Multi-objective optimization of a novel combined cooling, dehumidification and power system using improved M-PSO algorithm

• Published in: Energy (Oxford) Vol. 239; p. 122487
• Main Authors: Chang, Jinwei, Li, Zhi, Huang, Yan, Yu, Xiaonan, Jiang, Ruicheng, Huang, Rui, Yu, Xiaoli
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.01.2022; Elsevier BV
• Subjects: absorption; Air conditioning; Algorithms; batteries; Battery cycles; Carbon dioxide; Carbon dioxide emissions; case studies; Cooling; Cooling systems; Dehumidification; Desiccants; Design parameters; Distributed energy system; Electric power demand; Electric power systems; Electricity; Emissions; Emissions control; energy; Exhaust emissions; Heat; High temperature; hospitality industry; humidity; Internal combustion engines; Liquid desiccant dehumidification; liquids; Multi-objective optimization; Multiple objective analysis; Mutation; Mutation particle swarm optimization algorithm; Optimization; Particle swarm optimization; Performance assessment; Rankine cycle; Sensitivity analysis; Singapore; temperature; uncertainty; Waste heat; Waste heat recovery; Distributed energy system; Multi-objective optimization; Mutation particle swarm optimization algorithm; Liquid desiccant dehumidification
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2021.122487

This study proposes a novel combined cooling, dehumidification and power system based on internal combustion engine (ICE) for high temperature and humidity regions. In the proposed system, the electricity demand is mainly provided by ICE while the cooling and dehumidification demands are totally satisfied by absorption chiller (AC) and liquid desiccant dehumidification (LDD) units driven by waste heat of engine exhaust and jacket water. In addition, the electricity demand can be supplemented by battery and Organic Rankine Cycle (ORC) units driven by abundant waste heat of ICE. The aim of this system is designed to succeed the highly efficient utilization of ICE waste heat among AC, LDD and ORC units, and satisfy the multi-energy demands of users by optimizing the operation strategy. Firstly, a case study based on the actual power, cooling and dehumidification demands of a hotel building in Singapore is conducted to assess the performance of the proposed system. The parametric study of prominent design parameters in this system is investigated first to explore their effects on the system performance. Next, considering annual total cost and CO2 emissions as evaluation objectives, augmented ε-constraint method combined with improved Mutation particle swarm optimization (M-PSO) algorithm is used to conduct the multi-objective optimization of equipment capacity and operation. Finally, a sensitivity analysis of significant uncertainty factors is researched. The optimal results show that, compared to the traditional energy supply system, the annual carbon dioxide emission reduction ratio and total cost saving ratio can reach 35.91% and 25.46%, respectively. •A novel off-grid combined cooling, dehumidification and power system is proposed.•The effects of key design parameters on system performance are analysed.•Augmented ε-constraint with improved M-PSO algorithm is used for optimization.•The optimal configuration and operation strategy of the system are obtained.•The annual CO2 emission and total cost can be reduced by 25.46% and 35.91%.