To achieve the ever-stringent sustainable goals, this paper aims to synthesize a heat integrated hydrogen regeneration network (HIHRN) using a graph-theoretic-based sequential method. Firstly, the optimal and near-optimal structures for a hydrogen regeneration networks (HRN) are determined using P-graph model with consideration of both impurity and pressure constraints. These networks are then used as inputs in P-HENS software to generate a list of optimal and near-optimal heat exchanger network (HEN) structures. An eight source and sink problem is used to demonstrate the effectiveness of the proposed method. There are 199,677 feasible HIHRN structures identified, while the 6 near-optimal solutions which are within 0.05% tolerance of the optimal network cost (i.e., less than 33.04 M$/y) are presented together with the top four HEN designs that can offer comparable costs (∼115,500 $/y). In addition, the impacts of pressure swing adsorber (PSA) pressure drop consideration and minimum temperature difference on the optimal design are also presented.

Biofuel from microalgae is one of the promising solutions on addressing climate change by its possibility of reducing the fossil fuel dependency. Till-date, the overall competitiveness of microalgae based biorefinery is the major concern due to its unique operational mechanism, especially the biological growth of microalgae that fluctuates towards the surrounding. Therefore, a novel graph-theoretic approach has been proposed to provide an optimization approach for identifying optimal process design with the consideration of three aspects that includes: economic, environmental, and reliability. The optimization is conducted using P-graph (a powerful graph-theoretic tool) which is capable to determine optimal and near-optimal solutions based on three objective functions: (i) minimizing annual operating cost, (ii) minimizing potential environmental impact, and (iii) maximizing reliability of process. The pool of feasible solutions (optimal and near-optimal) is obtained by satisfying the constraints on both greenhouse gas emissions and its respective reliability along. Thereupon, a further analysis was carried out with the aid of TOPSIS considering three of the assessment aspects to identify the optimal microalgae biorefinery configuration

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.