Research On Building Energy Efficiency Analysis Technology And Energy Consumption Prediction Model

With the development of the national economy and social progress,building energy conservation and smart grid construction have attracted more and more attention of experts and scholars from all walks of life.Up to now,the total energy consumption of buildings in our country has accounted for 21% of the total energy consumption of the society,while the energy consumption of public buildings accounts for about 30.4% of the total energy consumption of buildings,which has great potential for energy conservation.At the same time,the analysis of power consumption from the grid side alone can only passively distribute grid power usage,which cannot fully achieve reasonable utilization and distribution of power,but strengthen the load management of the power demand side,can better optimize the regulation scheme of power load.Therefore,it is of great significance to effectively judge the actual power consumption of buildings and reduce the energy consumption of public buildings to effectively promote the development of energy-efficient buildings and smart grids.Based on the background of a large office building in Gansu Province,the thesis analyzes the energy structure and energy consumption characteristics of the office building,makes statistical analysis on the historical energy consumption data of the building,studies the main factors affecting the building energy consumption and the energy-saving potential of the building,and lays a foundation for energy efficiency analysis of the building and the realization of energy consumption prediction.In order to analyze the energy efficiency of the building,the energy consumption of office buildings in cold regions is investigated and counted.Based on the energy consumption data of sample buildings,the energy consumption quota of each power consumption system is determined respectively by means of statistical quota,and the energy consumption of the studied object is compared with it to evaluate the energy consumption of building.The thesis analyzes the situation of high energy consumption in HVAC system,and proposes to use air source heat pump to replace the electric boiler to reduce the energy consumption of electric heating.In order to achieve the prediction of building energy consumption in the future,a public building energy consumption prediction model based on RBF neural network is established,and the model is optimized by using the PSO algorithm and the LMalgorithm to obtain better prediction results.According to the existing historical energy consumption data and the factors affecting energy consumption,taking the two stage data of the building as samples,the MATLAB simulation is used to test the prediction effect of the model.The simulation result shows that the improved model can keep the error within 2.2%,and the average absolute error and relative error are significantly reduced,indicating that the improved prediction model has higher prediction accuracy in the prediction of office building.Through the research on the energy consumption quota methods and prediction models of large office buildings,it is possible to comprehensively grasp the energy usage,formulate reasonable energy saving measures,and judge the change trend of energy consumption,to achieve the energy consumption management and energy reduction of large office buildings.