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Environmental problems have offered new challenges to the energy production sector, starting from the need of increasing the efficiency of thermodynamic systems to preserve fuel consumption. Accordingly, multi-energy generation systems are among the most efficient generation systems, and Heat Recovery Steam Generators (HRSGs) represent key components of such systems. In this regard, this paper shows a comprehensive approach to optimize a HRSG by using a multi-objective Genetic Algorithm (GA). The aim is to highlight how to determine the optimal values of geometrical and thermodynamic design variables according to two objective functions: the global costs to be minimized and the steam turbine output power to be maximized. Starting from a reference HRSG design, thermodynamic modeling and simulations as well as the optimization procedure are performed in MATLAB®. A validation is carried out to show the accuracy of the modeling approach. Latin Hypercube Sampling is applied to create a uniform sample to select the design variables based on a global sensitivity analysis, producing a significant reduction of computational efforts. Then, the GA optimization is performed to achieve the Pareto front, collecting the best trade-off design solutions. Economic savings up to 20% are achieved limiting the HRSG size.

The paper proposes a multi-objective optimization approach to address the energy design of the building envelope. A genetic algorithm (GA) is implemented by means of the coupling between MATLAB® and EnergyPlus to minimize primary energy consumption (PEC), energy-related global cost (GC) and discomfort hours (DH). The design variables concern the set point temperatures, the radiative properties of plasters, the thermo-physical properties of envelope components, the window type, the building orientation. The GA performs a Pareto optimization and finally two optimal solutions are recommended: the nZEB (nearly zero energy building) optimal solution, which minimizes PEC, and the cost-optimal solution, which minimizes GC. These solutions provide the optimal design strategies for the public and private stakeholders, respectively, which represent the main actors involved in building design. The approach is applied for the design of a new typical Italian residential building. Four locations are considered to investigate the typical Italian climates. The outcomes can give precious indications to rebuild the Italian residential stock with a view to energy-efficiency and cost-optimality, given that the optimal solutions provide low values of PEC – between 62.0 and 91.9 kWhp/m2a – and of GC – between 456 and 665 €/m2 – depending on the location.