Research On Energy Consumption Model And Energy Saving Management Of An Office Building In Xi’an

In the total energy consumption structure of our society,the proportion of building energy consumption is above 30%,and as China’s urbanization process continues to accelerate,this share is increasing at a rate of 1 percentage point per year.In the architectural category,the proportion of large-scale office buildings are the largest among the public buildings,and they are typical large-scale energy users.Also,they are the key point in building energy saving work.Therefore,it is of great practical significance to study the energy consumption model and energy saving management of office buildings for promoting building energy conservation and building a conservation-oriented society.In order to provide scientific guidance in energy consumption scheduling and energy saving work for office building,the prediction model is studied.Based on a large number of domestic and foreign office building energy consumption analysis literature,this article studies the architectural features and energy consumption characteristics of office buildings,and proposes a grey model combined with adjustment parameters and a weighted least squares support vector machine regression.Office building electrical energy prediction model.Using grey models requires less raw data,simple modeling,and low computational workload,selects different samples to perform multi-type predictions for the same time period,and then uses a weighted least squares support vector machine model to have good nonlinear fit.The features of strong sample and generalization ability combine the prediction results;when solving the algorithm,the optimized particle swarm algorithm is used to optimize the parameters used in the weighted least squares support vector machine algorithm.Considering the characteristics of office buildings,this paper separates the working days from the holidays to model and predict,which improves the prediction accuracy.Compared with the classical RBF neural network method and the least squares support vector machine method that need to provide environmental information,the simulation results verify that the model is feasible in office building energy prediction,and the short-term prediction has higher accuracy.In view of the increasingly large data features of office building energy consumption data,in order to achieve automatic transmission,storage and access of energy consumption data,the SQL Server 2008 was used to design the office building energy consumption database to realize energy data storage and management.In order to realize the automatic and visual management of office building energy consumption,an energy management system for office buildings was designed by using the Visual Studio 2015 software development environment.The energy consumption database data visualization query and energy consumption forecasting functions were realized,which can be used as a guidance in engineering application and practical building energy saving work.