Investigating the Optimum Operational Strategy of Energy Storage Tank by Using Particle Swarm Algorithm. Issue 7 (17th April 2015)

• Record Type: Journal Article
• Authors: Hajabdollahi, Hassan; Pourgholamali, Najmeh
• Is Part Of: Heat transfer - Asian research. Volume 45:Issue 7(2016)
• Page Start: 648
• Page End: 660
• Publication Date: 2015-04-17
• Subjects: Energy storage tank -- Operational strategy -- Particle Swarm Optimization -- Total annual cost; Heat -- Transmission -- Periodicals; Electronic journals; 621.4022
• DOI: 10.1002/htj.21181
• Languages: English
• ISSNs: 1099-2871

Abstract

Abstract : Optimal design of an energy storage tank system is presented in this study. Total annual cost is considered as the objective. To minimize the total annual cost, 24 design parameters including the operational strategy of the chiller in each hour during a sample day are selected. A Particle Swarm Optimization (PSO) algorithm is used for three different strategies including partial storage (PS), full storage (FS), and variable storage (VS), separately. In addition, this procedure is performed for both electrical and absorption chillers. There was a 25.21% and 13.80% improvement in total annual cost observed in the VS strategy compared with the PS and FS strategies, respectively, in the case of an electrical chiller. Furthermore, 23.47% and 8.01% improvement in total annual cost is observed in the VS strategy compared with the PS and FS strategies, respectively, in the case of an absorption chiller. Moreover, the electrical chiller was found to be more suitable in this study but no sensible difference is observed in the FS strategy. Finally the optimum results of the PSO algorithm is compared with the Genetic Algorithm (GA) and differences are reported.