Optimization and performance assessment of solar-assisted combined cooling, heating and power system systems: Multi-objective gradient-based optimizer

Li, L.-L., Qu, L.-N., Tseng, M.-L., Lim, M. K. , Ren, X.-Y. and Miao, Y. (2024) Optimization and performance assessment of solar-assisted combined cooling, heating and power system systems: Multi-objective gradient-based optimizer. Energy, 289, 129784. (doi: 10.1016/j.energy.2023.129784)

Abstract

This study compares the performance of the optimal installation of solar-assisted combined cooling, heating, and power system (CCHP) running different strategies using the energy consumption information of hospital buildings as input to the model. In addition, a novel multi-objective gradient-based optimizer is developed to obtain CCHP configuration schemes under different strategies. A multi-objective optimum configuration model of solar-assisted CCHP, including solar thermal collector, photovoltaic system, microturbine, gas boiler, heat storage device, and battery, is constructed. In addition, two other strategies are obtained by adapting the basic operation strategy while renewable energy with a fossil fuel-based energy supply system achieves a significant reduction in the gas consumption and emission of pollutants. The optimization results prove that compared with other strategies, the solar-assisted CCHP system operating the following electric load with electric cooling ratio (FEL-ECR) strategy has a better economy, environmental protection, and energy saving. The corresponding carbon dioxide emission reduction rate, primary energy saving rate, and annual total cost saving rate of the system running the FEL-ECR strategy reach 53.27 %, 39.01 %, and 33.88 %.

• Item Type: Articles
• Keywords: Renewable energy, multi-objective gradient-based optimizer, combined cooling, heating and power system.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Professor Ming
• Authors: Li, L.-L., Qu, L.-N., Tseng, M.-L., Lim, M. K., Ren, X.-Y., and Miao, Y.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Journal Name: Energy
• Publisher: Elsevier
• ISSN: 0360-5442
• ISSN (Online): 1873-6785
• Published Online: 13 December 2023
• Copyright Holders: Copyright © 2023 Elsevier Ltd
• First Published: First published in Energy 289: 129784
• Publisher Policy: Reproduced in accordance with the publisher copyright policy