ENERGY CONSUMPTION MONITORING OF SMART GRID BASED ON SEMANTIC STREAM DATA ANALYSIS
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For citation: Kolchin M.A., Fensel A., Mouromtsev D.I., Popov S.O., Pavlov D.S., Klimov N.V., Andreev A.A., Garayzuev D.S. Energy consumption monitoring of Smart grid based on semantic stream data analysis. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol.15, no. 2, pp. 285–292.
Problem statement. Currently, the task of improving energy efficiency are addressed mainly through the creation of more efficient devices and appliances, the use of alternative energy sources, application of special additional equipment for power consumption control and other technological methods. All these solutions are quite expensive and often economically difficult to payback. At the same time, the issues of automated integrated analysis of existing data measuring equipment have been poorly known. But just these data contain all the necessary information for finding bottlenecks and failures in the equipment, leading to increased energy consumption.
Methods. Methods of web services creation are considered for current state monitoring of electrical networks using CQELS for static and streaming data integration of smart meters. RDF data model is used as the main way of data representation.
Results. The architecture of the energy monitoring system (Smart grid) based on semantic analysis of the streaming data is proposed. Ontology has been worked out, aimed at information domain model creation, which describes the measurement data and the possible situations for tracking by the system using semantic queries. An example of system operation is shown, and description of the visualization interfaces for streaming data and log of messages is given.
Practical relevance. Industrial application of the proposed approach will give the possibility to achieve significant energy efficiency through integrated analysis of smart meters data based on existing infrastructure of test and measurement equipment. An additional effect lies in the ability to create flexible Smart grid monitoring system and visualization of their states by an ontological approach to the domain modeling.
Acknowledgements. This work was partially financially supported by the Government of the Russian Federation (Grant 074-U01).