Abstract
Recently, requirements on the operation of electric power systems (EPS) aimed at improving the reliability of power supply to the consumer, power quality and energy efficiency have increased. To satisfy these requirements intelligent network technologies (Smart Grid) which allow the most efficient use of energy resources have purposefully been introduced. The implementation of these requirements is based on the deliberate introduction of smart grids technologies (Smart Grid) which allow the most efficient use of energy resources.
The Smart Grid concept envisages the creation of a developed system of automatic control of EPS modes on the basis of active devices and distributed generators (DG). To provide their effective operation it is necessary to solve the problem of optimal tuning of automatic exciting regulators (AER) and automatic speed regulators (ASR) of these generators
The article describes the methods of using the wavelet transform and genetic algorithms (GA) for consistent tuning of AERs and ASRs of distributed generators operating in the railway power supply system (RPSS). It shows the efficiency of the wavelet transform technology in separating the noise of the regulator used in identification and reception as well as in obtaining the DG experimental structural and mathematical model using frequency transfer functions. The proposed adaptive GA makes it possible to solve the problem of finding optimal coefficients of AER and ASR control taking into account their cross effect. The described algorithms are implemented in the MATLAB language in a specialized software package designed for the EPS identification and optimization of AER and ASR generator settings.
The computer simulation results obtained on the RPSS model with DGs in MATLAB show the efficiency of the proposed method which provides the necessary stability margin and good damping of electromechanical oscillations in the system.
Keywords: electric power systems; distributed generators, wavelet transform, identification, optimization of automatic regulator settings, genetic algorithms, automatic exciting regulator, automatic speed regulator,harmonized settings
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