2025 AIChE Annual Meeting

(392ab) Optimal Technology Selection and Strategic Planning for Industrial Decarbonization

Authors

M. M. Faruque Hasan - Presenter, National University of Singapore
Industrial sources of carbon dioxide (CO₂) emissions encompass manufacturing, processing industries, refineries, and other energy-intensive sectors. In 2022 direct and indirect emissions from these sources account for 30% of total U.S. emissions [1]. Within this, industrial process heating contributes about 9% of national emissions and nearly half of the energy-related emissions produced by the manufacturing sector [2]. Conventionally, industrial decarbonization involves substituting existing heating systems with alternatives that have lesser emissions, a process that often demands significant capital investment and operational expenses [3,4,5]. This issue can be addressed by devising a framework that leverages existing heating infrastructure while incorporating diverse decarbonization strategies. There have been similar studies in the past which integrate renewables-based processes for fuels and power production networks [6,7]. However, the complexity of industrial heating consisting of a range of temperatures and processes poses significant challenges to model decarbonization strategies. In a manufacturing unit, there are various processes with energy demands which can be satisfied by numerous sources of energy that have some emissions associated with them. These emissions can then be processed by various decarbonization technologies.


In this work, we introduce a mathematical programming based systematic technique which integrates existing heat and power infrastructure with diverse decarbonization pathways to minimize costs while achieving emissions reduction targets. We formulate a mixed-integer nonlinear programming (MINLP) model. The model optimizes energy flows from multiple sources to meet plant demands taking into consideration multi-period operation and the availability of energy sources during that particular period of operation. The model considers a set of energy demands which can be satisfied by a set of energy sources which themselves can be decarbonised by a set of technologies during a particular period of operation. Under these settings, the objective of this model is to minimize the total cost of decarbonization, subject to the availability of sources and meeting the decarbonization goal. The overall superstructure resembles a pooling problem where the flows are replaced by energy flows, considering the decarbonization technologies as pools which make sure that the carbon emissions stay under the target.

This approach models energy flows to fulfil the energy needs of industrial processes, treating emissions from specific streams as the critical quality factor for assessing decarbonization performance. By treating emissions as a quality factor within a pooling problem framework, this approach offers a cost-effective and flexible solution for decarbonizing industrial heating without necessitating equipment replacement in some cases. We apply the MINLP framework to identify the most cost-effective solution to decarbonize an existing 600 TPA propylene manufacturing unit having 10 demands of energy which can be satisfied with various sources of energy such as Natural gas, Coal, Solar, Wind & Hydrogen. These sources of energy can be decarbonized or used in various technologies namely, Carbon Capture, Electrification Technologies, Hydrogen Furnaces which supply energy to the demands. This case study aims to curb 90% of emissions from the manufacturing unit. We find that the total cost of decarbonization is heavily dependent on changes of prices of green hydrogen over the future. Industries dependant on process heating can leverage this model to identify the optimal technology considerations and analyse the cost implications for decarbonization.

Keywords: Fuel Switching, Industrial Decarbonization, Mixed Integer Nonlinear problems, Energy Management.

References:

[1] U.S. Department of Energy, “Industrial heat shot.” https://www.energy.gov/topics/industrial-heat-shot ,2025.

[2] U.S. Environmental Protection Agency, “Industry Sector Emissions” https://www.epa.gov/ghgemissions/industry-sector-emissions, 2022.

[3] S. Madeddu, F. Ueckerdt, M. Pehl, J. Peterseim, M. Lord, K. A. Kumar, C. Kruger, and G. Luderer, “The CO2 reduction potential for the European industry via direct electrification of heat supply (power-to-heat),” Environmental Research Letters, vol. 15, no. 124004, 2020.

[4] M. Bui, et al. “Carbon capture and storage (CCS): the way forward,” Energy & Environmental Science, vol 11, pp 1062-1176, 2018

[5] M. Fasihi, O. Efimova, and C. Breyer, “Techno-economic assessment of CO2 direct air capture plants,” Journal of Cleaner Production, vol. 224, pp. 957–980, 2019.

[6] Qi Zhang, Mariano Martín, Ignacio E. Grossmann, “Integrated design and operation of renewables-based fuels and power production networks” Computers and Chemical Engineering, vol 122, pp 80-92, 2019.

[7] Mariano Martína, Ignacio E. Grossmann, “Optimal integration of renewable based processes for fuels and power production: Spain case study” Applied Energy, vol 213, pp 595-610, 2018.