Research On The Application Of Complex Event Processing Technology In Smart Grid

In recent years, with the rapid development of social economy, technology, so the size of the grid system has been increasingly great. And, at the same time, the frequency and accuracy of monitoring such power, temperature and other indicators are also increasing, which leads to increasingly large amounts of monitored data in power grid. This also increases the demand for smart grid data processing. And, because the power system is becoming a professional sensor networking with the characteristics of the power industry, it needs to aggregate and integrate massive perceptual information generated by a large number of sensors in real-time. Also, it distributed different levels of processed information to different application participants, thus triggering related e business systems to collaborate appropriately and timely. The emerging complex event processing technology caters to this demand perfectly, its main feature is able to execute event modeling, event capture, correlation analysis and pattern matching of events on the rapidly multiple data stream and find interesting event from a large number of events thus providing rapid response.Therefore, this article is based big data analytics and business interaction issues on smart grid demand side, making a research about methods of information system design and data flow analysis techniques on basis of complex event processing. Specifically, the following research is carried out like:Firstly, because current complex event processing engine is lacking of the perfect solution to process the historical data, the paper proposes a solution that is extending "real time" window in complex event processing engines by adding a historical data buffer, called "history" window and filtering the recent historical events by the complex event processing engines to update the buffer. Secondly, the paper puts forward a kind of complex event processing method based on the publish/subscribe mechanism for flexible real-time monitoring of distributed system behavior, and expounds related design architecture and the important details in the realization process. Thirdly, the simulation experiment of monitoring the multi-user performance of demand response in smart grid has been programed and executed. And, at the end, the result proved fine.