Design And Engineering Application Of Optimal Control Of Energy Consumption In Industrial Refrigeration System

In order to ensure normal production,the preparation and supply of chilled water in factories are often extensive,resulting in a waste of energy.The prior art adjusts the temperature and pressure of the water supply based on manual experience,and the operation is complicated.Therefore,through the research of the factory refrigeration system,the system’s operating parameters and equipment scheduling are optimized,and then the energy-saving potential of the system is tapped,which is of great significance for reducing the production cost of the enterprise and improving the energy utilization rate of the system.This article takes the power workshop of a typical refrigeration system as the object.First,according to the actual operation of the power workshop of a pharmaceutical factory,a mathematical model of the main energy-consuming equipment in the system: refrigerator,centrifugal pump,and cooling tower is established,and then the water temperature in the refrigeration system is analyzed.,The impact of water pressure on the energy consumption of the main energy-consuming equipment in the system.According to the equipment model built,the refrigeration system optimization problem was constructed and solved with the goal of minimizing the total energy consumption of the system,and then a set of refrigeration system energy optimization control schemes were designed,which solved the problem of the imbalance of cooling supply and demand in the workshop and improved the system The high cooling efficiency meets the factory’s demand for energy-saving optimization in the workshop.The main research contents of this paper are as follows:(1)Establish mathematical models for the main energy-consuming equipment in the system: refrigerators,centrifugal pumps,and cooling towers.This paper has successively studied the modeling of refrigerators and cooling towers based on support vector regression,and the modeling of centrifugal pumps based on empirical formulas.The models of refrigerators,centrifugal pumps and cooling towers were tested,and the root mean square error of the models was within 5%,which met the actual needs of the site.(2)Aiming at the optimization problem of the main working condition parameters in the refrigeration system,in order to ensure the balance between the cooling capacity of the cooling end and the cooling end,the genetic algorithm is used to solve the optimal operating parameters of the refrigeration system according to the mathematical model built by the equipment,including:cooling water temperature,Flow rate,the temperature of chilled water supply.The overall energy consumption optimization scheme of the cooling water system,chilled water system and refrigeration system is verified through simulation,and it has obvious energy saving effect;selecting the time zone for the stable operation of the system and investing in each optimization control module has obvious energy saving effect,meeting The plant’s demand for energy saving optimization in the workshop.(3)Aiming at the problem of multi-stage parallel group control of energy-consuming equipment in the system,under the condition of ensuring the temperature and pressure of the water supply in the refrigeration system,an exhaustive method is used to solve the optimal equipment start-stop problem through the built model.It mainly includes: group control of centrifugal pumps and group control of refrigeration units.The group control scheme of centrifugal pumps under different operating conditions is verified,and the energy-saving effect is more obvious;the group control of refrigeration units provides guidance for manual operation through simulation.By establishing a mathematical model of the refrigeration system,this paper compares the unoptimized field operation data with the simulation test data and the optimized field operation data from the perspective of system energy consumption.The data shows that the optimized control scheme of the refrigeration system designed in this paper effectively reduces the energy consumption of the refrigeration system compared with the traditional control scheme.