Abstract
The high integration of cyber and physics is the development trend of intelligent distribution network in the future, but the cyber system not only supports the stable operation of the physical system, also brings some security risks to the cyber physical system of distribution network. Aiming at the requirements of real-time, accuracy, efficiency and other characteristics of distribution network monitoring, this paper proposes an early warning method of distribution network cyber physical system based on Hidden Markov model. Firstly, the online monitoring and early warning system architecture of distribution network information physical system is proposed, and then the early warning method of distribution network cyber physical system based on Hidden Markov model is established. Finally, an example is given to verify that the proposed strategy can accurately and efficiently early warn the fault.
Highlights
At present, power equipment monitoring is still in the stage of manual inspection [1]
Power equipment monitoring is still in the stage of manual inspection [1]. This method has the following problems: the internal situation of power equipment can not be monitored in real time, a lot of manpower and material resources are consumed in the inspection process, and safety accidents are prone to occur
Aiming at the problems existing in the operation and supervision of power equipment which are lack of the above research, this paper innovatively uses the cyber physical system (CPS) and hidden Markov model to build the online monitoring and early warning system of
Summary
Power equipment monitoring is still in the stage of manual inspection [1]. In reference [2] uses the Internet of things technology to monitor the power equipment, and establishes the electrical equipment monitoring system based on the Internet of things. This technology solves the problem of electrical equipment monitoring, but the system itself does not process the data, the degree of intelligence is not high, and can not carry out real-time warning. Aiming at the problems existing in the operation and supervision of power equipment which are lack of the above research, this paper innovatively uses the cyber physical system (CPS) and hidden Markov model to build the online monitoring and early warning system of. According to the data flow process, the system is divided into global data collection, intelligent data processing and evaluation, and human-computer interaction
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