Office Action 1: Notice of Allowance (2024-11-12)

CLAIMS:
CLAIMS WHAT IS CLAIMED IS:
1\. A microgrid self-triggering control method for resisting false data injection (FDI) attacks, comprising the following steps: S1: adopting a primary control based on a droop control for a microgrid; S2: designing a secondary control strategy of the microgrid, wherein the secondary control strategy comprises a frequency recovery and a fair distribution of an active power; wherein the S2 comprises the following steps: for the frequency recovery, recovering a frequency setting of the microgrid by adopting a local proportional-integral (PI) control method; and for the fair distribution of the active power, setting an active power self-triggering controller for each distributed generation i in the microgrid, and achieving the fair distribution of the active power through the active power self-triggering controller, wherein a distributed secondary control target of the microgrid is as follows: wherein SVG {EMBED HERE} , SVG {EMBED HERE} is a reference frequency, SVG {EMBED HERE} is an output frequency of the distributed generation i; for the frequency recovery, a frequency set point SVG {EMBED HERE} is adjusted by adopting a local PI control to recover a voltage and a frequency of each distributed generation to a reference value, wherein an expression of the frequency set point SVG {EMBED HERE} is as follows: wherein SVG {EMBED HERE} is a frequency control input, SVG {EMBED HERE} is an active power control input, SVG {EMBED HERE} is a terminal active power of the distributed generation i, and SVG {EMBED HERE} is a SVG {EMBED HERE} control droop coefficient of the distributed generation i; an expression of recovering the frequency of each distributed generation by adopting the local PI control is as follows: wherein SVG {EMBED HERE} is the reference frequency, SVG {EMBED HERE} and SVG {EMBED HERE} are a proportional coefficient and an integral coefficient of a local PI controller, respectively; for an active power distribution, an expression of designing the active power control input SVG {EMBED HERE} is as follows: wherein SVG {EMBED HERE} is a neighbor set of the distributed generation i; an expression of performing an aperiodic triggering by designing a distributed active power self-triggering controller is as follows: wherein SVG {EMBED HERE} 0.406250.5625 is an active power state variable of the distributed generation i, SVG {EMBED HERE} is a local active power control input of the distributed generation i and a distributed generation j, and SVG {EMBED HERE} is a clock variable on a communication link SVG {EMBED HERE} ; an expression of defining a trigger rule of the distributed active power self-triggering controller is as follows: wherein when SVG {EMBED HERE} reaches 0, the distributed generation i obtains active power state information of the distributed generation j, then the local active power control input SVG {EMBED HERE} and the clock variable SVG {EMBED HERE} are correspondingly updated, and an expression of an active power difference SVG {EMBED HERE} between the distributed generation i and the distributed generation j at a moment SVG {EMBED HERE} is as follows: correspondingly, an expression of an update rule for designing the local active power control input SVG {EMBED HERE} is as follows: wherein SVG {EMBED HERE} meets a following formula: wherein SVG {EMBED HERE} is a sign function, SVG {EMBED HERE} is a constant, and SVG {EMBED HERE} is a preset active power error; an update rule for designing the clock variable SVG {EMBED HERE} is as follows: wherein SVG {EMBED HERE} is represented as: correspondingly, a trigger moment of the distributed active power self-triggering controller is defined as: achieving the fair distribution of the active power by above processes; S3: designing a microgrid distributed self-triggering control method of a hash encryption method after considering a condition that the FDI attacks are injected into a secondary control communication link, to resist false malicious data in the microgrid and achieve a secondary control, wherein the S3 comprises the following steps: S31: the distributed generation performs a hash transformation on an active power value to be transmitted to obtain a corresponding self hash transformation value and sends the corresponding self hash transformation value to an adjacent distributed generation; S32: after the adjacent distributed generation receives a corresponding data packet, the adjacent distributed generation performs the hash transformation on a received active power value to obtain a corresponding received hash transformation value, wherein the corresponding received hash transformation value is expressed as: SVG {EMBED HERE} 0.656252.34375图片包含 图示 描述已自动生成 (14) wherein SVG {EMBED HERE} is a binary value of the active power SVG {EMBED HERE} , and SVG {EMBED HERE} is a binary value of SVG {EMBED HERE} shifted to a left by 3 bits; and therefore, a hash transformation of the active power SVG {EMBED HERE} is represented as: SVG {EMBED HERE} ; S33: the adjacent distributed generation judges the corresponding self hash transformation value and the corresponding received hash transformation value, if the two hash values are not equal, the adjacent distributed generation is judged to suffer from the FDI attacks, and otherwise, the adjacent distributed generation is not attacked by the FDI attacks, comprising as follows: each distributed generation sends an active power value of each distributed generation and a corresponding hash transformation value to the adjacent distributed generation, when receiving the corresponding data packet, the adjacent distributed generation performs the hash transformation on the received active power value, and compares the corresponding received hash transformation value with a hash value obtained after the hash transformation is performed on the corresponding received hash transformation value, and if the two hash values are not equal, an FDI attack signal is detected to be received.
2\. The microgrid self-triggering control method for resisting the FDI attacks according to claim 1, further comprising the following step: S4: performing a verification by a Lyapunov stability method and a simulation experiment.
3\. The microgrid self-triggering control method for resisting the FDI attacks according to claim 1, wherein in the S1, the microgrid adjusts an output of each distributed generation by adopting a primary control strategy based on the droop control to achieve a rapid balance between a load and an output power in the microgrid.
4\. The microgrid self-triggering control method for resisting the FDI attacks according to claim 1, wherein in the S33, when the FDI attacks occur, the corresponding received hash transformation value is not used, but an active power value before the transformation is used.
5\. A control system using the microgrid self-triggering control method for resisting the FDI attacks according to claim 1, comprising: a primary control module, configured to adjust an output of each distributed generation in the microgrid by applying a droop control strategy to achieve a rapid balance between a load and an output power in the microgrid; a secondary control module, configured to design the secondary control strategy of the microgrid, wherein the secondary control strategy comprises the frequency recovery and the fair distribution of the active power; and an attack module, configured to design the microgrid distributed self-triggering control method of the hash encryption method after considering the condition that the FDI attacks are injected into the secondary control communication link to resist the false malicious data in the microgrid and achieve the secondary control.
6\. The control system according to claim 5, further comprising: a verification module, configured to perform a verification by applying a Lyapunov stability method and a simulation experiment.
7\. The control system according to claim 5, wherein the microgrid self-triggering control method further comprises the following step: S4: performing a verification by a Lyapunov stability method and a simulation experiment.
8\. The control system according to claim 5, wherein in the S1 of the microgrid self-triggering control method, the microgrid adjusts the output of each distributed generation by adopting a primary control strategy based on the droop control to achieve the rapid balance between the load and the output power in the microgrid.
9\. The control system according to claim 5, wherein in the S33 of the microgrid self-triggering control method, when the FDI attacks occur, the corresponding received hash transformation value is not used, but an active power value before the transformation is used.

OFFICE ACTION:
DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-9 are allowed.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/14/24 is being considered by the examiner.
EXAMINER’S AMENDMENT
An examiner’s amendment to the record appears below. Should the changes and/or additions be unacceptable to applicant, an amendment may be filed as provided by 37 CFR 1.312. To ensure consideration of such an amendment, it MUST be submitted no later than the payment of the issue fee.
Authorization for this examiner’s amendment was given in an interview with Tsung Wu on 10/25/24.
The application has been amended as follows:
1. (Currently Amended) A microgrid self-triggering control method for resisting false data injection (FDI) attacks, wherein the microgrid self-triggering control method is performed by a control system of a microgrid containing electronic circuitries, and the method comprises[[ing]] the following steps:
S1: adopting a primary control based on a droop control for [[a ]]the microgrid;
S2: generating a secondary control strategy of the microgrid, wherein the secondary control strategy comprises a frequency recovery and a [[fair ]]distribution of an active power; wherein the S2 comprises the following steps:
for the frequency recovery, recovering a frequency setting of the microgrid by adopting a local proportional-integral (PI) control method; and
for the [[fair ]]distribution of the active power, setting an active power self-triggering controller for each distributed generation i in the microgrid, wherein each of the distributed generation i represents a distributed power in the microgrid, and achieving the [[fair ]]distribution of the active power through the active power self-triggering controller, wherein a distributed secondary control target of the microgrid is as follows:
PNG
media_image1.png
32
108
media_image1.png
Greyscale
PNG
media_image2.png
25
117
media_image2.png
Greyscale
wherein
PNG
media_image3.png
23
83
media_image3.png
Greyscale
,
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media_image4.png
28
32
media_image4.png
Greyscale
is a reference frequency in Hz,
PNG
media_image5.png
25
20
media_image5.png
Greyscale
is an output frequency of the distributed generation i, wherein
PNG
media_image6.png
28
39
media_image6.png
Greyscale
is an active power state variable of the distributed generation i, with both
m
and
p
not equal to zero;
for the frequency recovery, a frequency set point
PNG
media_image7.png
28
31
media_image7.png
Greyscale
is adjusted by adopting a local PI control to recover a voltage and a frequency of each distributed generation to a reference value, wherein an expression of the frequency set point
PNG
media_image7.png
28
31
media_image7.png
Greyscale
is as follows:
PNG
media_image8.png
25
167
media_image8.png
Greyscale
wherein
PNG
media_image9.png
25
24
media_image9.png
Greyscale
is a frequency control input,
PNG
media_image10.png
25
24
media_image10.png
Greyscale
is an active power control input,
PNG
media_image11.png
24
16
media_image11.png
Greyscale
is a terminal active power of the distributed generation i, and
PNG
media_image12.png
28
28
media_image12.png
Greyscale
is a
PNG
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20
47
media_image13.png
Greyscale
control droop coefficient of the distributed generation i;
an expression of recovering the frequency of each distributed generation by adopting the local PI control is as follows:
PNG
media_image14.png
29
245
media_image14.png
Greyscale
wherein
PNG
media_image4.png
28
32
media_image4.png
Greyscale
is the reference frequency, [[
PNG
media_image15.png
25
21
media_image15.png
Greyscale
]]
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media_image16.png
25
49
media_image16.png
Greyscale
and [[
PNG
media_image17.png
25
19
media_image17.png
Greyscale
]]
PNG
media_image18.png
25
48
media_image18.png
Greyscale
are a proportional coefficient and an integral coefficient of a local PI controller, respectively;
for an active power distribution, an expression of designing the active power control input
PNG
media_image19.png
25
24
media_image19.png
Greyscale
is as follows:
PNG
media_image20.png
39
196
media_image20.png
Greyscale
wherein
PNG
media_image21.png
25
49
media_image21.png
Greyscale
is an active power control gain,
PNG
media_image22.png
25
23
media_image22.png
Greyscale
is a neighbor set of the distributed generation i,
PNG
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28
73
media_image23.png
Greyscale
is the adjacent parameter associated with distributed generation i and distributed generation j,
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28
47
media_image24.png
Greyscale
means that distributed generation i is the neighbor of distributed generation j,
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media_image25.png
28
49
media_image25.png
Greyscale
means that distributed generation i is not the neighbor of distributed generation j;
an expression of performing an aperiodic triggering by designing a distributed active power self-triggering controller is as follows:
PNG
media_image26.png
121
153
media_image26.png
Greyscale
wherein
PNG
media_image27.png
39
54
media_image27.png
Greyscale
is an active power state variable of the distributed generation i,
PNG
media_image28.png
29
108
media_image28.png
Greyscale
is a local active power control input of the distributed generation i and a distributed generation j, and
PNG
media_image29.png
24
23
media_image29.png
Greyscale
is a clock variable on a communication link
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28
71
media_image30.png
Greyscale
;
an expression of defining a trigger rule of the distributed active power self-triggering controller is as follows:
wherein when
PNG
media_image29.png
24
23
media_image29.png
Greyscale
reaches 0, the distributed generation i obtains active power state information of the distributed generation j, then the local active power control input
PNG
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24
21
media_image31.png
Greyscale
and the clock variable
PNG
media_image32.png
24
23
media_image32.png
Greyscale
are correspondingly updated, and an expression of an active power difference
PNG
media_image33.png
29
68
media_image33.png
Greyscale
between the distributed generation i and the distributed generation j at a moment
PNG
media_image34.png
17
11
media_image34.png
Greyscale
is as follows:
PNG
media_image35.png
31
225
media_image35.png
Greyscale
correspondingly, an expression of an update rule for designing the local active power control input
PNG
media_image31.png
24
21
media_image31.png
Greyscale
is as follows:
PNG
media_image36.png
65
337
media_image36.png
Greyscale
wherein
PNG
media_image37.png
33
124
media_image37.png
Greyscale
meets a following formula:
PNG
media_image38.png
65
412
media_image38.png
Greyscale
wherein
PNG
media_image39.png
28
63
media_image39.png
Greyscale
is a sign function,
PNG
media_image40.png
23
43
media_image40.png
Greyscale
is a constant, and
PNG
media_image41.png
20
41
media_image41.png
Greyscale
is a preset active power error;
an update rule for designing the clock variable
PNG
media_image32.png
24
23
media_image32.png
Greyscale
is as follows:
PNG
media_image42.png
65
317
media_image42.png
Greyscale
wherein
PNG
media_image43.png
33
103
media_image43.png
Greyscale
is represented as:
PNG
media_image44.png
107
300
media_image44.png
Greyscale
correspondingly, a trigger moment of the distributed active power self-triggering controller is defined as:
PNG
media_image45.png
36
183
media_image45.png
Greyscale
wherein
PNG
media_image46.png
28
16
media_image46.png
Greyscale
is a kth triggering moment of the active power self-triggering controller of distributed generation i;
achieving the [[fair ]]distribution of the active power by above processes;
S3: generating a microgrid distributed self-triggering control method of a hash encryption method after considering a condition that the FDI attacks are injected into a secondary control communication link, to resist false malicious data in the microgrid and achieve a secondary control, wherein the S3 comprises the following steps:
S31: the distributed generation performs a hash transformation on an active power value to be transmitted to obtain a corresponding self hash transformation value and sends the corresponding self hash transformation value to an adjacent distributed generation;
S32: after the adjacent distributed generation receives a corresponding data packet, the adjacent distributed generation performs the hash transformation on a received active power value to obtain a corresponding received hash transformation value, wherein the corresponding received hash transformation value is expressed as:
PNG
media_image47.png
63
225
media_image47.png
Greyscale
(14)
wherein
PNG
media_image48.png
28
27
media_image48.png
Greyscale
is a binary value of the active power
PNG
media_image49.png
28
20
media_image49.png
Greyscale
, and
PNG
media_image50.png
33
61
media_image50.png
Greyscale
is a binary value of
PNG
media_image48.png
28
27
media_image48.png
Greyscale
shifted to a left by 3 bits; and therefore, a hash transformation of the active power
PNG
media_image49.png
28
20
media_image49.png
Greyscale
is represented as:
PNG
media_image51.png
28
68
media_image51.png
Greyscale
;
S33: the adjacent distributed generation judges the corresponding self hash transformation value and the corresponding received hash transformation value, [[if ]]when the two hash values are not equal, the adjacent distributed generation is judged to suffer from the FDI attacks, and otherwise, the adjacent distributed generation is not attacked by the FDI attacks, comprising as follows:
each distributed generation sends an active power value of each distributed generation and a corresponding hash transformation value to the adjacent distributed generation, when receiving the corresponding data packet, the adjacent distributed generation performs the hash transformation on the received active power value, and compares the corresponding received hash transformation value with a hash value obtained after the hash transformation is performed on the corresponding received hash transformation value, and [[if ]]when the two hash values are not equal, an FDI attack signal is detected to be received.
2. (Original) The microgrid self-triggering control method for resisting the FDI attacks according to claim 1, further comprising the following step:
S4: performing a verification by a Lyapunov stability method and a simulation experiment.
3. (Original) The microgrid self-triggering control method for resisting the FDI attacks according to claim 1, wherein in the S1, the microgrid adjusts an output of each distributed generation by adopting a primary control strategy based on the droop control to achieve a rapid balance between a load and an output power in the microgrid.
4. (Original) The microgrid self-triggering control method for resisting the FDI attacks according to claim 1, wherein in the S33, when the FDI attacks occur, the corresponding received hash transformation value is not used, but an active power value before the transformation is used.
5. (Currently Amended) A control system using the microgrid self-triggering control method for resisting the FDI attacks according to claim 1, comprising:
a primary control circuitry, configured to adjust an output of each distributed generation in the microgrid by applying a droop control strategy to achieve a rapid balance between a load and an output power in the microgrid;
a secondary control circuitry, configured to design the secondary control strategy of the microgrid, wherein the secondary control strategy comprises the frequency recovery and the [[fair ]]distribution of the active power; and
an attack circuitry, configured to design the microgrid distributed self-triggering control method of the hash encryption method after considering the condition that the FDI attacks are injected into the secondary control communication link to resist the false malicious data in the microgrid and achieve the secondary control.
6. (Currently Amended) The control system according to claim 5, further comprising:
a verification circuitry, configured to perform a verification by applying a Lyapunov stability method and a simulation experiment.
7. (Original) The control system according to claim 5, wherein the microgrid self-triggering control method further comprises the following step:
S4: performing a verification by a Lyapunov stability method and a simulation experiment.
8. (Original) The control system according to claim 5, wherein in the S1 of the microgrid self-triggering control method, the microgrid adjusts the output of each distributed generation by adopting a primary control strategy based on the droop control to achieve the rapid balance between the load and the output power in the microgrid.
9. (Original) The control system according to claim 5, wherein in the S33 of the microgrid self-triggering control method, when the FDI attacks occur, the corresponding received hash transformation value is not used, but an active power value before the transformation is used.
Allowable Subject Matter
The following is an examiner’s statement of reasons for allowance:
Qi et al. U.S. Pub. No. 20220342435 discloses distributed collaborative control method for a microgrid frequency under attack of false data injection based on cyber-physical fusion by establishing simulation model to simulate communication among distributed generations based on an OPNET.
Nakayama et al. U.S. Pub. No. 20190113549 discloses detection of false data injection attacks in power systems using multiplex invariant networks and domain knowledge by detecting an anomaly from the invariant relationships for the plurality of meters with a residual anomaly threshold.
Ma et al. CN 116904769A discloses micro-grid control method for resisting false data injection attack, which belongs to the technical field of micro-grid safety and comprises the steps of constructing a port micro-grid model based on distributed secondary control under FDI attack, constructing a secondary controller based on an extended state observer, expanding an attack signal into a system state to obtain an augmentation system, estimating the attack signal in real time by using the proposed extended state observer, and compensating the attack by using the proposed secondary controller when the FDI attack occurs, so as to realize the frequency, voltage recovery and power distribution of the port micro-grid.
The prior art of record, individually or in combination, does not explicitly disclose the specific mathematical equations recited in independent claims to detect and resist false data injection by a control system in microgrid containing electronic circuitries.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion



CITED REFERENCE SUMMARIES: Ref US20220342435A1: Claims:
A stimulation method of distributed collaborative control for a microgrid frequency under attack of false data injection based on cyber-physical fusion, comprising following steps: S1, establishing a distributed collaborative control simulation model for a microgrid frequency based on a RT_LAB real-time simulation tool OPAL-RT; S2, designing a distributed collaborative control algorithm for a microgrid under the attack of false data injection based on a DSP; S3, simulating a real-time communication among distributed generations based on an OPNET; and S4, simulating constant injection of false data such that the microgrid frequency is strictly tracked to a reference frequency ultimately.
S1, establishing a distributed collaborative control simulation model for a microgrid frequency based on a RT_LAB real-time simulation tool OPAL-RT;
S2, designing a distributed collaborative control algorithm for a microgrid under the attack of false data injection based on a DSP;
S3, simulating a real-time communication among distributed generations based on an OPNET; and
S4, simulating constant injection of false data such that the microgrid frequency is strictly tracked to a reference frequency ultimately.
The stimulation method of distributed collaborative control for microgrid frequency under the attack of false data injection based on cyber-physical fusion according to claim 1 , wherein the step S1 specifically comprises: establishing a simulation model of a distributed generation cluster in a RT-LAB, realizing a physical mirror image of the cluster, and using a target machine to expand a signal output port of the cluster, wherein the simulation model includes two parts, a first part is a primary circuit module composed of a distributed generation with a voltage source converter (VSC) and a three-phase AC load of the microgrid, and a second part is a secondary control module composed of a plurality of distributed generation PWM pulse control modules.
establishing a simulation model of a distributed generation cluster in a RT-LAB, realizing a physical mirror image of the cluster, and using a target machine to expand a signal output port of the cluster, wherein the simulation model includes two parts, a first part is a primary circuit module composed of a distributed generation with a voltage source converter (VSC) and a three-phase AC load of the microgrid, and a second part is a secondary control module composed of a plurality of distributed generation PWM pulse control modules.
The stimulation method of distributed collaborative control for microgrid frequency under the attack of false data injection based on cyber-physical fusion according to claim 2 , wherein the step S2 specifically comprises: acquiring analog quantity from the signal output port of the RT-LAB of the secondary control module by the DSP to realize a distributed collaborative control algorithm for the microgrid under the attack of false data injection, wherein a digital signal is uploaded to the secondary control module in the RT-LAB through a preset communication protocol.
acquiring analog quantity from the signal output port of the RT-LAB of the secondary control module by the DSP to realize a distributed collaborative control algorithm for the microgrid under the attack of false data injection, wherein a digital signal is uploaded to the secondary control module in the RT-LAB through a preset communication protocol.
The stimulation method of distributed collaborative control for microgrid frequency under the attack of false data injection based on cyber-physical fusion according to claim 2 , wherein in the step S2, the distributed collaborative control algorithm for the microgrid frequency under the attack of false data injection specifically comprises: in the microgrid, accessing the distributed generations to the microgrid through the VSC to supply power to the microgrid, and controlling active power and reactive power of an output of the VSC by a traditional droop control method;
in the microgrid, accessing the distributed generations to the microgrid through the VSC to supply power to the microgrid, and controlling active power and reactive power of an output of the VSC by a traditional droop control method;
{ Ï i = Ï n , i - m p , i â¢ P i U m â¢ a â¢ g , i = U n , i - n q , i â¢ Q i ( 1 ) wherein Ï i and U mag,i are an angular frequency and a voltage of an output of an inverter i respectively, P i and Q i are an active power and a reactive power of the output of the inverter i respectively; m p,i and n q,i are an active droop coefficient and a reactive droop coefficient of the inverter i respectively, which are obtained by a rated value of the inverter; Ï n,i and U n,i are an angular frequency and a voltage set point of the inverter i respectively; performing a secondary control to compensate for frequency and voltage deviations in a droop control; wherein the secondary control is intended to restore a frequency and a voltage to a normal working range by adjusting the angular frequency and the voltage set point; only distributed collaborative control under attack is analyzed, and a control objective is that in the case of attack, a secondary control algorithm is designed to satisfy a following formula: lim tââ |Ï i âÏ ref =0ââ(2) wherein Ï i is an angular frequency of the i th distributed generation; Ï ref is a reference angular frequency; and t denotes a control time; in order to achieve the above control objective by using distributed collaborative control, designing an auxiliary controller to obtain a control input Ï n,i in Formula (2); differentiating the Formula (1) as: {dot over (Ï)} i ={dot over (Ï)} n,i âm p,i {dot over (P)} i =u i ââ(3) wherein {dot over (Ï)} i , {dot over (Ï)} n,i and {dot over (P)} i are differentials of Ï i , Ï n,i and P i ; u i is a control rate of the distributed collaborative control algorithm against the attack of false data injection; u i =âk Ï â«[Î£ jâN i a i,j (Ï i âÏ j )+ b i (Ï i âÏ ref )] dtâÏ i ââ(4) wherein k Ï , a i,j , b i are all control coefficients, Ï i is an angular frequency of the i th distributed generation, Ï j is an angular frequency of the j th distributed generation, and N i is a set of distributed generations collaborating with the distributed generation i; the design of the above control rate is capable of eliminating the influence on the secondary control when the false data injection is a constant.
wherein Ï i and U mag,i are an angular frequency and a voltage of an output of an inverter i respectively, P i and Q i are an active power and a reactive power of the output of the inverter i respectively; m p,i and n q,i are an active droop coefficient and a reactive droop coefficient of the inverter i respectively, which are obtained by a rated value of the inverter; Ï n,i and U n,i are an angular frequency and a voltage set point of the inverter i respectively;
performing a secondary control to compensate for frequency and voltage deviations in a droop control; wherein the secondary control is intended to restore a frequency and a voltage to a normal working range by adjusting the angular frequency and the voltage set point; only distributed collaborative control under attack is analyzed, and a control objective is that in the case of attack, a secondary control algorithm is designed to satisfy a following formula: lim tââ |Ï i âÏ ref =0ââ(2)
lim tââ |Ï i âÏ ref =0ââ(2)
wherein Ï i is an angular frequency of the i th distributed generation; Ï ref is a reference angular frequency; and t denotes a control time;
in order to achieve the above control objective by using distributed collaborative control, designing an auxiliary controller to obtain a control input Ï n,i in Formula (2); differentiating the Formula (1) as: {dot over (Ï)} i ={dot over (Ï)} n,i âm p,i {dot over (P)} i =u i ââ(3)
{dot over (Ï)} i ={dot over (Ï)} n,i âm p,i {dot over (P)} i =u i ââ(3)
wherein {dot over (Ï)} i , {dot over (Ï)} n,i and {dot over (P)} i are differentials of Ï i , Ï n,i and P i ; u i is a control rate of the distributed collaborative control algorithm against the attack of false data injection; u i =âk Ï â«[Î£ jâN i a i,j (Ï i âÏ j )+ b i (Ï i âÏ ref )] dtâÏ i ââ(4)
u i =âk Ï â«[Î£ jâN i a i,j (Ï i âÏ j )+ b i (Ï i âÏ ref )] dtâÏ i ââ(4)
wherein k Ï , a i,j , b i are all control coefficients, Ï i is an angular frequency of the i th distributed generation, Ï j is an angular frequency of the j th distributed generation, and N i is a set of distributed generations collaborating with the distributed generation i; the design of the above control rate is capable of eliminating the influence on the secondary control when the false data injection is a constant.
The stimulation method of distributed collaborative control for microgrid frequency under the attack of false data injection based on cyber-physical fusion according to claim 1 , wherein in the step S3, the OPNET acts as a router for simulating signal transmission and reception among distributed generation controllers (DSPs) to realize physical topology simulation and realize interaction of a frequency collaborative control signal of a distributed generation unit.
The stimulation method of distributed collaborative control for microgrid frequency under attack of false data injection based on cyber-physical fusion according to claim 1 , wherein the step S4 specifically comprises: specifying a secondary control attack value for the microgrid frequency by a platform model, simulating the false data injection, and transmitting a frequency fluctuation value to a DSP controller by the RT-LAB simulation model; performing a distributed generation frequency secondary control algorithm in the DSP controller; transmitting the control signal back to RT-LAB simulation model, so as to realize distributed collaborative control for microgrid frequency under the attack of false data injection.
specifying a secondary control attack value for the microgrid frequency by a platform model, simulating the false data injection, and transmitting a frequency fluctuation value to a DSP controller by the RT-LAB simulation model; performing a distributed generation frequency secondary control algorithm in the DSP controller; transmitting the control signal back to RT-LAB simulation model, so as to realize distributed collaborative control for microgrid frequency under the attack of false data injection.
Ref US20200106301A1: Claims:
A method for removing false data in a nested microgrid system, the method comprising: calculating, with a first microgrid control system of a first microgrid, a first local state estimation using a first plurality of local measurements; calculating, with a second microgrid control system of a second microgrid, a second local state estimation using a second plurality of local measurements; calculating, with a central control system, a plurality of global state estimations including a first global state estimation using the first plurality of measurements and the second plurality of measurements, and a second global state estimation using the first local state estimation and the second local state estimation; performing, with the first microgrid control system, a first false data detection test using the first local state estimation and one global state estimation of the plurality of global state estimations; performing, with the central control system, a second false data detection test using the first global state estimation and the second global state estimation; detecting false data in response to performing the first false data detection test or the second false data detection test; and updating the first global state estimation, the second global state estimation, or the first local state estimation in response to detecting the false data.
calculating, with a first microgrid control system of a first microgrid, a first local state estimation using a first plurality of local measurements;
calculating, with a second microgrid control system of a second microgrid, a second local state estimation using a second plurality of local measurements;
calculating, with a central control system, a plurality of global state estimations including a first global state estimation using the first plurality of measurements and the second plurality of measurements, and a second global state estimation using the first local state estimation and the second local state estimation;
performing, with the first microgrid control system, a first false data detection test using the first local state estimation and one global state estimation of the plurality of global state estimations;
performing, with the central control system, a second false data detection test using the first global state estimation and the second global state estimation;
detecting false data in response to performing the first false data detection test or the second false data detection test; and
updating the first global state estimation, the second global state estimation, or the first local state estimation in response to detecting the false data.
The method of claim 1 wherein the first microgrid includes a first plurality of field devices structured to generate the first plurality of local measurements corresponding to physical or electrical characteristics of the first microgrid, and wherein the second microgrid includes a second plurality of field devices structured to generate the second plurality of local measurements corresponding to physical or electrical characteristics of the second microgrid.
The method of claim 1 wherein false data is detected in response to performing the first false data detection test, and wherein updating in response to detecting the false data includes determining, with the first microgrid control system, the first local state estimation includes false data, recalculating, with the first microgrid control system, the local state estimation without the false data, and transmitting the recalculated local state estimation to the central control system.
The method of claim 1 wherein false data is detected in response to performing the second false data detection test, and wherein updating in response to detecting the false data includes determining, with the central control system, the first local state estimation includes false data, recalculating, with the central control system, the plurality of global states estimations without the false data, and transmitting one recalculated global state estimation to the central control system.
The method of claim 1 comprising: generating, with the first microgrid control system, a first microgrid topology using the first plurality of measurements; generating, with the central microgrid control system, a system topology using the first plurality of measurements and the second plurality of measurements; detecting, with the first microgrid control system, a topology error in response to comparing the system topology error and the first microgrid topology; and updating the first microgrid topology in response to detecting the topology error.
generating, with the first microgrid control system, a first microgrid topology using the first plurality of measurements;
generating, with the central microgrid control system, a system topology using the first plurality of measurements and the second plurality of measurements;
detecting, with the first microgrid control system, a topology error in response to comparing the system topology error and the first microgrid topology; and
updating the first microgrid topology in response to detecting the topology error.
The method of claim 1 comprising: receiving a switch command with the first microgrid control system; and generating, with the first microgrid control system, a simulated microgrid topology, wherein calculating the local state estimation includes using the simulated microgrid topology, and wherein detecting false data includes determining the received switch command would cause a voltage collapse or a voltage limit violation.
receiving a switch command with the first microgrid control system; and
generating, with the first microgrid control system, a simulated microgrid topology,
wherein calculating the local state estimation includes using the simulated microgrid topology, and
wherein detecting false data includes determining the received switch command would cause a voltage collapse or a voltage limit violation.
The method of claim 1 comprising: determining a source of the false data; and preventing false data from being introduced into future state estimations.
determining a source of the false data; and
preventing false data from being introduced into future state estimations.
The method of claim 7 wherein preventing false data from being introduced into future state estimations includes transmitting an alarm to a system operation or blocking data received from the determined source of the false data.
The method of claim 7 wherein the false data includes data injected by a cyber intruder and the determined source of the false data is a field device, the first microgrid control system, or the central control system.
The method of claim 7 wherein a first plurality of field devices and the first microgrid control system are structured to communicate by way of a software defined networking (SDN) controller and wherein preventing false data from being introduced into future state estimations includes transmitting a command to the SDN controller effective to disable communication by the determined source of the false data.
The method of claim 10 wherein the first microgrid includes a circuit breaker, and wherein preventing false data from being introduced into future state estimations includes toggling the circuit breaker with the SDN controller before disabling communication by the determined source of false data.
The method of claim 1 wherein the first plurality of measurements includes a voltage magnitude and phase angle for a first plurality of buses of the first microgrid and the second plurality of measurements includes a voltage magnitude and phase angle for a second plurality of buses of the second microgrid.
A method for mitigating a false switching command in a nested microgrid system including a first microgrid, the method comprising: receiving, with a first microgrid control system of the first microgrid, a switching command effective to toggle a controllable switch of the first microgrid; generating, with the first microgrid control system, a simulated microgrid topology using a first plurality of measurements; generating, with a central control system, a simulated system topology using a first plurality of measurements and a second plurality of measurements from a second microgrid; calculating, with a first microgrid control system of a first microgrid, a first local state estimation using the simulated microgrid topology; calculating, with the central control system, a plurality of global state estimations including a first global state estimation using simulated system topology, and a second global state estimation using the first local state estimation; performing, with the first microgrid control system, a first false data detection test by comparing the first local state estimation and one global state estimation of the plurality of global state estimations; performing, with the second microgrid control system, a second false data detection test by comparing the first global state estimation and the second global state estimation; determining the switching command includes false data in response to performing the first false data detection test or the second false data detection test; and ignoring, with the first microgrid control system, the received switch command.
receiving, with a first microgrid 
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