Abstract
The pump provides the necessary pressure and flow for the organic Rankine cycle (ORC) system. The traditional methods have obvious limitations when analyzing the time-varying characteristics of the key operating parameters of the pump. This study first introduces the scatter plot analysis method to analyze and evaluate the time-varying and coupling characteristics of the hydraulic diaphragm metering pump. Then, a machine learning-fitting algorithm hybrid model is constructed to solve and verify the actual matching correlation equation of the key operating parameters. In addition, the complicated non-linear relationship brings great challenges to obtaining the limit value of the pump isentropic efficiency. This study introduces the bilinear interpolation algorithm to systematically analyze the change trend between operating parameters and isentropic efficiency. Based on the wavelet neural network (WNN) with momentum term and particle swarm optimization-adaptive inertia weight adjusting (PSO-AIWA), a machine learning framework with an intelligent algorithm is constructed. Under this framework, the maximum isentropic efficiency of the pump can be stabilized at 70.22–74.67% under all working conditions. Through the theoretical analysis model, the effectiveness of this framework is evaluated. Finally, the optimal cycle parameters are evaluated. This study can provide direct significance for the analysis and optimization of the actual performance of the ORC system.
Highlights
Energy is the foundation of economic development
The working fluid pump provides the necessary pressure for the organic Rankine cycle (ORC), which directly determines the performance of the system (Villani and Tribioli, 2019; Ping et al, 2021a; Ping et al, 2021b)
The key operating parameter matching correlation equation of the hydraulic diaphragm metering pump takes into account the nonlinear mapping relationship between operating parameters and time-varying characteristics, which provides useful guidance for the theoretical analysis, experimental design, and component matching of the ORC system
Summary
Energy is the foundation of economic development. The rapid economic development is accompanied by the massive consumption of energy, which makes the problem of energy shortage and environmental pollution increasingly severe. This study introduces the scatter plot analysis method and the bilinear interpolation algorithm to analyze timevarying characteristics of the key operating parameters and the change trend of isentropic efficiency under all working conditions. The key operating parameter matching correlation equation of the hydraulic diaphragm metering pump takes into account the nonlinear mapping relationship between operating parameters and time-varying characteristics, which provides useful guidance for the theoretical analysis, experimental design, and component matching of the ORC system. Obtaining the maximum value of the isentropic efficiency of the hydraulic diaphragm metering pump under different working conditions is conducive to the selection of numerical values in theoretical calculations It brings direct guidance for obtaining the ORC system performance limits. The corresponding hydraulic diaphragm metering pump speeds are 870 r/min–2900 r/min
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