A forecasting method of air conditioning energy consumption based on extreme learning machine algorithm
This paper deals with the issue on air conditioning energy consumption and system monitoring of different data in building. Various environmental parameters inside the building are changed in real time, while the conventional air conditioning energy consumption forecasting with the load simulation software cannot adapt to these variations. Therefore, the air conditioning energy consumption forecasting model is established based on extreme learning machine (ELM) algorithm, within the interior environmental parameters of the building. These parameters are obtained through the building monitoring system which takes into account the environmental parameters, number of people, region area and energy consumption. The performance and effectiveness of the proposed forecasting model of air conditioning energy consumption are demonstrated through a case study of a building from practical engineering.