Monitoring and fault diagnosis system of wind–solar hybrid power station based on ZigBee and BP neural network

ABSTRACT

The integration of real-time monitoring datas of wind-solar hybrid power stations was not high, and a design plan for monitoring system based on ZigBee and B/S architecture was proposed. The data  acquisition module was based; a network centre based on B/S architecture was constructed with cloud hosting to process information uploaded and provide services for users through browser or WeChat. At the same time, the BP neural network was used to extract and analyse the fault data and fault type. It was verified by experiments that the system was highly automated with stable and reliable data transmission.

KEYWORDS:

• ZigBee
• cloud hosting
• neural network

Acknowledgements

This work was supported financially by the Quzhou Municipal Science and Technology Project (Grant no. 2013Y018).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Science and technology project of Quzhou science and Technology Bureau.