All-condition simulation modeling method and system for radial turbine based on particle swarm optimization

Abstract

The invention discloses an all-condition simulation modeling method and system for a radial turbine based on particle swarm optimization for compressed-air energy storage. The method comprises the steps of: determining an input quantity, an output quantity and model parameters of a dynamic radial turbine simulation model; establishing a radial turbine simulation model for calculating the frictionloss and incidence loss of the radial turbine, and optimizing the process of solving the radial turbine simulation model; solving the optimization problem using the particle swarm optimization to obtain the output quantity of the radial turbine simulation model; reducing the simulation error caused by falling into local optimal value by using a loop iterative processing method; and building an all-condition simulation module of the radial turbine based on the particle swarm optimization on a Matlab / Simulink platform, wherein the module can be freely combined with other models in the Matlab / Simulink. The simulation model obtained can effectively show the running condition of the radial turbine under all conditions, and has a low simulation error.

Description

technical field [0001] The invention belongs to the field of system simulation modeling, and more specifically relates to a particle swarm algorithm-based simulation modeling method and system for full working conditions of a centripetal turbine. Background technique [0002] Compressed-Air Energy Storage (CAES) technology has the advantages of low cost, long life, large capacity, and relatively few site selection constraints, and is considered to be the most promising large-scale energy storage technology. However, traditional compressed air energy storage technology has three obvious disadvantages: dependence on fossil fuels, low cycle efficiency, and the need for large gas storage chambers. Among them, supercritical compressed air energy storage (SC-CAES) technology is considered to be one of the most effective ways to solve the above three defects. At present, many SC-CAES demonstration projects are under construction in China. In the SC-CAES system, the turbine is the...

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Problems solved by technology

However, traditional compressed air energy storage technology has three obvious disadvantages: dependence on fossil fuels, low cycle efficiency, and the need for large gas storage chambers

[0003] At present, in the simulation modeling research on turbines, most of them are based on static thermodynamic models of turbines or dynamic simulation modeling for piston turbines, and there are relatively few researches on simulation modeling methods for centripetal turbines.

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