ESTIMATION OF SUBMERSIBLE INDUCTION MOTOR EQUIVALENT CIRCUIT PARAMETERS BASED ON TEST DATA

Abstract

One of the main problems in operation of wells equipped with installations of electric centrifugal pumps is determining the technical condition of submersible electrical equipment and preventing its failures. Among the various approaches to solving this problem, one can single out a method for determining the technical state of an installation of electric centrifugal pumps using a complete customizable mathematical model of the installation, including a model of a submersible electric motor. This article discusses an approach to determining and restoring the necessary parameters for tuning a submersible electric motor model based on the data given in the submersible electric motor test report. The main aim of the research is todevelop a methodology for restoring the parameters of the equivalent circuit for submersible electric motor on the basis of typical data contained in the acceptance test report. Methods. The proposed approach is based on the combined use of a tunable dynamic model of a squirrel-cage induction motor and a differential evolution algorithm. The actual solution to determine the parameters of submersible electric motor damage is reduced to solving the global optimization problem, i.e. to the problem of finding the global (best) minimum of a function. Results.The authors have developed an approach for restoring the parameters of the submersible electric motor equivalent circuit, which allows setting the values of the equivalent circuit parameters for the submersible electric motor, acceptable for practice, according to the test results; the performance of the developed identification approach was tested using global optimization methods and mathematical modeling of submersible induction motors; the obtained estimates are stable for all parameters of the equivalent circuit except for the parameter of the mechanical subsystem.

Keywords

• identification
• induction machine
• genetic algorithms
• heuristics
• submersible electric motor
• differential evolution
• multivariate mathematical optimization
• multivariate data
• stochastic algorithms