Introducing machine learning and hybrid algorithm for prediction and optimization of multistage centrifugal pump in an ORC system

Abstract The isentropic efficiency of the working fluid pump has a significant impact on the overall performance of the organic Rankine cycle (ORC) system. Based on machine learning, this paper proposes an experimental data-driven isentropic efficiency prediction model. Meanwhile, S-fold cross validation algorithm and smoothing factor circulation screening technology are used to improve the predictive ability of the model. The prediction accuracy of the optimized model and the unoptimized model are compared with each other. The influence of several operating parameters on isentropic efficiency are analyzed. In addition, with intelligent algorithm, the boundary values of operating parameters are determined. The genetic algorithm (GA) and particle swarm optimization (PSO) are combined into a GA-PSO hybrid algorithm. Subsequently, the hybrid algorithm is integrated with the machine learning model to predict and optimize the isentropic efficiency under full operating conditions. The highest isentropic efficiency reaches up to 58.73%. The prediction and optimization of the isentropic efficiency of multistage centrifugal pump under full operating conditions provides not only a useful guidance on assuming pump efficiencies in theoretical analysis, but also a meaningful reference for obtaining the optimum overall operating performance of the ORC system.

[1]  Wenguang Li,et al.  Correction of cavitation with thermodynamic effect for a diaphragm pump in organic Rankine cycle systems , 2020, Energy Reports.

[2]  Jianhua Liu,et al.  Experimental study on multi-stage gas-liquid booster pump for working fluid pressurization , 2017 .

[3]  Jian Zhang,et al.  Prediction and optimization of power output of single screw expander in organic Rankine cycle (ORC) for diesel engine waste heat recovery , 2021 .

[4]  R. Carapellucci,et al.  Enhanced performances of ORC-based units for low grade waste heat recovery via evaporator layout optimization , 2019, Energy Conversion and Management.

[5]  Hongguang Zhang,et al.  Parametric optimization and performance analysis of ORC (organic Rankine cycle) for diesel engine waste heat recovery with a fin-and-tube evaporator , 2015 .

[6]  Vincent Lemort,et al.  Techno-economic survey of Organic Rankine Cycle (ORC) systems , 2013 .

[7]  Sergio Rech,et al.  Semi-empirical model of a multi-diaphragm pump in an Organic Rankine Cycle (ORC) experimental unit , 2018 .

[8]  Jian Zhang,et al.  Thermoeconomic multi-objective optimization of a dual loop organic Rankine cycle (ORC) for CNG engine waste heat recovery , 2017 .

[9]  B. Lei,et al.  Matching and operating characteristics of working fluid pumps with organic Rankine cycle system , 2018, Applied Thermal Engineering.

[10]  Massimiliano Renzi,et al.  A general methodology for performance prediction of pumps-as-turbines using Artificial Neural Networks , 2018, Renewable Energy.

[11]  Hongguang Zhang,et al.  Prediction and optimization of isentropic efficiency of vortex pump under full operating conditions in Organic Rankine Cycle waste heat recovery system based on deep learning and intelligent algorithm , 2020 .

[12]  Roberto Cipollone,et al.  Design and analysis of a sliding vane pump for waste heat to power conversion systems using organic fluids , 2017 .

[13]  Richard N. Christensen,et al.  EXPERIMENTAL TESTING OF GEROTOR AND SCROLL EXPANDERS USED IN, AND ENERGETIC AND EXERGETIC MODELING OF, AN ORGANIC RANKINE CYCLE , 2009 .

[14]  Roberto Cipollone,et al.  Modeling and Experimental Activities on a Small-scale Sliding Vane Pump for ORC-based Waste heat Recovery Applications , 2016 .

[16]  Yonghong Xu,et al.  Experimental and simulation study of a free piston expander–linear generator for small-scale organic Rankine cycle , 2018, Energy.

[17]  Yiji Lu,et al.  Parametric study on melting process of a shell-and-tube latent thermal energy storage under fluctuating thermal conditions , 2020 .

[18]  A. Roskilly,et al.  Chemisorption power generation driven by low grade heat – Theoretical analysis and comparison with pumpless ORC , 2017 .

[19]  Hongguang Zhang,et al.  Study of efficiency of a multistage centrifugal pump used in engine waste heat recovery application , 2017 .

[20]  Heejin Cho,et al.  Artificial neural network (ANN) based prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery , 2018 .

[21]  Xiang-long Luo,et al.  Experimental investigation of operation behavior of plate heat exchangers and their influences on organic Rankine cycle performance , 2020 .

[22]  Xiaoli Yu,et al.  Parametric study for small scale engine coolant and exhaust heat recovery system using different Organic Rankine cycle layouts , 2017 .

[23]  Suresh Kumar,et al.  A technical review on waste heat recovery from compression ignition engines using organic Rankine cycle , 2018 .

[24]  A. Pesyridis,et al.  Review of Organic Rankine Cycle experimental data trends , 2018, Energy Conversion and Management.

[25]  Jiang Wang,et al.  Performance evaluation of a low-temperature solar Rankine cycle system utilizing R245fa , 2010 .

[26]  Yang Shi,et al.  Sensitivity analysis and thermoeconomic comparison of ORCs (organic Rankine cycles) for low temperature waste heat recovery , 2015 .

[27]  Judith Gurney.  BP Statistical Review of World Energy , 1985 .

[28]  Wei Wang,et al.  Experimental study and theoretical analysis of a Roto-Jet pump in small scale organic Rankine cycles , 2016 .

[29]  Rémi Revellin,et al.  Performance investigation of reciprocating pump running with organic fluid for organic Rankine cycle , 2017 .

[30]  G. Kosmadakis,et al.  Investigating the performance and cost effects of nanorefrigerants in a low-temperature ORC unit for waste heat recovery , 2020 .

[31]  Joaquín Navarro-Esbrí,et al.  Experimental characterization of an Organic Rankine Cycle (ORC) for micro-scale CHP applications , 2015 .

[32]  Jinliang Xu,et al.  Operation and performance of a low temperature organic Rankine cycle , 2015 .

[33]  Qian Wang,et al.  Modelling, simulation and comparison of phase change material storage based direct and indirect solar organic Rankine cycle systems , 2020, Applied Thermal Engineering.

[34]  Yi Liu,et al.  Experimental study and performance analysis of a hydraulic diaphragm metering pump used in organic Rankine cycle system , 2018 .

[35]  Min-Soo Kim,et al.  Parametric study and performance evaluation of an organic Rankine cycle (ORC) system using low-grade heat at temperatures below 80 °C , 2017 .

[36]  Hua Tian,et al.  Design space exploration for waste heat recovery system in automotive application under driving cycle , 2019, Energy.

[37]  Henk Huisseune,et al.  Experimental testing of a low-temperature organic Rankine cycle (ORC) engine coupled with concentrating PV/thermal collectors: Laboratory and field tests , 2016 .

[38]  C. Markides,et al.  Working-fluid selection and thermoeconomic optimisation of a combined cycle cogeneration dual-loop organic Rankine cycle (ORC) system for solid oxide fuel cell (SOFC) waste-heat recovery , 2020 .

[39]  Hao Liu,et al.  Unsteady analysis of a bottoming Organic Rankine Cycle for exhaust heat recovery from an Internal Combustion Engine using Monte Carlo simulation , 2016 .

[40]  J. Mahmoudimehr,et al.  Modeling and thermo-economic optimization of a new multi-generation system with geothermal heat source and LNG heat sink , 2019, Energy Conversion and Management.

[41]  Kai Yang,et al.  Development and experimental study on organic Rankine cycle system with single-screw expander for waste heat recovery from exhaust of diesel engine , 2014 .

[42]  Tzu-Chen Hung,et al.  Experimental study on low-temperature organic Rankine cycle utilizing scroll type expander , 2015 .

[43]  T. Turunen-Saaresti,et al.  Experimental study of small scale and high expansion ratio ORC for recovering high temperature waste heat , 2020, Energy.