Research On Energy-consumption Model And Management Information System For Large-scale Public Buildings

Nowadays, the energy issues have received extensive attention.Especially,with therapid development of economic society and the popularization of new-type urbanizationin China, the incremental areas of architecture has reached more than two billion squaremeters yearly. At present, the total area of large-scale public buildings is about600million square meters. The gross area of large-scale public buildings is less than4percent of the whole area of all the buildings in cities and towns. However, the annualenergy consumption is more than22percent of the whole buildings’ and it occupiesabout30percent of national total energy consumption.Therefore, in order to takeeffective measures to suppress high energy consumption of the large public buildings,itis necessary to obtain accurate and particular energy data which is the basis of energyanalysis, statistics and diagnosis. The energy consumption monitoring and managementsystem solve the problems.This dissertation is just based on these problems above.Firstly, the factors whichinfluence building energy consumption are analyzed,the factors that affect the energyconsumption of the outdoor meteorological and work status are considered, and thescheme about large public energy consumption and outdoor meteorological factorsindex parameter acquisition based on wireless sensor network are proposed. Secondly, itcombines the large-scale public building’s characteristic itself, so as to determine thekey energy-using superstore large-scale public building, the significant factors thateffect the power consumption which include outdoor meteorological factors(temperature, humidity, wind speed, sunshine, weather conditions), holidays and so on.In addition,using various sensors (power, temperature and humidity, wind speed,sunshine) collect related parameters based on wireless sensor network technology, andaccording to the features of the energy consumption influencing factors to create amodified particle swarm optimization T-S fuzzy-neural network algorithm model. And it combined with examples to test the model for the energy trends，the results show thatthis model is accurate and effective in energy trends for the Large-scale publicbuilding.Finally, using SQL Server2008database software to build large-scale publicbuilding’s energy consumption databases, and designing energy consumptionmanagement information system base on B/S by Java,which can improve the operabilityand validity of energy management.The research of this dissertation provides a scientific and informationalizedplatform formonitoring and supervising the energy consumption of the large-scalepublic buildings in China. To lay the basis for the energy statistic,audits andenergy-saving supervision in large-scale public building.It is scientific guidingsignificance in achieving energy efficiency and quota.