Big data used in energy efficiency and load forecasting of heating boilers

Boilers are large energy conversion equipment in the Heating industry, it has the characteristics of extensive management, higher energy consumption and so on. There is the lack of effective “handle” and difficult to carry out targeted operational guidance in the actual operation management. This paper proposed methods of operation optimization and load forecasting based on big data thinking. The performance management system of boiler is big data platform, using clustering theory by big data to analysis data for the boilers, to find main factors affecting efficiency of boilers, and operational guidance and optimization. Meanwhile, the theory of information mining is used to forecasting load of boilers. Obtain remarkable benefit of energy saving 9%, and to achieve the boiler load guidance, the error of 1%.