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.

Cryogenic separation of CO2 is a potential technology that can benefit from energy efficiency improvements. However, the current conventional and emerging cryogenic technologies face challenges in terms of high utility consumption. The high utility requirement leads to increasing operational costs and emissions due to the production of required utilities from external energy sources. This issue can be solved if the heat recovery potential of the technology can be realized. Heat recovery enables further improvement in energy efficiency that is required to elevate the feasibility of cryogenic separation. This paper explores heat recovery opportunities between hot and cold streams in a novel cryogenic CO2 capture technology known as Turbo-Expander-based Cryogenic Distillation (CryoDT). This is achieved using P-HENS, a P-graph-based heat exchanger network synthesis tool where multiple feasible heat exchanger network configurations are generated to determine the options that effectively recover process heat to reduce utility consumption. Moreover, the solutions generated by P-HENS are benchmarked with other tools like Aspen Energy Analyzer, by comparing the number of required heat exchangers, along with the associated capital and operating costs. For the predefined hot and cold process streams of the novel technology, the total number of heat exchangers present in the network was lower in the recommended design using P-HENS (i.e., 9 heat exchangers) as opposed to Aspen Energy Analyzer (16 heat exchangers) while maintaining similar energy consumption levels. This indicates that there is a further opportunity to reduce capital costs as a result of less heat exchangers. The CryoDT configuration that is integrated with a heat exchanger network offers significant economic advantages as opposed to other existing cryogenic processes in the market such as the Ryan Holmes and Controlled Freeze Zone (CFZ) processes. Despite its high capital cost, the CryoDT process demonstrates significantly lower operating cost relative to the other two processes. Hence, while the initial investment is substantial, the CryoDT process is much more cost efficient to operate. The low operating cost is attributed to its higher energy efficiency and minimal energy penalties, with only 0.26 GJ/tonne of CO2 compared with 0.82 GJ/tonne of CO2 for the CFZ process and 2.33 GJ/tonne of CO2 for Ryan Holmes. In contrast, the Ryan Holmes process, despite its low capital cost, incurs extremely high annual operational costs, rendering it less economic in the long term. The CFZ process, with its moderate operating cost, presents a balance between capital cost and operational efficiency.

Conversion of plastic waste into hydrogen is a potential solution to address the issues of growing demand for hydrogen and the massive accumulation of plastic waste simultaneously. However, most studies on plastic-to-hydrogen technology selection were based on predetermined plastic waste composition, limiting their applicability to dynamic real-life operations. To address this, this work introduces a flexible optimisation model capable of accommodating varying compositions of plastic waste. With the aid of regression models, the optimisation model can optimise the plastic-to-hydrogen production pathways, considering economic and environmental performances, without the constraints of specific plastic waste types or mixture compositions. Regression models are developed based on the ultimate analysis data (carbon, hydrogen, nitrogen, oxygen, and sulphur content) to estimate hydrogen yield and purity across various pathways. Thereafter, fuzzy optimisation is employed to identify the trade-off between cost and environmental impact. In addition to the selection of optimal plastic waste-to-hydrogen pathways, the model also considers different purification technologies that can improve the hydrogen purity to various extents. The model demonstrated that pyrolysis-steam reforming combined with PSA is capable of achieving hydrogen purity of 99.999 % with a highest overall satisfaction of 0.7141 (equivalent to total cost of 3.43 M$ and emissions of 528,647 kg CO2/y) while pyrolysis-catalytic decomposition is more suitable to produce hydrogen with lower purity (55 %).

Energy-intensive industries contribute large amounts of greenhouse gas emissions. An effective strategy to decarbonise these industries is by applying process integration tools to enhance energy efficiency and reduce overall energy consumption. Recent studies showed that thermal energy storage offers significant benefits in energy efficiency enhancement, as it can amplify the energy recovery potential. Despite its potential, studies that applied process integration tools to address heat recovery problems with consideration of heat storage remain limited. This work develops an optimisation framework that aims to determine optimal heat storage type and size based on the total annualised cost (i.e., costs associated with storage facilities and utilities) to form a feasible heat recovery network between plants. The proposed framework is demonstrated through a case study that focuses on optimising the sensible heat storage selection for indirect heat integration between a mixed plastic waste treatment plant and a steel mill. By analysing the performance and effectiveness of the storage media studied, nitrate salt storage medium is selected due to its greatest energy and cost savings of 12.7 % and 20.7 %, when compared to direct Heat Integration. Insights from this provide information on the feasibility of implementing a storage-supported heat recovery network in the energy-intensive industry.

Plastic waste conversion has been widely recognized as a promising strategy to address growing waste management challenges. However, the feasibility of its integration into existing industrial systems remains uncertain. This paper explores a plastic waste-to-X strategy aimed at reintegrating plastic waste into its original supply chain, in alignment with circular economy principles. A graph-theoretic optimization model is developed using P-graph to identify the optimal and near-optimal pathway configurations under multiple scenarios. Under a cost minimization scenario, the optimal solution achieves a 0.013–0.19% lower cost compared with alternative pathways; however, related to the higher opportunity cost of up to 24,364 USD/y from forgone utility savings and carbon tax reductions. Incorporating carbon credits shifts the focus toward balancing cost efficiency and emission reduction. Under budget constraints, the benefit-cost analysis reveals that emission reduction does not increase linearly with budget expansion. These findings guide decision-makers in setting realistic emission reduction targets and allocating budget efficiently, while helping policymakers to develop a financial scheme that promotes greater emission reductions without excessive expenditure.

Energy-based industrial symbiosis is a potential decarbonisation strategy for energy-intensive industries, which contribute significantly to carbon emissions. Thermal energy storage (TES) can be integrated to enhance energy efficiency and operational flexibility, while addressing issues related to supply–demand fluctuations. Nonetheless, the economic feasibility of TES-supported interplant heat recovery depends on the costs and properties of the storage media incorporated. Therefore, this work presents a systematic framework for optimising TES selection across a spectrum of storage options for interplant indirect heat integration. The objective is to minimise the total annualised cost (TAC), comprising energy and storage capital costs. The optimal TES option can then be identified based on its respective TAC ranking. A case study that compares the effectiveness of the indirect method against the intraplant and direct methods is conducted. The results show that among the 33 TES options evaluated, silica fire brick offers the lowest TAC and energy-related carbon emissions, leading to a reduction of 21.60% and 13.16%, respectively, as compared to the intraplant method. Subsequently, a sensitivity analysis is performed to explore the impacts of varying stream flowrates and storage capacity redundancy allocation on the TES selection. This provides insights into the performance of various TES options under intraplant, direct, and indirect heat integration methods. Finally, the threshold (i.e., stream flowrate required to provide economic gain under a given redundant allocation scenario) aligned with the strategic planning can be determined. This work demonstrates that TES integration can improve the economic feasibility and sustainability of industrial symbiosis in energy-intensive industries.