2026/2/12
Shoaib Khanmohammadi

Shoaib Khanmohammadi

Academic rank: Associate Professor
ORCID: 0000-0002-7659-7363
Education: PhD.
H-Index:
Faculty: Faculty of Engineering
ScholarId: View
E-mail: shoaib.khanmohammadi [at] gmail.com
ScopusId:
Phone: 0833-8305001
ResearchGate:

Research

Title
Performance enhancement and multi-objective optimization of a novel solar-driven system using soft computing for sustainable energy applications
Type
JournalPaper
Keywords
Solar-powered system exergoeconomic analysis multi-criteria optimization
Year
2025
Journal APPLIED SOFT COMPUTING
DOI
Researchers Reza Omidipour ، Shoaib Khanmohammadi

Abstract

The increasing demand for sustainable energy highlights the need for innovative systems capable of delivering efficient and environmentally responsible performance. This paper investigates a novel solar-driven hybrid thermodynamic system that integrates a Brayton cycle, a Rankine cycle with an open feedwater heater, and an ejector-based refrigeration subsystem (HBER), analyzed through energy, exergy, and exergoeconomic perspectives. Additionally, thermoelectric generators are incorporated at the heat rejection sides to enhance performance, minimize energy losses, and increase system power output. The study employs mass and energy conservation laws under steady-state conditions, while exergy analysis identifies exergy destruction and inefficiencies. The system achieves a net power output of 745.8 kW, an energy efficiency of 46.6 %, and an exergy efficiency of 19.65 %. The highest exergy destruction share occurs in the Brayton cycle subsystem, which is 93.73 % of the total exergy destruction rate. The addition of thermoelectric generators significantly boosts efficiency and power output. A parametric study explores the impact of turbine temperature, pressure, and radiation intensity on the system performance. Optimization via a genetic algorithm (GA) enhances energy and exergy efficiency by 1.63 % and 0.68 %, respectively, while increasing electricity production costs by 14.89 %. Also, two objective optimization scenarios have been discussed. The comprehensive nature of this study, with its thorough examination of the system from multiple perspectives, underscores the validity of its findings and the technological viability of the system, providing reassurance to the audience.