An efficient integration strategy for a SOFC-GT-SORC combined system with performance simulation and parametric optimization. (5th July 2017)

• Record Type: Journal Article
• Authors: Zhang, Shiqi; Liu, Haolun; Liu, Meili; Sakaue, Eiichi; Li, Ning; Zhao, Yingru
• Is Part Of: Applied thermal engineering. Volume 121(2017)
• Page Start: 314
• Page End: 324
• Publication Date: 2017-07-05
• Subjects: SOFC -- GT -- Supercritical ORC -- Integrated system modelling -- Parametric sensitivity analysis -- gPROMS; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2017.04.066
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: A novel integrated power system comprising SOFC, GT and ORC is proposed. A split flow preheating configuration of the supercritical ORC is adopted. The electrical and CHP efficiencies can reach 66.27% and 88.43% respectively. The integrated model is formulated in gPROMS with detailed parametric analyses. The optimal system behavior is determined with design trade-offs being addressed. Abstract: The present study aims to establish an integrated modelling and optimization framework for a combined power system comprising fuel cell, gas turbine and Organic Rankine Cycle (ORC). The method is based upon the coupling of a syngas fueled solid oxide fuel cell-gas turbine (SOFC-GT) hybrid model and a bottoming supercritical ORC model developed using gPROMS to efficiently determine the range of appropriate operating conditions. A comprehensive and detailed analysis is carried out to simulate system behavior and to investigate the influence of key design and operating parameters on the system performance. The fuel flowrate and operating temperature of fuel cell, the pressure ratios of turbines, together with the flow split ratio of the ORC cycle are all set to be controllable variables. The results indicate that an electrical efficiency of 66.27% and a CHP efficiency of 88.43% are achievable for the integrated system. The analysis enables us to identify the system design tradeoffs, and therefore to determine optimal integration strategies for complex polygeneration systems.