A novel TLFD-GA algorithm for multi-objectives optimization of ORC power plants with the effect of pressure drop considered

Abstract

This research introduces a novel TLFD-GA algorithm for the three-level criteria optimization of organic Rankine cycle (ORC) power plants. It replaces the non-dominated sorting of NSGA-II with three-level fuzzy decision to simultaneously optimize environmental, thermodynamic, and techno-economic criteria. The algorithm provides direct optimization results without needing additional decision-making methods. Furthermore, the impact of pressure drop in plate heat exchangers is investigated, revealing a proportional relationship between pressure drop and the increment of evaporation pressure. A parametric study on 24 basic and recuperative trans-critical geothermal ORC systems indicates that compensating for pressure drop leads to a 5% decrease in thermodynamic performance, a 20% decrease in techno-economic performance, and a 20–60% increase in heat transfer area per net output power. After TLFD-GA optimization, the saving to investment ratio improves by an average of 4.5% across scenarios. R1270 stands out with a remarkable ratio of 3.13 and 4.32 in medium and high-temperature geothermal reservoirs. Moreover, the proposed TLFD-GA optimization algorithm has demonstrated its superiority in terms of superb convergence and stability when compared to NSGA-II, which suggests its prospective application in the low-carbon and green energy fields.