A constructal theory framework for optimizing HRSG design: Enhancing thermal performance and cost-effectiveness - Morteza Mehrgoo; Majid Amidpour (Results in Engineering)
This study utilizes Constructal Theory and genetic algorithms to formulate a comprehensive optimization framework for selecting the appropriate type of Heat Recovery Steam Generator (HRSG) in combined cycle power plants. Constructal Theory facilitates the design of HRSG systems that achieve an optimal balance between thermodynamic efficiency and capital costs within a fixed volume, effectively addressing space constraints and geometric configurations in industrial applications. The framework utilizes both single- and multi-objective optimization techniques across three HRSG types, each linked to five different gas turbine models. The optimization considers critical geometric parameters directly influencing thermal efficiency by optimizing surface area, temperature gradients, and gas flow paths within the volume constraint. The results identify the optimal HRSG Type for each turbine: single-pressure for smaller turbines, dual-pressure for mid-sized, and triple-pressure for high-capacity turbines. Each type designed to minimize exergy destruction and capital costs while adhering to the specified volume constraints. The integrated Constructal-Genetic optimization framework delivers substantial performance enhancements, reducing exergy destruction by 18.3% (1.5 MW) in AE V94.3A turbines and 17.6% (0.9 MW) in GE LM6000 units compared to conventional designs. Thermal efficiency improvements facilitate a 7.3-9.8% increase in steam production while maintaining optimal pinch point temperature differences of 10-12°C. Additionally, the economic analysis highlights a 15% reduction in capital expenditures. These findings highlight the effectiveness of Constructal Theory in determining the optimal HRSG Type and precise geometric design for various gas turbine specifications, resulting in substantial improvements in energy recovery and cost efficiency.