9E analysis of a flat plate solar collector system implementation: A new approach based on digital twin model coupled with global sensitivity analysis and multi-objective optimization

Abstract

Flat plate solar collectors are technology with the most solar thermal energy field applications, and different studies based on artificial intelligence have been used to model these systems. This research study presents a 9E analysis based on a digital twin model coupled with global sensitivity analysis and multi-objective optimization of a solar system integrated with an array of flat plate solar collectors to satisfy residential hot water demand that represents a case study with different applications. A model based on artificial neural networks was trained, and a global sensitivity analysis using the Sobol method and a multi-objective optimization study using a genetic algorithm were also implemented. The main outcomes revealed that the digital twin model presented a high correlation above 0.99, and the 9E analysis reported a maximum value of 25.18% for thermal efficiency and 0.266% for exergetic efficiency. Also, a value of 1798.5 kgCO2/year was obtained for the amount of CO2 mitigated, $1342.9 USD for net present value, $0.0104 USD/kWh for levelized cost of energy, and 92.62, 0.519 kgCO2/year, $3.43, $1.34, and $0.00752 USD/year for energoenvironmental, exergoenvironmental, enviroeconomic energoenviroeconomic, and exergoenviroeconomic indicators, respectively. The methodology and the 9E analysis results provide a comprehensive approach that determines the optimal choice by analyzing the system's viability with different assessments and goes beyond the conventional analyses currently presented in the literature as it shows an untapped market potential for the best decision-making.