4.7 Article

Multi-objective optimization of CCHP system with hybrid chiller under new electric load following operation strategy

期刊

ENERGY
卷 219, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.119574

关键词

Combined cooling; Heating and power system; Electric load following strategy; Hybrid chiller; Multi-objective optimization

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A new electric load following strategy, NELF, was developed for hybrid chiller based CCHP systems and found to be the best choice in terms of reducing primary energy consumption, annual total cost, and carbon dioxide emission. Performance of CCHP systems and operation strategies were compared, with NELF showing better energetic, economic, and environmental performance under optimized conditions.
The performance of combined cooling, heating and power (CCHP) system is greatly affected by its operating strategy and design. In this paper, a new electric load following (NELF) strategy was developed. It is based on the alternation between absorption cooling and electric cooling according to the building energy requirements, for hybrid chiller based CCHP systems. A comparison of the new proposed strategy with the modified electric load following (MELF) and electric load following (ELF) strategies is performed. A multi-objective optimization approach based on genetic algorithm is carried out to predict the optimal capacity of CCHP systems. Performance criteria like primary energy consumption, annual total cost and carbon dioxide emission were considered as objective functions. The performances of these CCHP systems and operation strategies were examined and compared with the separated production (SP) system for a Mosque complex located in Algiers, Algeria. Results show that hybrid chiller CCHP based NELF strategy is the best choice, which can reduce the primary energy consumption by 34.45 GWh/year, annual total cost by 0.313 million V/year and carbon dioxide emission by 8.37 kton/year. Compared to the other configurations and strategies, the hybrid CCHP based NELF achieves better energetic, economic and environmental performance under the optimized conditions. (C) 2020 Elsevier Ltd. All rights reserved.

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