Short term prediction of itemized building energy consumption based on AR-DBN
摘要
To address the problem that the existing methods of total energy consumption prediction cannot accurately distinguish where the consumption of building energy is consumed and have the low prediction.To this end,according to the use of energy consumption,this paper divides the total energy consumption into four items and proposes a prediction model of itemized building energy consumption.Firstly,based on time sequence Auto-regression(AR) model,the lighting energy consumption of a building is predicted in short term.Secondly,a Deep Belief Network(DBN) model is constructed,which predicts air conditioning energy consumption,power energy consumption and special energy consumption of the building according to the lighting energy consumption prediction results,hourly average outdoor temperature,hourly average outdoor relative humidity,weather feature,holiday,hourly average wind speed,time.Experimental results show that,compared with the total energy consumption prediction models iPSO-BP and BP,the proposed model can predict the itemized energy consumption of a building more accurately and effectively.