In order to improve the operational energy efficiency of the water treatment process in wastewater plants and accelerate the transformation of smart water plants to energy saving and digitalization,an energy consumption monitoring and evaluation and abnormal diagnosis manage-ment platform for wastewater treatment plants is designed.Based on Building Information Model and Energy Management System,the platform establishes a dynamic supervised energy consump-tion prediction model based on machine learning algorithm by collecting information such as sewage plant operation data and meteorological data and realizes real-time monitoring and evaluation of plant operation conditions.The operation and maintenance managers can adjust the energy struc-ture of the plant and identify and diagnose abnormal energy use based on the state evaluation index generated by the platform.Finally,the feasibility and effectiveness of each functional module of the platform are verified with actual case data.The analysis results show that the platform's early warning module can monitor 96％of abnormal energy use situations.
维普
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