Research And Development On The Central Air-Conditioning's Control System Of Ice Storage And Ground Source Heat Pump

With the rapid development of China's economy,energy consumption continues to increase.Resulting in energy supply more nervous,ice storage and ground source heat pump air conditioning technology arises at the historic moment.Ice storage technology can balance the pressure of summer power supply to achieve peak shaving.Ground source heat pump technology can use geothermal resources for winter heating and summer refrigeration,but the peak shaving role is limited.Therefore,the combination of these two techniques can balance with the level of electricity peak and the low cost of geothermal resources and make up the ice cold storage technology in the heating problems.How to combine the two and get the biggest benefit,is also the question which this article needs to study.Ice storage and ground source heat pump central air conditioning control system and based on the system load forecasting is the main content of this paper.Needle the problem,I do many attempts and explorations.According to the control process requirements of ice storage and ground source heat pump central air conditioning system,this paper chooses Advantech industrial computer as upper computer,SIEMENS S7-400 series PLC as lower computer.Using the double CPU redundancy makes the system more stable and reliable.By analyzing the working process of the system,the overall scheme of the automatic control system is determined.Then complete the hardware equipment selection and use software STEP7 programming to control the field equipments.Finally use KingView to design man-machine interface,interface display,real-time monitoring,security management,control parameters setting and adjusting,historical data query,data management,and other functions.Load forecasting is to reduce the waste of resources.The load of air conditioning system in this subject is influenced by the outdoor weather factors.So we have forecasted the solar radiation intensity,outdoor temperature and relative humidity.Several common methods of load forecasting are analyzed.Then decided to use artificial neural network forecasting method which is high accuracy and more suitable for nonlinear system.The BP neural network model was established by using MATLAB software,and the collected data samples were trained and simulated.Predictive error is controlled within the allowable range,in order to achieve good prediction results.