Research And Application On Heating Data Analysis System In The Internet Of Things

As the economics,science and technology saw a high-speed development,the central heating experienced the stages of starting up,developing,challenge and evolution.Central heating is the dominant way of heating in the north of China during this period.However,the traditional way of central heating is rather rough and brings a lot of waste of energy.It not only leads to excessive energy consumption,but also pollutes the environment to some extent.Meanwhile,with the processing of developing and population,traditional heating industry comes to the new age of development combining the techniques of the Internet of Things and Big Data.Heating companies begin to collect heating data,analysis data and provide guidance for heating operation with data mining technology.Data analysis and mining on heating system will make sure that it gains high performance of heating and makes fully use of fossil energy.Moreover,it provides a new way of heating pipeline network monitoring and analysis to supervise the operation of heating network,which will let the heating processing work efficiently.As a result,such smart heating technology will archive the goal of efficient energy usage and reduce the environmental pollution.More importantly,it will improve the heating quality for users and provide them with the fundamental conditions of living and working.This paper focuses on the researches of heating data analysis.Specific topics include the problem of heating prediction,hydraulic calculation of heating pipeline network and finally the design and implementation of heating data analysis system.First,in order to archive high-accuracy and efficient heating process,heating prediction need to be put forward.However,it is difficult to some extent because the district heating system is nonlinear,with large-scaled delay and other characteristics.Taking the heating time delay into account,a model of heating prediction is proposed according to the laws of physics in the heating system.This model is based on least squared error principle and pruning algorithm,and could be used for short-term heating prediction.Specifically,it uses logarithmic transformation to solve the non-linear problem in heating system.According to the physics transmission rule of heating system,the delay model conforms the heating conduction theory.In order to solve the coefficient of delay,it applies pruning algorithm to reduce the computational cost.Secondly,according to the theory of the traditional hydraulic calculation,a novel form of reverse hydraulic calculation is put forward.When operating the heat supply network,some key parameters cannot be measured directly because of network loss and modification of network.This method optimizes the heating parameters inversely by using stochastic optimization method.And then,it modifies the flux and pressure drop of heating pipeline.At last,this paper proposes the design and implementation of heating data analysis system.The front end application of this system provides the input interface of heating pipeline and elementary data and application interface to upload the data constantly.It can also do system simulation and online computing.Its analysis and decision support features could guide the operation of heating.