METHOD FOR CONTROLLING BUILDING AIR CONDITIONING SYSTEM BY USING INTELLIGENT CONTROL ALGORITHM

摘要

PURPOSE: A building air conditioning method using an intelligent control algorithm is provided to control air conditioning equipment by the intelligent control algorithm using a neural network model, thereby maintaining an environment of a building to be pleasant. CONSTITUTION: A building air conditioning method using an intelligent control algorithm is as follows. A back propagation neural network model, which is adopted by being studied with reservation time as an output variable and indoor temperature, an indoor temperature inclination, outdoor temperature, and an outdoor temperature inclination as input variables, is fetched(S101). A measurement variable including the indoor and outdoor temperature is measured at a preset time interval(S102). A calculation variable including the indoor and outdoor temperature inclinations is calculated based on the measurement variable(S104). The input variable is input into the neural network model so that the reservation time of measurement timing is calculated(S106). A difference between the reservation time and target set time is calculated, and air conditioning the building is performed according to operation processes when the difference is within a preset value. [Reference numerals] (AA) Start; (BB,DD) No; (CC,EE) Yes; (FF) End; (S101) Loading an adapted neural network model; (S102) Measuring indoor and outdoor temperatures every minute; (S103) No noise exists in the measured data?; (S104) Storing the indoor and outdoor temperatures, and calculating and storing the gradients of the indoor and outdoor temperatures; (S105) Inputting the stored data in the adapted neural network model; (S106) Calculating a preheating time in each measuring point through a neural network image; (S107) Calculating the difference between the calculated preheating time and a target set time; (S108) Difference between the calculated preheating time and a target set time is within a set value?; (S109) Operating a heating facility; (S110) Starting the operation of a boiler, an air conditioner, and an FCU with full power; (S111) Storing the time, indoor temperature, indoor temperature gradient, outdoor temperature, and outdoor temperature gradient at the time of starting operation; (S112) Storing the time when reaching a set temperature; (S113) Inputting learning data collected through the operation and relearning an adapted backpropagation neural network model; (S114) Storing information about learning of the backpropagation neural network model;