Sin Yong Teng
57208248696
Publications - 7
Exhaustive enumeration of heat exchanger networks with minimum utility consumption using graph-theoretic approach
Publication Name: Energy
Publication Date: 2025-10-30
Volume: 335
Issue: Unknown
Page Range: Unknown
Description:
Enhancement in energy recovery is always an essential element that requires academic spotlights to ensure its capability to contribute towards carbon neutrality. Recent works have extended to cover multi-solution heat exchanger networks (HEN) synthesis instead of generating a single best solution, which is not guaranteed to be practical. Nevertheless, owing to the technical challenges of synthesising all feasible networks, none of the existing works attempts to comprehensively elucidate how network topologies affect the network cost. To address this gap, P-HENS, a graph theoretic-based HEN synthesis tool, was utilised to generate the set of all heat exchanger networks with minimum utility consumption. Its effectiveness is demonstrated through an illustrative case study, which eventually generates more than 45,000 HENs. The impacts of structural variables on the cost, including the number of exchangers and the stream pairings, were analysed. The cost range of the networks was identified, revealing cost differences of 30 % despite minimum utility consumption or 15 % despite the minimum number of exchangers. Key stream pairs required to meet maximum energy recovery and influence cost were identified, leading to recommendations for improving solution searches. The solution set and the insight from this work are available to the research community for further analysis, offering valuable insights to enhance energy integration in the industry.
Open Access: Yes
The P-graph application extension in multi-period P2P energy trading
Publication Name: Renewable and Sustainable Energy Reviews
Publication Date: 2024-08-01
Volume: 200
Issue: Unknown
Page Range: Unknown
Description:
An optimization model that incorporates all combinatorically feasible inter-plant collaboration networks is developed using P-graph. It has been theoretically proven that time-sliced-based energy planning optimization has positive impacts and is capable of achieving carbon emissions reduction goals and minimizing costs simultaneously. However, as the number of entities increased, an exponential growth in possible combinatorial feasible coalitions is anticipated. Therefore, an extension of the P-graph optimization tool that is capable of generating all possible outcomes in multi-period P2P energy trading – PEP (P-graph for energy planning) is developed. The PEP software can be effectively used in modelling complex process networks graphically and solving optimization problems with the combined advantages of combinatorial algorithms and mathematical programming. In this paper, a systematic framework for implementing P2P energy trading using PEP software is proposed and demonstrated using a real-life case study.
Open Access: Yes
Electrification of oil refineries through multi-objective multi-period graph-theoretical planning: A crude distillation unit case study
Publication Name: Journal of Cleaner Production
Publication Date: 2024-01-01
Volume: 434
Issue: Unknown
Page Range: Unknown
Description:
Electrification using renewable energy sources is the key to paving a sustainable and cleaner future for the oil and gas sector, which is known to be a significant carbon dioxide emitter. Nevertheless, the suitability of the electrification designs heavily depends on the seasonal availability of renewable energy sources. This work proposes to use a multi-period graph-theoretical (P-graph) approach to determine the optimal retrofit strategy to achieve electrification with consideration of economic and environmental factors. Both single-period and multi-period models are considered via a graph-theoretical approach to rank and evaluate all the combinatorically feasible electrification pathways based on the overall performance. The effectiveness of the proposed method is developed using a crude distillation unit (CDU) case study adopted from a multinational company. The effectiveness of the proposed method is illustrated using a crude distillation unit (CDU) case study shown in three different scenarios that include prioritizing economic aspect (Scenario 1), prioritizing environmental aspect (Scenario 2), and considering equal importance of both aspects (Scenario 3). For single-period operation, the results showed a mix of natural gas and hydropower energy, exclusive use of onshore wind energy, and a mix of onshore wind energy and biogas cogeneration energy for Scenario 1, Scenario 2, and Scenario 3, respectively. In contrast, the multi-period model also utilized nuclear energy for Scenario 2 and Scenario 3 given the seasonal availability constraint. Following that, a sensitivity analysis is conducted to see the effect of the absence of the most influential energy sources on the optimal solution of each scenario and the top solutions under budget and CO2 emission constraints. Pareto analysis is outlined to offer an understanding of tradeoffs between differently prioritized solutions that decision-makers can select. The combination of the proposed analysis provides a systemic approach towards transforming traditional industries towards a cleaner future via electrification.
Open Access: Yes
Retrofit heat exchanger network optimization via graph-theoretical approach: Pinch-bounded N-best solutions allows positional swapping
Publication Name: Energy
Publication Date: 2023-11-15
Volume: 283
Issue: Unknown
Page Range: Unknown
Description:
Retrofit heat exchanger network (HEN) optimization is a fundamentally unique problem which requires the consideration of existing structures, compared to grassroots design problems. The optimization of retrofit HENs is particularly difficult due to the integration of both existing and newly acquired equipment. The re-routing of existing equipment can lead to various network topologies, increasing the complexity of considerations. In this work, we exploit the P-graph framework to solve retrofit HEN problems, guaranteeing to find the topology of optimal solutions within the constrained space of the HEN retrofit problem. The P-graph framework has additional advantages that allows topologically-efficient search space, simplifies additional unit placement, considers unit positional swapping (re-sequencing and re-piping within search constraints), considers stream splitting, and n-best solution visualization. The pinch minimum utility constraint also provides a bound for the maximum number of modifications in the HEN, significantly reducing search space. The proposed P-graph-based approach is demonstrated using a real refinery case study to show its capability in obtaining the topology of the optimal HEN, highlighting the economic and energy benefits. Further extensions to other retrofit process integration problems (e.g. retrofit water network, hydrogen network etc.) will be enabled via the proposed P-graph approach.
Open Access: Yes
Enabling in-depth analysis in heat exchanger network synthesis via graph-theoretic tool: Experiences in Swinburne University of Technology Sarawak Campus
Publication Name: Education for Chemical Engineers
Publication Date: 2023-04-01
Volume: 43
Issue: Unknown
Page Range: 100-112
Description:
The ability and capability to analyze and benchmark alternative designs on top of the optimal network are deemed valuable competencies for current and future chemical engineers. In this context, a process graph (P-graph)-inspired tool – P-HENS is introduced to an integrated plant design unit in an undergraduate chemical engineering degree program at Swinburne University of Technology Sarawak Campus in Malaysia. The energy recovery aspect is one of the key design elements in the integrated plant design unit. The introduction of P-HENS, which is capable of mathematically determining multiple optimal and sub-optimal solutions is considered useful for the students to (i) identify plausible heat exchanger networks (HENs) structures that may be overlooked using conventional approaches and (ii) enable a more in-depth analysis to justify the selected design. Overall, the implementation of P-HENS shows positive outcomes, where this free-of-charge software complements the learning of conventional manual approaches used in HENs synthesis. Furthermore, recommendations suggested by the users (students) are collected and compiled for potential future software development. This work serves as an essential reference for other chemical engineering educators who are teaching pinch analysis or heat integration-related courses.
Open Access: Yes
Framework to embed machine learning algorithms in P-graph: Communication from the chemical process perspectives
Publication Name: Chemical Engineering Research and Design
Publication Date: 2022-12-01
Volume: 188
Issue: Unknown
Page Range: 265-270
Description:
P-graph is a popularly used framework for process network synthesis (PNS) and network topological optimization. This short communication introduces a Python interface for P-graph to serve as a linkage to modern programming ecosystems. This allows for a wider application of the fast and efficient P-graph solver, to provide structural and topological enumeration in numerous fields. The proposed framework allows for more integrative usage in Artificial Intelligence (AI), machine learning, process system engineering, chemical engineering and chemometrics. Large and repetitive topologies can also be automated using the new programming interface, saving time and effort in modelling. This short communication serves as a demonstration of the newly developed open-sourced P-graph interface.
Open Access: Yes
Heat Integrated Water Regeneration Network Synthesis via Graph-Theoretic Sequential Method
Publication Name: Chemical Engineering Transactions
Publication Date: 2021-01-01
Volume: 88
Issue: Unknown
Page Range: 49-54
Description:
The integration of multiple resources conservation networks is necessary to attain the ever-stringent sustainable goals. This work takes initiatives to develop a heat integrated water network via a proposed P-graph-based sequential methodology. In the first step, a set of feasible water regeneration networks is generated using the conventional P-graph framework. Then, the obtained feasible networks will be used as the inputs in the second stage which aims to generate various sets of feasible heat exchanger networks. It is worth noting that the second model is solved by an extended P-graph framework (P-HENS) for combinatorial process network optimization. The solutions are then ranked based on the total network cost. To demonstrate the effectiveness of the proposed method, a typical water regeneration network (three sources and three sinks) with multi-contaminants is used. The results show a total of 103 feasible water network structures (water network cost ranging from 0.76 M$/y to 1.18 M$/y). Thereafter, a list of feasible HIWRN can be determined using P-HENS. The top four HIWRNs which offer similar total network cost (~1.639 M$/y) are demonstrated. This proposed method provides valuable insights that allow decision-makers to further select the optimal solution which may be more beneficial as compared to the one obtained via conventional methods.
Open Access: Yes
DOI: 10.3303/CET2188008
