Research On Energy Saving Control System Of Air Compressors

Compressed air as a clean and safe pneumatic energy,it is widely used in industrial sites.Air compressor is a machine used for the production of compressed air,the electrical energy consumption accounts for more than 90%of the entire compressed air system.Therefore,the energy-saving research of the air compressor has great significance.Due to the compressed air consumption is constantly changing,it will lead to the problems of frequent start or stop and energy waste if we always fixed unit operation combination.Therefore,it is necessary to dynamically match the optimal operation of air compressor according to the real-time changes of gas consumption.This paper focuses on the energy-saving control of air compressor units with the largest proportion of energy consumption in compressed air systems.On the one hand,the precise prediction of the gas consumption used during each period is made.On the other hand,the optimal operation combination and the optimum gas production of each air compressor unit are calculated.Finally,through the design of automatic control system software to achieve remote automatic optimal start and stop of the air compressor units,thus minimizing the system energy consumption.The load forecasting model of the least squares support vector machine was established to predict the compressed air system gas consumption of each period in the next day,which achieved good prediction accuracy and convergence speed.In order to improve the stability and reliability of the prediction,aiming at the shortcomings of artificial selection parameters of least square support vector machine model,the particle swarm optimization algorithm is adopted to optimize the parameters automatically.The simulation results show that the least square support vector machine model based on Particle Swarm Optimization algorithm improves the overall prediction accuracy and avoids the uncertainty caused by the manual selection of parameters.This method has strong theoretical basis and practical value.Based on the result of short-term load forecasting,the optimization model of air compressor unit is established with the objective of minimizing the energy consumption of compressed air system.The optimum number,operation combination and gas production of air compressor units are calculated dynamically in each scheduling period,one day in advance to develop optimal scheduling.In this paper,Lagrange relaxation theory,dynamic programming and adaptive subgradient algorithm are used to solve the optimal scheduling problem of air compressor units.The twenty four hours of ten units are simulated and verified,The simulation results show that the proposed algorithm can effectively solve the scheduling problem of compressed air system.A compressed air energy-saving control system is designed and implemented as the background of the compressed air system optimization and improvement project in a factory of Dongfeng Nissan.The system consists of two parts,the end decompression control system and the optimal scheduling system of the air compressor unit.The two systems work together to achieve the energy-saving control of the compressed air system.The end decompression control system through the PID control strategy to reduce the gas pressure in each workshop,while significantly reduce the pressure fluctuation range.The optimal scheduling system of air compressor combines the real-time control strategy such as priority,time average and pressure balance with the optimal schedule obtained from the scheduling model to control the optimal start and stop of the air compressor automatically and balance supply and demand.