA0003570701570000031
in the formula uiRepresenting the secondary voltage control quantity of the distributed power supply i;
Figure FDA0003570701570000032
and
Figure FDA0003570701570000033
respectively representing the voltage amplitude and the reactive power control quantity of the distributed power source i; v. ofrefAnd QrefRespectively representing the reference values of the voltage amplitude and the reactive power control deviation of the microgrid; hv=(kpv+kivS) and HQ=(kpQ+kiQ/s) PI controllers, k) representing the voltage amplitude and reactive power, respectively, of the distributed power supply ipv、kpQ、kivAnd kiQRespectively representing proportional and integral parameters of the PI controller;
Figure FDA0003570701570000034
representing an average voltage estimate of the distributed power source i;
Figure FDA0003570701570000035
representing the reactive power control deviation of the distributed power source i;
Figure FDA0003570701570000036
represents the average voltage control deviation of the distributed power source i; a isijRepresenting a communication coupling gain parameter if distributed power source i and distributed power source j are connected via a communication line,aijNot equal to 0, otherwise, aij=0;
Figure FDA0003570701570000037
Representing an average voltage estimate for distributed power source j; n is a radical ofiA set of neighbors representing the ith agent; c. CiA local confidence factor representing the distributed power source i; t isijRepresenting the confidence factor of the distributed power source i to the neighbor distributed power source j.
2. The microgrid distributed elastic control method based on a confidence factor as claimed in claim 1, wherein primary droop control of the microgrid in the step S1 is controlled by the following formula:
Figure FDA0003570701570000038
in the formula, omegaiAnd viRespectively representing the angular frequency and amplitude, omega, of the output AC voltage of the ith distributed power supply0And v0Nominal values, m, respectively representing the angular frequency and amplitude of the designed output AC voltageiAnd niRespectively representing the droop coefficients of angular frequency and voltage, PiAnd QiRespectively representing the active power and the reactive power output by the distributed power supply.
CN202110643162.7A 2021-06-09 2021-06-09 Micro-grid distributed elastic control method based on confidence factors Active CN113285496B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110643162.7A CN113285496B (en) 2021-06-09 2021-06-09 Micro-grid distributed elastic control method based on confidence factors

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110643162.7A CN113285496B (en) 2021-06-09 2021-06-09 Micro-grid distributed elastic control method based on confidence factors

Publications (2)

Publication Number Publication Date
CN113285496A CN113285496A (en) 2021-08-20
CN113285496B true CN113285496B (en) 2022-05-31

Family

ID=77283908

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110643162.7A Active CN113285496B (en) 2021-06-09 2021-06-09 Micro-grid distributed elastic control method based on confidence factors

Country Status (1)

Country Link
CN (1) CN113285496B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114512983B (en) * 2022-03-02 2024-05-07 国网浙江省电力有限公司信息通信分公司 Distributed power supply elasticity control method for network attack

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112701723B (en) * 2020-12-22 2022-12-16 华南理工大学 Micro-grid economic control system and method for resisting data tampering attack
CN112701729B (en) * 2021-01-08 2022-09-27 东北大学 Micro-grid distributed cooperative control system and method based on edge calculation

Also Published As

Publication number Publication date
CN113285496A (en) 2021-08-20

Similar Documents

Publication Publication Date Title
CN108363306B (en) Micro-grid distributed controller parameter determination method based on linear quadratic optimization
CN105896537B (en) A kind of power distribution network service restoration method based on intelligent Sofe Switch
CN111953013A (en) Self-adaptive optimization regulation and control method under fault of true bipolar flexible direct-current transmission system
CN113285495B (en) Micro-grid distributed synchronous detection method for false injection attack
CN113285496B (en) Micro-grid distributed elastic control method based on confidence factors
CN113206500B (en) Micro-grid distributed secondary control clock synchronization method based on event triggering
CN112311007A (en) Design method of three-phase LCL type grid-connected conversion controller in photovoltaic power generation system
CN108985561A (en) A kind of active power distribution network isolated island division methods based on chance constraint
Zhang et al. Distributed control strategy of DC microgrid based on consistency theory
Gao et al. Distributed multi‐agent control for combined AC/DC grids with wind power plant clusters
CN113300405B (en) Island protection method and system with island fault ride-through capability
Ahilan Wind connected distribution system with intelligent controller based compensators for power quality issues mitigation
CN112600214B (en) Micro-grid average voltage observer based on distributed proportional consistency
CN108599974B (en) Micro-grid distributed communication topology design method based on graph theory connectivity
CN109560557A (en) A kind of micro-capacitance sensor frequency intelligence control system and its frequency stabilization control algolithm
WO2022041364A1 (en) Smooth switching method for control policy of voltage-source-type converter
Sahoo et al. Multi‐mode control and operation of a self‐sufficient multi‐microgrid system
Fan et al. Controlled islanding algorithm for AC/DC hybrid power systems utilising DC modulation
Li et al. Robust nonlinear control of DFIG-based wind farms for damping inter-area oscillations of power systems
Lai et al. Distributed voltage control for DC mircogrids with coupling delays & noisy disturbances
Sheng et al. Comprehensive fault simulation method in active distribution network with the consideration of cyber security
Sahoo et al. Execution of advanced solar‐shunt active filter for renewable power application
Lv et al. Multi‐resolution modelling method based on time‐state‐machine in complex distribution network
CN110649661A (en) Low-voltage annular micro-grid control system and method based on virtual synchronous generator
Du et al. Operation and coordination control scheme of an enhanced AC–DC hybrid microgrid under abnormal distribution network

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