US 12,147,259 B2
Distributed collaborative control method for microgrid frequency under attack of false data injection based on cyber-physical fusion
Donglian Qi, Hangzhou (CN); Jingcheng Mei, Hangzhou (CN); Jianliang Zhang, Hangzhou (CN); Yulin Chen, Hangzhou (CN); and Zhenyu Wang, Hangzhou (CN)
Assigned to ZHEJIANG UNIVERSITY, Hangzhou (CN)
Filed by ZHEJIANG UNIVERSITY, Hangzhou (CN)
Filed on May 25, 2021, as Appl. No. 17/329,204.
Claims priority of application No. 202110434398.X (CN), filed on Apr. 22, 2021.
Prior Publication US 2022/0342435 A1, Oct. 27, 2022
Int. Cl. G06F 30/20 (2020.01); G05B 17/02 (2006.01); G05F 1/66 (2006.01); H02J 3/38 (2006.01); H04L 41/14 (2022.01); G06F 113/04 (2020.01)
CPC G05F 1/66 (2013.01) [G05B 17/02 (2013.01); G06F 30/20 (2020.01); H02J 3/38 (2013.01); H04L 41/145 (2013.01); G06F 2113/04 (2020.01); H02J 2203/20 (2020.01)] 4 Claims
OG exemplary drawing
 
1. A simulation method of distributed collaborative control for a microgrid frequency under attack of false data injection based on cyber-physical fusion, wherein the simulation method is applied to a scenario of adjusting AC bus frequency of a microgrid composed of distributed generations and AC loads, and comprises following steps:
S1, establishing a distributed collaborative control simulation model for a microgrid frequency based on a real-time simulation tool OPAL-RT of a real-time simulation platform;
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;
S4, simulating constant injection of false data such that the microgrid frequency is strictly tracked to a reference frequency ultimately;
S5, deploying the distributed collaborative control simulation model and the distributed collaborative control algorithm to a target microgrid under attack of false data injection, and adjusting parameters corresponding to the distributed collaborative control simulation model and the distributed collaborative control algorithm according to operating parameters of the target microgrid, wherein the target microgrid comprises four distributed generations and an AC load; and
S6, adjusting active power and voltage of the target microgrid through the distributed collaborative control simulation model and the distributed collaborative control algorithm, in such a manner to adjust AC bus frequency of the four distributed generations of the target microgrid to 50 Hz;
wherein the step S1 specifically comprises:
establishing a simulation model of a distributed generation cluster in the real-time simulation platform, 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;
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;

OG Complex Work Unit Math
wherein ωi and Umag,i are an angular frequency and a voltage of an output of an inverter i respectively, Pi and Qi are an active power and a reactive power of the output of the inverter i respectively; mp,i and nq,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; ωn,i and Un,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:

OG Complex Work Unit Math
wherein ωi is an angular frequency of the ith distributed generation; ωref 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 ωn,i in Formula (2); differentiating the Formula (1) as:
ωl=ωn,l−mp,iPl=ui  (3)
wherein ωl, ωn,l and Pl are differentials of ωi, ωn,i and Pi; ui is a control rate of the distributed collaborative control algorithm against the attack of false data injection;
ui=−kω∫[Σj∈Niai,j(ωi−ωj)+bi(ωi−ωref)]dt−ωi  (4)
wherein kω, ai,j, bi are all control coefficients, ωi is an angular frequency of the ith distributed generation, ωj is an angular frequency of the jth distributed generation, and Ni 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.