Parametric Energy Efficiency Impact Analysis for Industrial Process Heating Furnaces Using the Manufacturing Energy Assessment Software for Utility Reduction

• Published in: Processes Vol. 12; no. 4; p. 737
• Main Authors: Bisht, Prakash Singh, Gopalakrishnan, Bhaskaran, Dahal, Rupesh, Li, Hailin, Liu, Zhichao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2024
• Subjects: Air temperature; Atmospheric models; Coalitions; Combustion; Comparative analysis; Cost control; Electric arc furnaces; Electric resistance furnaces; Electricity; Energy audits; Energy consumption; Energy efficiency; Energy management systems; Energy minerals; Energy modeling; Energy use; Environmental impact; Firing (igniting); Flue gas; Fossil fuels; Fractional factorial design; Furnaces; Heat; Heat balance; Heat treating furnaces; Heat treatment; Heat treatments; Heating; Heating furnaces; Heating systems; Impact analysis; Insulation; Kilns; Manufacturing; Parameters; Production processes; Software; Software utilities; Steel making; Stoichiometry; Surface temperature; Temperature; Thermal energy; Thermal storage; United States > US
• ISSN: 2227-9717; 2227-9717
• DOI: 10.3390/pr12040737

Industrial process heating furnace operations consume considerable energy in the U.S. manufacturing sector, making it crucial to identify energy efficient strategies due to the growing need to minimize energy usage and emissions. It is important to identify the potential impact of these factors to enable process engineers to operate process heating systems at the maximum possible efficiency. This study examines and identifies the key impact factors that influence the efficiency of process heating systems using MEASUR (v1.4.0), the DOE software tools such as the insulation effectiveness, the burner stoichiometry, cooling medium, thermal storage, and atmospheric gases. Data from a two-fuel-fired heat treatment furnace and an electric arc furnace (EAF) for steelmaking were employed to establish the baseline heat balance models in MEASUR. The fractional factorial design experiment was developed with two-level parameter values and energy efficiency strategies for the heat input into industrial furnaces. The three most significant parameters for the heat input for a fuel-fired industrial furnace, Industrial Furnace A, are excess air percentage or the oxygen percentage in flue gas (OF), average surface temperature (ST), and combustion air temperature (CT). Similarly, for an electric industrial furnace, Industrial Furnace B, the parameters are charge temperature (CHT), average surface temperature (ST), and time open (TO). A comparative analysis was carried out for the fuel-fired and equivalent electric resistance furnaces to identify the prospect of electrification of industrial furnaces relying upon fossil fuels. The study aims to assist industries and designers in making informed decisions regarding industrial furnace upgrades, process optimization, and maintenance investments, resulting in substantial energy and cost savings, and a reduced environmental impact.