Research On Building Energy System Based On Comfor

The total energy consumption of building energy systems is huge and the elasticity of energy use is high,and the potential for energy-saving optimization is strong,so it has received wide attention from scholars at home and abroad.According to the statistics of Tsinghua University Building Energy Efficiency Research Center,the energy consumption of buildings in China accounts for almost 40% of the total energy consumption of society.With the continuous promotion of building a well-off society,the increase of industrialization and the continuous improvement of people’s living standards,the demand for energy in China is on a continuous growth trend,and the energy consumption of buildings is gradually increasing,so it is urgent to reduce energy consumption.Heating Ventilation and Air Conditioning(HVAC)systems account for the largest proportion of energy consumption in buildings,and by controlling HVAC systems effective energy control will be achieved in buildings.The use of renewable energy sources for energy efficiency is an emerging research topic.On the other hand,user comfort is an important indicator for energy saving and consumption reduction,however,comfort and energy saving are often contradictory.Therefore,this paper conducts a study on the comfort index Predicted Mean Vote(PMV)and HVAC system energy saving,and proposes to control the solar heat gain to achieve energy saving and improve PMV in HVAC systems,specifically as follows:(1)Firstly,the building space model and indoor loads(lighting equipment,electrical equipment,air conditioning,etc.)are modelled in Energy Plus software,and energy consumption simulations are carried out for different envelope heat transfer coefficients and HVAC system operation scenarios under ideal load air systems,respectively,to arrive at the optimal envelope heat transfer coefficient and optimal HVAC system operation scenarios,which are used in subsequent experiments.(2)Based on the building energy consumption data obtained in Chapter 2 for modelling,the Whale Optimization Algorithm(WOA)and the Attention mechanism are chosen to optimize the Long Short-Term Memery Network(LSTM)with hyperparameters,and a WOA-Attention-LSTM prediction model.Based on the model prediction control principle,the WOA-Attention-LSTM prediction control model was established,and the results showed that it has good control effect on HVAC energy consumption and PMV.(3)The control strategy of the shading device is designed based on solar radiation and room temperature models,and the strategy is validated using a joint simulation with the Building Control Virtual Test Bed(BCVTB)and Energy Plus software.The strategy was compared with other control strategies for indoor temperature,PMV and energy consumption.The tests showed that the designed control strategy has advantages in energy saving and PMV regulation.