Load Forecasting And Research Of Demand Response Energy-saving Operation On Air Conditioning Refrigeration Station For Large-scale Public Buildings

In recent years, our country is in the rapid development phase of industrialization and urbanization. Along with the total building increasing and living comfort improvement, large-scale public building will increase sharply in the next few years, and more than90%of large-scale public buildings are typical major energy consumption in our country. With the proportion of building energy consumption increasing, the conflict between energy and development will be increasingly prominent. The application of demand response technology in large-scale public building system has important significance to ease the contradiction between energy and development.The research bases on air conditioning refrigeration station system about large-scale public buildings in Beijing in this paper. Firstly, it classifies the building from the perspective of building energy consumption characteristics, and analyses energy consumption characteristics, categories, the necessity of energy-saving design and comprehensive solutions of large-scale public building.Secondly, by using BP neural network the cooling load of air conditioning system is predicted, the results which are in combination with good energy saving operation strategy, not only can satisfy the requirement of system load, but also is beneficial to the economy and reliability of system operation plan.Again, the paper researches the mathematical model of part of the important components and digital simulator, uses TRNSYS software to structure ice storage system dynamic simulation platform in cold machine separate cooling condition, and completes system simulation and result analysis in the platform.Finally, the paper researches the control model of water chiller, specific power and energy consumption under partial load rate, completes fuzzy expert system simulation of cold machine running in the Matlab environment, and researches large-scale public buildings’ energy efficiency evaluation system from the statistical analysis of energy efficiency and evaluation system of energy efficiency.