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Advanced Research on Heat Exchanger Networks and Heat Recovery: 2nd Edition

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: 10 November 2026 | Viewed by 1737

Special Issue Editors

Dr. Stanislav Boldyryev

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Zagreb, Croatia
Interests: heat exchanger networks; heat transfers; energy saving; heat recovery; process integration
Special Issues, Collections and Topics in MDPI journals
Dr. Bohong Wang

E-Mail Website
Guest Editor
School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, China
Interests: energy storage system; energy network integration; energy system optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Timothy Gordon Walmsley

E-Mail Website
Guest Editor
School of Engineering Teaching and Research, The University of Waikato, Hamilton, New Zealand
Interests: energy; process integration; heat pumps; digital twins; heat and mass transfer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy is the one of the most important resources for modern society, with the use of energy defining the paradigm of economic development around the globe. Consequently, energy efficiency is a key issue in terms of both economic efficiency and environmental impact. Heat exchanger networks in different industries can recover processed heat energy, preventing additional fuel consumption in furnaces or electricity consumption for cooling cycles. Heat exchanger network synthesis, retrofitting, and optimisation comprise the long-term development goals that currently face new challenges. The industrial energy transition to renewable energies in line with low-carbon strategies guides new objectives towards heat exchanger network and heat recovery research. Both theoretical aspects and techno-economic criteria affect future industrial energy systems, wherein heat recovery plays a key role. This Special Issue aims to explore new advancements and prospective developments in heat exchanger networks, including topics such as network synthesis and optimisation, thermodynamic and thermal design, operation and maintenance, networks for industry electrification, digital twins of heat recovery systems, hydrogen-containing recovery systems, and the integration of renewable energies into heat recovery networks, among others.

Dr. Stanislav Boldyryev
Dr. Bohong Wang
Dr. Timothy Gordon Walmsley
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • heat exchanger networks
  • design and retrofit of recovery systems
  • network modelling and optimization
  • energy savings
  • operation, maintenance, prediction

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Related Special Issue

Published Papers (2 papers)

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28 pages, 3721 KB  
Article
A Fuzzy Bayesian-Based Integrated Framework for Risk Analysis of a Dual-Cycle Liquefied Natural Gas Cold Energy Power Generation System
by Yulin Zhou, Yungen He, Guojin Qin, Yihuan Wang, Chuanqi Guo, Chen Fang, Rongsheng Lin and Bohong Wang
Energies 2026, 19(3), 688; https://doi.org/10.3390/en19030688 - 28 Jan 2026
Viewed by 464
Abstract
LNG serves as a pivotal element within integrated energy systems, especially in coastal regions where the implementation of a stable and reliable LNG cold energy power generation system significantly elevates energy efficiency. This system can effectively meet concurrent demands for cold energy utilization [...] Read more.
LNG serves as a pivotal element within integrated energy systems, especially in coastal regions where the implementation of a stable and reliable LNG cold energy power generation system significantly elevates energy efficiency. This system can effectively meet concurrent demands for cold energy utilization and electricity supply while contributing to the mitigation of carbon emissions. However, the inherent complexity of the system coupled with the scarcity of historical operational data for the novel dual-Rankine cycle process renders conventional reliability assessment methodologies inadequate. This study proposes an integrated framework utilizing fuzzy Bayesian methods to address data scarcity during the early stages of equipment deployment. A hierarchical risk factor model, incorporating process decomposition, expert evaluations, and triangular fuzzy numbers, is developed to quantify uncertainties in failure probabilities. The Bayesian network models the causal relationships among equipment failure factors, allowing for the inference of overall system reliability from individual equipment performance. Through a case study of a LNG terminal in Zhoushan, this approach integrates sensitivity analysis with forward-backward reasoning methodologies to rigorously evaluate and quantify system reliability under operational conditions. The results show that under high load conditions within the 1000 h prior to overhaul, following long-term accumulated operation, the probability of complete system shutdown in the power generation system is 3.30%, while the probability of the LNG cold energy power generation system failing to operate fully due to aging-related faults is 8.24%, demonstrating the system’s strong reliability under extreme conditions. Critical risks identified through backward inference include the seawater pump SWP1, with a posterior failure probability of 59.92% during complete shutdown, and the propane-side pump SWP3, with a posterior failure probability of 32.29% when the cold energy power generation system can only operate in a single-cycle mode. This study provides an advanced methodological framework for risk management in newly constructed LNG cold energy power generation systems, playing a crucial role in promoting sustainable, low-carbon technologies in the energy sector. Full article
(This article belongs to the Special Issue Advanced Research on Heat Exchanger Networks and Heat Recovery: 2nd Edition)
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26 pages, 3837 KB  
Article
Design and Performance Analysis of MPPT Algorithms Applied to Multistring Thermoelectric Generator Arrays Under Multiple Thermal Gradients
by Emerson Rodrigues de Lira, Eder Andrade da Silva, Sergio Vladimir Barreiro Degiorgi, João Paulo Pereira do Carmo and Oswaldo Hideo Ando Junior
Energies 2025, 18(24), 6613; https://doi.org/10.3390/en18246613 - 18 Dec 2025
Cited by 1 | Viewed by 696
Abstract
Thermoelectric systems configured in multistring arrays of thermoelectric generators (TEGs) represent a promising solution for energy harvesting in environments with non-uniform thermal gradients. However, the presence of multiple maximum power points (MPPs) in such configurations poses significant challenges to energy extraction efficiency. This [...] Read more.
Thermoelectric systems configured in multistring arrays of thermoelectric generators (TEGs) represent a promising solution for energy harvesting in environments with non-uniform thermal gradients. However, the presence of multiple maximum power points (MPPs) in such configurations poses significant challenges to energy extraction efficiency. This study presents a comprehensive performance evaluation of four maximum power point tracking (MPPT) algorithms, Perturb and Observe (P&O), Incremental Conductance (InC), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), applied to multistring thermoelectric generator (TEG) arrays under multiple and asymmetric thermal gradients. The simulated systems, modeled in MATLAB/Simulink, replicate real-world thermoelectric configurations by employing series-parallel topologies and eleven distinct thermal scenarios, including uniform, localized, and sinusoidal temperature distributions. The key contribution of this work lies in demonstrating the superior capability of metaheuristic algorithms (PSO and GA) to locate the global maximum power point (GMPP) in complex thermal environments, outperforming classical methods (P&O and InC), which consistently converged to local maxima under multi-peak conditions. Notably, PSO achieved the best average convergence time (0.23 s), while the GA recorded the fastest response (0.05 s) in the most challenging multi-peak scenarios. Both maintained high tracking accuracy (error ≈ 0.01%) and minimized power ripple, resulting in conversion efficiencies exceeding 97%. The study emphasizes the crucial role of algorithm selection in maximizing energy harvesting performance in practical TEG applications such as embedded systems, waste heat recovery, and autonomous sensor networks. Future directions include physical validation through prototypes, incorporation of dynamic thermal modeling, and development of hybrid or AI-enhanced MPPT strategies. Full article
(This article belongs to the Special Issue Advanced Research on Heat Exchanger Networks and Heat Recovery: 2nd Edition)
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