Статья

Modeling of geothermal tailored CCHP system with heat recovery centered thermal design/analysis; ANN-based optimization and economic study

Weifeng LingXijing University, Xi’an, Shaanxi,710123, ChinaAzher M. AbedAir Conditioning and Refrigeration Techniques Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Babylon, 51001, IraqNaeim FaroukMechanical Engineering Department, College of Engineering in Alkharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi ArabiaYasser FouadDepartment of Applied Mechanical Engineering, College of Applied Engineering, Muzahimiyah Branch, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaDilsora AbduvalievaDepartment of Mathematics and Information Technologies, Tashkent State Pedagogical University, Bunyodkor avenue, 27, Tashkent, 100070, UzbekistanSaiful Islam‎Civil Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi ArabiaHakim AL GarallehDepartment of Mathematical Science, College of Engineering, University of Business and Technology, Jeddah 21361, Saudi ArabiaAlbara Ibrahim AlrawashdehDepartment of Chemistry and Chemical Technology, College of Science, Tafila Technical University, Tafila 66110 Jordan

Case Studies in Thermal Engineeringjournal2024en

ABI

Аннотация

This study conducts an evaluation of an integrated power, heat, and cooling system reliant on geothermal energy. The process involves integrating both the Organic Rankine Cycle (ORC) and the Goswami cycle. The main objective of this investigation is to analyze the effects of different variables on the system's operation. Additionally, a comprehensive analysis is undertaken to examine how the presence of operational fluids in the ORC affects the overall efficiency of the system. Subsequently, an in-depth economic evaluation is conducted, taking into account the initial investment for system implementation, operational capital, and the levelized cost of goods. The calculation process involves determining the system's income, cash flow, and pay-back time, which heavily rely on the selling prices of the products. By utilizing a genetic algorithm in conjunction with an artificial intelligence algorithm, the system can be optimized to minimize pay-back time and levelized cost of energy, while simultaneously maximizing net production power. The results of this optimization process are then compared with the baseline state of the system to assess the effectiveness of the proposed enhancements. The multifaceted approach enables the evaluation of the system's performance across different conditions and facilitates the optimization of its parameters to improve efficiency and economic feasibility. The comparative optimization results demonstrated a 21% reduction in payback time, a 14% increase in net power, and a 12% improvement in cooling when compared to the reference system state. The payback periods for different operating fluids ranged from 10 to 15 years. Isobutane demonstrated the shortest payback period of approximately 10 years, which was further optimized to 8. 6 years. The system demonstrated a power output of 655. 8 kW, a cooling output of 578. 3 kW, and a heat output of 3042 kW.

Темы

Thermodynamic and Exergetic Analyses of Power and Cooling Systems Geothermal Energy Systems and Applications Advanced Thermodynamics and Statistical Mechanics

Идентификаторы

DOI: 10.1016/j.csite.2024.104511

Цитирования и источники

Цитирований: 3 Использованных источников: 50

Показатели — AkademScholar · Скоро