Investigation On Operation And Control Methods For Resilience Improvement Of Cyber-physical Power System

With the rapid development of economic and society,the demand of energy is higher and higher.However,as the global environmental problems become much more serious,the structure of energy consumption has to change from traditional fossil energy to renewable energy,so as to achieve the goal of ”Emission peak,Carbon neutrality”.In order to adapt to the uncertainty of renewable resources,to improve the efficiency of energy utilization,and to strengthen the perception and control ability of power system,the traditional power system has gradually transformed into a New Type Power System with high informatization,digitization and intelligence,which makes the future power system a large-scale,nonlinear,cyber-physical system.On the other hand,as extreme events occur frequently in recent years,research on resilience of power system is more and more significant.From the perspective of Cyber-Physical Power System,this thesis studies the operation and control methods for resilience improvements,which are detailed as follows:(1)In this thesis,two sets of co-simulation platforms for Cyber-Physical Power System are built.In order to improve the accuracy of simulation,both cyber system and power system are modelled and simulated in professional network simulation software and power system simulation software respectively.For the non-real-time co-simulation platform,OPNET and MATLAB/Simulink are used in a single computer environment and corresponding time synchronization strategy is proposed based on the master-slave mode;For the real-time co-simulation platform,RT-LAB,OPAL-RT,OPNET and MATLAB/Simulink are used in a multi-devices environment.Besides,the interface between devices are extended.Finally,these two proposed co-simulation platforms are tested and verified with examples.(2)This thesis proposes an adaptive economic operation strategy of island microgrid based on information exchange.First,the voltage and frequency stability of microgrid is realized by centralized and distributed exchanging modes of distributed generations(DGs).Second,for the distributed mode with no microgrid center controller(MGCC),an adaptive state switching method is proposed to run the system at the economic optimal operation point.The methods mentioned above are verified with our co-simulation platform.(3)This thesis proposes an resilient strategy for island cyber-physical microgrid to resist certain kind of extreme cyber attack,false data injection attack(FDIA).With the proposed resilient method,DGs adaptively adjust the amount of data that needed to be removed,and this method reduces the mis-removal rate effectively.Compared with the traditional extreme data remove method,the convergence condition of the proposed method is much more relaxed.Besides,based on the graph theory,the proof of convergence is given and the required cyber topology is pointed out.Lastly,the proposed method is verified with our co-simulation platform.(4)This thesis proposes a resilient assessment and improvement strategy for cyber-physical transmission network under certain kind of extreme natural disaster,ice storm.According to the meteorological forecast of ice storm,the resilient assessment of power transmission network can be conducted and the corresponding resilient improvements are proposed.Firstly,the structure of cyber-physical transmission network based on optical fiber composite overhead ground wire(OPGW)is analyzed.Then,the cyber-physical spatiotemporal fault model and response model are established.Finally,the corresponding maintenance model is proposed for the damaged components.Simulation results show that the traditional resilient assessment is too ideal due to the lack of considering cyber faults,and the cyber-physical transmission network resilient assessment proposed can be more accurate.In addition,based on such cyber-physical model,this thesis puts forward the corresponding resilient improvements,which improve the resilience of the system during ice storm more accurately.