Use of Gray Relational Analysis to Manage and Optimize Full-Scale Industrial Furnace Operation

Abstract

In the context of waste gas energy recovery and management, the gray relational analysis method is applied to construct the optimum parameters and management of the operation conditions for a heating furnace used in the petrochemical industry. Comparing the results of tail gas recycling, the operational parameters are adjusted and the residual oxygen concentration in flue gases, preheated air temperature, and fuel oil temperature are studied for saving energy. The results show that the efficiency of the heating furnace is improved and the fuel consumption and carbon dioxide emissions are reduced. In addition, gray relational analysis is used to predict the parameters to optimize the operation and best energy saving demand. The results show that the optimal operating conditions are between 3.1% and 2.9% by volume, between 226°C and 232°C, and between 127°C and 129°C for residual oxygen concentration in flue gases, preheated air temperature, and fuel oil temperature, respectively. These values agree with the conditions actually used on-site for the optimum operation of heating furnaces. Therefore, gray relational analysis is the best way to evaluate and manage the operation parameters of a reheating furnace.