An optimization-based multilayer operability framework is introduced for the process design of nonlinear energy systems that are challenged by complexity and highly constrained environments. In the first layer of this framework, a mixed-integer linear programming (MILP)-based iterative algorithm considers the minimization of the footprint and the achievement of process intensification targets. Then, in the second layer, an operability analysis is performed to incorporate into the approach key features for optimality and feasibility, accounting for the system operation with changeable input conditions. The outcome of the framework consists of a set of modular designs, considering the aspects of both size and process operability. For this study, the nonlinear system is represented by multiple linearized models, resulting in low computational expense and efficient quantification of operability regions. The developed framework is applied to a membrane reactor for direct methane aromatization conversion to hydrogen and benzene. Subsystems of dimensionalities of 2 × 2 and 3 × 3 (design inputs × outputs) are considered in the first layer to obtain a modular design region. The possible modular designs inside this region are then ranked according to an operability index obtained from an additional 3 × 3 (operational inputs × outputs) mapping. This step analyzes the effect of operational inputs, producing a mapping of total dimensionality of 6 × 3 (inputs × outputs). The application of the developed framework generates two candidate designs for system modularity, the most operable design and the optimal design with respect to process intensification in terms of footprint minimization. The developed framework thus provides guidelines for obtaining modular designs that simultaneously consider process intensification and operability aspects.

In this Article, the recently developed multimodel and NLP-based operability approaches are reviewed and further developed in terms of theory, application, and software infrastructure. Classical process operability concepts are also revisited and contrasted with new extensions present in both approaches. A focus is given on the comparison between distinct measures of the operability index and the handling of infeasible portions of the desired operating region. For the software infrastructure outcome, a framework for the development of process operability algorithms is provided. In particular, generated codes from the studied approaches are included in an open-source platform that will grant access of the algorithms to researchers from academia and industry. This platform has the purpose of dissemination and future improvement of process operability algorithms and methods. For the development of a versatile process operability tool, the considered approaches are adapted to support process models of generic dimensionalities. New contributions are also incorporated such as the conventional operability index calculation and other methods to find optimal design regions. Nonlinear energy systems of different input × output dimensionalities (6 × 3, 7 × 3, and 3 × 3) are addressed to demonstrate the applicability of the features available in the developed software tool to process achievability analysis, intensification, and modularization.

In this work, a novel systematic techno‐economic analysis framework is proposed for costing intensified modular systems. Conventional costing techniques are extended to allow estimation of capital and operating costs of modular units. Economy of learning concepts are included to consider the effect of experience curves on purchase costs. Profitability measures are scaled with respect to production of a chemical of interest for comparison with plants of traditional scale. In the developed framework, a base case scenario is analyzed to identify the relevance of the economy of learning and cost parameters that are yet to be established for modular projects that will be deployed. Then, a sensitivity analysis step is conducted to define changes in relevant variables that benefit the construction of modular systems. In a final step, scenarios in which the modular technology presents break‐even and further reduction in cost are identified. A process model for a modular hydrogen unit is developed and used for demonstration of the proposed framework. In this application, process synthesis is carried out, including operability analysis for selection of feasible operating conditions. A comparison with a benchmark conventional steam methane reforming plant shows that the modular hydrogen unit can benefit from the economy of learning. A synthesized flowsheet for a modular steam methane reforming plant is used to map the decrease in natural gas price that must be needed for the plant to break even when compared to traditional technologies. Scenarios in which the natural gas price is low allow break‐even cost for both individual hydrogen units and the assembled modular plant. For such break‐even cases, the economy of learning must produce a reduction of 40% or less in capital cost when the natural gas price is under 0.02 US$/Sm3. This result suggests that the synthesized modular hydrogen process has potential to be economically feasible under these conditions. The developed tools can thus be used to accelerate the deployment and manufacturing of standardized modular energy systems.

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