The objective of the current work is to support the design of a pilot hydrogen and electricity producing plant that uses natural gas (or biomethane) as raw material, as a transition option towards a 100% renewable transportation system. The plant, with a solid oxide fuel cell (SOFC) as principal technology, is intended to be the main unit of an electric vehicle station. The refueling station has to work at different operation periods characterized by the hydrogen demand and the electricity needed for supply and self‐consumption. The same set of heat exchangers has to satisfy the heating and cooling needs of the different operation periods. In order to optimize the operating variables of the pilot plant and to provide the best heat exchanger network, the applied methodology follows a systematic procedure for multi‐objective, i.e. maximum plant efficiency and minimum number of heat exchanger matches, and multi‐period optimization. The solving strategy combines process flow modeling in steady state, superstructure‐based mathematical programming and the use of an evolutionary‐based algorithm for optimization. The results show that the plant can reach a daily weighted efficiency exceeding 60%, up to 80% when considering heat utilization.

This work proposes a novel approach for the simultaneous synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems. Given a set of hot and cold process streams and a set of available utility systems, the method determines the optimal selection, arrangement and design of utility systems and the heat exchanger network aiming to rigorously consider the trade-off between efficiency and capital costs. The mathematical formulation uses the SYNHEAT superstructure for the HEN, and ad hoc superstructures and nonlinear models to represent the utility systems. The challenging nonconvex MINLP is solved with a two-stage algorithm. A sequential synthesis algorithm is specifically developed to generate a good starting solution. The algorithm is tested on a literature test problem and two industrial problems, the optimization of the Heat Recovery Steam Cycle of a Natural Gas Combined Cycle and the heat recovery system of an Integrated Gasification Combined Cycle.

A novel sequential approach is proposed for the multiperiod synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems. The framework can be used also for single period problems. Given the set of hot and cold process streams with period dependent heat loads and target temperatures and a set of available utility systems, the algorithm determines the optimal utility system selection, design, and operation scheduling, as well as the optimal HEN. In this work, the approach of solving multiperiod problems by adopting (1) the Multiperiod Utility Integration and Scheduling model of Marećhal and Kalitventzeff, a modified formulation for (2) the Multiperiod Minimum Number of Units problem of Floudas and Grossmann, and (3) the Multiperiod Minimum Investment Network problem proposed by Floudas and Grossmann is improved by coupling the existing framework with the derivative-free hybrid algorithm PGS-COM of Martelli and Amaldi. Compared to the classic sequential approach, 3 it is possible to select, design, and determine the optimal operation scheduling (switching on/off) of the utility systems, to design the HEN considering not only parallel configuration of utilities but also series of utility exchangers and hybrids configurations, to optimize the matches between streams looking for the minimum total cost rather than only for the minimum number of units, and to account for nonlinear cost functions not related to heat exchangers area. The proposed framework is tested on small-scale and medium-scale case studies in order to make a comparison with the classic sequential approach.

To reach optimal/better conceptual designs of energy systems, key design variables should be optimized/adapted with system layouts, which may contribute significantly to system improvement. Layout improvement can be proposed by combining system analysis with engineers’ judgments; however, optimal flowsheet synthesis is not trivial and can be best addressed by mathematical programming. In addition, multiple objectives are always involved for decision makers. Therefore, this paper reviews progressively the methodologies of system evaluation, optimization, and synthesis for the conceptual design of energy systems, and highlights the applications to thermal power plants, which are still supposed to play a significant role in the near future. For system evaluation, both conventional and advanced exergy-based analysis methods, including (advanced) exergoeconomics are deeply discussed and compared methodologically with recent developments. The advanced analysis is highlighted for further revealing the source, avoidability, and interactions among exergy destruction or cost of different components. For optimization and layout synthesis, after a general description of typical optimization problems and the solving methods, the superstructure-based and -free concepts are introduced and intensively compared by emphasizing the automatic generation and identification of structural alternatives. The theoretical basis of the most commonly-used multi-objective techniques and recent developments are given to offer high-quality Pareto front for decision makers, with an emphasis on evolutionary algorithms. Finally, the selected analysis and synthesis methods for layout improvement are compared and future perspectives are concluded with the emphasis on considering additional constraints for real-world designs and retrofits, possible methodology development for evaluation and synthesis, and the importance of good modeling practice.

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