Performance evaluation of solar hybrid combined cooling, heating and power systems: a multi-objective arithmetic optimization algorithm

Li, L.-L., Ren, X.-Y., Tseng, M.-L., Wu, D.-S. and Lim, M. K. (2022) Performance evaluation of solar hybrid combined cooling, heating and power systems: a multi-objective arithmetic optimization algorithm. Energy Conversion and Management, 258, 115541. (doi: 10.1016/j.enconman.2022.115541)

Abstract

The coupling of solar thermal and photovoltaic technologies with combined cooling, heating and power systems has significant impacts on the reduction of fossil fuel consumption and pollutant emissions. In this study, a mathematical model of a hybrid combined cooling, heating, and power system consisting of thermal storage units, batteries, microturbines, photovoltaic units, and solar thermal collectors, is developed. Meanwhile, based on the following thermal load strategy and following electric load strategy, the following the state of battery strategy is proposed. A multi-objective arithmetic optimization algorithm is proposed by using non-dominated sorting, mutation operations, and external archive mechanism to optimize the configuration of the hybrid system under different strategies. Besides, an optimal compromise is obtained by technique for order preference by similarity to an ideal solution method. A large hotel case is used to evaluate the performance of the hybrid system under different strategies. The optimization results show that the Pareto solutions obtained by the developed optimization algorithm are uniformly distributed. Moreover, compared with the hybrid system under the following electric load and following thermal load strategies, the hybrid system under the proposed strategy achieves better primary energy saving ratio, carbon dioxide emission reduction ratio, and energy efficiency, and these indicators reach 46.56%, 54.64%, and 78.51%, respectively.

• Item Type: Articles
• Additional Information: This study was supported by the key project of Tianjin Natural Science Foundation [Project No. 19JCZDJC32100] and the Natural Science Foundation of Hebei Province of China [Project No. E2018202282].
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Professor Ming
• Authors: Li, L.-L., Ren, X.-Y., Tseng, M.-L., Wu, D.-S., and Lim, M. K.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Journal Name: Energy Conversion and Management
• Publisher: Elsevier
• ISSN: 0196-8904
• ISSN (Online): 1573-0638
• Published Online: 29 March 2022
• Copyright Holders: Copyright © 2022 Elsevier Ltd.
• First Published: First published in Energy Conversion and Management 258: 115541
• Publisher Policy: Reproduced in accordance with the publisher copyright policy