A Method for Identifying Abnormal Energy Consumption in Multi-Energy System

The multi-energy system (MES), or integrated energy system (IES), is able to manage planning and dispatching for various types of energy such as electricity, gas, heat, and cooling in a unified way. In order to improve energy efficiency and reduce energy waste, it is necessary to conduct energy efficiency analysis and diagnosis on the integrated energy system. However, the data acquisition meters, the transmission protocols, and the data formats and units are quite different among the various types of integrated energy, leading to difficulties in the unified processing of energy flow data. Therefore, this article proposes an identification model for probing the energy utilization abnormality in integrated energy system. This model provides a method to comprehensively analyze, monitor and manage multi-energy data, revealing behaviors such as sudden changes in energy consumption and energy waste. With this identification model, the abnormal energy utilization data are screened and processed with big data mining analysis. Through technical managements, abnormalities in data collection devices, data calculation, and customer-side energy utilization are recognized, achieving accurate measurement of energy consumption process, and efficient energy conservation for users.