Abstract
Industrial boilers are important energy supply equipment in modern socialized mass production and one of the main sources of air pollution. Which makes monitoring and managing energy efficiency emissions of boilers an inevitable requirement for environmental management. Most small and medium capacity industrial boilers are not fully equipped with online monitoring/testing functions for thermal efficiency parameters and emission parameters. Moreover, due to the instability of boiler operation system, operation and maintenance management and personnel operation specifications during boiler operation process also would affect the energy efficiency and emission optimization level of industrial boilers greatly. In view of the above characteristics, a multidimensional evaluation model of energy-efficiency emission of industrial boilers is proposed in this paper. Firstly, the multi-dimensionality evaluation metrics including boiler operation status detection factors, transformation technology application factors, personnel operation and process management factors is established, and then back propagation neural network, hierarchical analysis method AHP((Analytic Hierarchy Process) and fuzzy multi-attribute TOPSIS(Technique for Order Preference by Similarity to an Ideal Solution) method are used to judge index weights and evaluate score according to the actual condition, and finally the quantitative comprehensive evaluation value of energy-efficient emissions of industrial boilers is obtained. The established model was also verified by example.
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