Home / Current Issue / Paper 1723034
Advanced Thermal Performance Optimization of Refinery Heat Transfer Systems for Saudi Vision 2030
Subject area: Science,Engineering and Technology · Area of research: Heat Transfer Systems
Abstract
The manner in which refinery heat-transfer systems function has a direct bearing on how efficiently high-grade process heat can be recovered before additional fuel, steam, or electricity is consumed; since this affects both operating costs and the achievement of industrial decarbonisation, the performance of these systems is of vital importance. This review gathers the research conducted between 2020 and 2025 on the advanced optimisation of the thermal performance of refinery heat exchangers and heat exchanger networks, with a specific emphasis on the relevance of these findings to Saudi Arabia's Vision 2030 transition. The evidence is organised around five interrelated factors: heat-integration retrofit, fouling-aware operation, equipment-level improvements, data-driven condition monitoring, and low-carbon heat upgrading. Recent studies of refineries have demonstrated that even technically sound measures can be undermined if the network's topology, pressure-drop constraints, changes in crude oil properties, the availability of cleaning operations, and interactions with utility systems are taken into account separately. A more dependable approach is to optimise thermal recovery and hydraulic operability over the entire operating cycle rather than merely at a single point that corresponds to a clean design condition. The review therefore offers a decision-making framework tailored to Saudi Arabia, giving priority to high measurement quality, accurate fouling diagnosis, operational changes that require no capital or only low capital, targeted network retrofit, and finally the integration of electrified or renewable heat. The synthesis indicates that the most beneficial action in the short term is to combine pinch-guided retrofit with fouling prediction and dynamic control, while longer-term decarbonisation will need the use of heat pumps, renewable energy, and flexible utility systems. There are still research gaps relating to plant-scale validation, the management of uncertainty, water-aware optimisation, operation at high ambient temperatures, and explainable machine-learning models. These gaps define a practical research programme for reducing refinery energy intensity without having to compromise reliability, throughput, or product quality.
References
[1] Seijo-Bestilleiro E, Arias-Fernández I, Carro-López D, Naveiro M. Opportunities for emission reduction in the transformation of petroleum refining. Fuels. 2025;6:66. MDPI
[2] Talaei A, Oni AO, Ahiduzzaman M, Roychaudhuri PS, Rutherford J, Kumar A. Assessment of the impacts of process-level energy efficiency improvement on greenhouse gas mitigation potential in the petroleum refining sector. Energy. 2020;191:116243. Crossref
[3] Amran YHA, Amran YHM, Alyousef R, Alabduljabbar H. Renewable and sustainable energy production in Saudi Arabia according to Saudi Vision 2030: Current status and future prospects. Journal of Cleaner Production. 2020;247:119602. Crossref
[4] Alshammari YM. Achieving climate targets via the circular carbon economy: The case of Saudi Arabia. C. 2020;6(3):54. MDPI
[5] Alhajri IH, Gadalla MA, Abdelaziz OY, Ashour FH. Retrofit of heat exchanger networks by graphical Pinch Analysis - A case study of a crude oil refinery in Kuwait. Case Studies in Thermal Engineering. 2021;26:101030. Crossref
[6] Lai YQ, Wan Alwi SR, Manan ZA. Graphical customisation of process and utility changes for heat exchanger network retrofit using individual stream temperature versus enthalpy plot. Energy. 2020;203:117766. Crossref
[7] Zhi K, Wang B, Guo L, Chen Y, Li W, Ocłoń P, Wang J, Chen Y, Tao H, Li X, Varbanov PS. Graphical pinch analysis-based method for heat exchanger networks retrofit of a residuum hydrogenation process. Energy. 2024;299:131538. Crossref
[8] Teng SY, Orosz A, How BS, Jansen JJ, Friedler F. Retrofit heat exchanger network optimization via graph-theoretical approach: Pinch-bounded N-best solutions allows positional swapping. Energy. 2023;283:129029. Crossref
[9] Zhao K, Zhao L, Tang QQ, Chen QL, He C, Zhang BJ. A novel optimization framework integrating multiple initialization, automatic topologization and MINLP reduction to accelerate large-scale heat exchanger network synthesis. Energy. 2024;307:132508. Crossref
[10] Langner C, Svensson E, Harvey S. A computational tool for guiding retrofit projects of industrial heat recovery systems subject to variation in operating conditions. Applied Thermal Engineering. 2021;182:115648. Crossref
[11] Stampfli JA, Ong BHY, Olsen DG, Wellig B, Hofmann R. Applied heat exchanger network retrofit for multi-period processes in industry: A hybrid evolutionary algorithm. Computers & Chemical Engineering. 2022;161:107771. Crossref
[12] Halmschlager D, Beck A, Knöttner S, Koller M, Hofmann R. Combined optimization for retrofitting of heat recovery and thermal energy supply in industrial systems. Applied Energy. 2022;305:117820. Crossref
[13] Boldyryev S, Gil T, Ilchenko M. Environmental and economic assessment of the efficiency of heat exchanger network retrofit options based on the experience of society and energy price records. Energy. 2022;260:125155. Crossref
[14] Hang P, Zhao L, Liu G. Optimal design of heat exchanger network considering the fouling throughout the operating cycle. Energy. 2022;241:122913. Crossref
[15] Ishiyama EM, Pugh SJ, Wilson DI. Incorporating deposit ageing into visualisation of crude oil preheat train fouling. Process Integration and Optimization for Sustainability. 2020;4:187-200. Springer
[16] Lozano Santamaria F, Macchietto S. Online integration of optimal cleaning scheduling and control of heat exchanger networks under fouling. Industrial & Engineering Chemistry Research. 2020;59(6):2471-2490. ACS
[17] Trafczynski M, Markowski M, Urbaniec K. Energy saving and pollution reduction through optimal scheduling of cleaning actions in a heat exchanger network. Renewable and Sustainable Energy Reviews. 2023;173:113072. Crossref
[18] Ishiyama EM, Pugh SJ, Zettler HU. Economic and environmental implications of fouling in crude preheat trains. Heat Transfer Engineering. 2024;45(15):1277-1285. Taylor & Francis
[19] Wu Y, Wang Y, Liu R, Feng X. Applying plate heat exchangers in crude preheat train for fouling mitigation. Chemical Engineering Research and Design. 2021;165:150-161. Crossref
[20] Jamil MA, Goraya TS, Shahzad MW, Zubair SM. Exergoeconomic optimization of a shell-and-tube heat exchanger. Energy Conversion and Management. 2020;226:113462. Crossref
[21] Prajapati P, Raja BD, Savaliya H, Patel V, Jouhara H. Thermodynamic evaluation of shell and tube heat exchanger through advanced exergy analysis. Energy. 2024;292:130421. Crossref
[22] Isafiade AJ. Synthesis and retrofit of multiperiod heat exchanger networks considering heat transfer enhancement and environmental impact. Process Integration and Optimization for Sustainability. 2023;7:1031-1053. Springer
[23] Chen X, Huang J, Zhang L. A new programmed method for retrofitting heat exchanger networks using graph machine learning. Applied Thermal Engineering. 2024;242:122427. Crossref
[24] Villa L, Brusamarello CZ. Application of machine learning in monitoring fouling in heat exchangers in chemical engineering: A systematic review. Canadian Journal of Chemical Engineering. 2025;103(4):1786-1801. Wiley
[25] He S, Ye Y, Wang M, Zhang J, Tian W, Qiu S, Su GH. A machine learning and CFD based approach for fouling rapid prediction in shell-and-tube heat exchanger. Nuclear Engineering and Design. 2025;432:113759. Crossref
[26] Hou G, Zhang D, Yan Q, Wang S, Ma L, Jiang M. Application of machine learning algorithms in real-time fouling monitoring of plate heat exchangers. International Communications in Heat and Mass Transfer. 2025;164:108809. Crossref
[27] Ujević Andrijić Ž, Rimac N. Data-driven fouling detection in refinery preheat train heat exchangers using neural networks and gradient boosting. Sensors. 2025;25(16):4936. MDPI
[28] Jovet Y, Lefèvre F, Laurent A, Clausse M. Combined energetic, economic and climate change assessment of heat pumps for industrial waste heat recovery. Applied Energy. 2022;313:118854. Crossref
[29] Toghyani M, Saadat A. From challenge to opportunity: Enhancing oil refinery plants with sustainable hybrid renewable energy integration. Energy Conversion and Management. 2024;305:118254. Crossref
[30] Lau CYF, Chew YE, How BS, Andiappan V. Planning and optimisation of renewable energy systems for decarbonising operations of oil refineries. Process Integration and Optimization for Sustainability. 2025;9:93-116. Springer
How to cite this paper
@article{1723034,
author = {Mohammad Ismail Ansar Ahmed Ansari},
title = {Advanced Thermal Performance Optimization of Refinery Heat Transfer Systems for Saudi Vision 2030},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {2372-2384},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723034.pdf},
abstract = {The manner in which refinery heat-transfer systems function has a direct bearing on how efficiently high-grade process heat can be recovered before additional fuel, steam, or electricity is consumed; since this affects both operating costs and the achievement of industrial decarbonisation, the performance of these systems is of vital importance. This review gathers the research conducted between 2020 and 2025 on the advanced optimisation of the thermal performance of refinery heat exchangers and heat exchanger networks, with a specific emphasis on the relevance of these findings to Saudi Arabia's Vision 2030 transition. The evidence is organised around five interrelated factors: heat-integration retrofit, fouling-aware operation, equipment-level improvements, data-driven condition monitoring, and low-carbon heat upgrading. Recent studies of refineries have demonstrated that even technically sound measures can be undermined if the network's topology, pressure-drop constraints, changes in crude oil properties, the availability of cleaning operations, and interactions with utility systems are taken into account separately. A more dependable approach is to optimise thermal recovery and hydraulic operability over the entire operating cycle rather than merely at a single point that corresponds to a clean design condition. The review therefore offers a decision-making framework tailored to Saudi Arabia, giving priority to high measurement quality, accurate fouling diagnosis, operational changes that require no capital or only low capital, targeted network retrofit, and finally the integration of electrified or renewable heat. The synthesis indicates that the most beneficial action in the short term is to combine pinch-guided retrofit with fouling prediction and dynamic control, while longer-term decarbonisation will need the use of heat pumps, renewable energy, and flexible utility systems. There are still research gaps relating to plant-scale validation, the management of uncertainty, water-aware optimisation, operation at high ambient temperatures, and explainable machine-learning models. These gaps define a practical research programme for reducing refinery energy intensity without having to compromise reliability, throughput, or product quality.},
month = {September},
}