Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters

Abstract

Line-start permanent magnet synchronous motors (LSPMSMs) are of great interest to researchers because of their high energy efficiency, due to the growing interest of manufacturers in energy-efficient units. However, LSPMSMs face some difficulties in starting and synchronization processes. The LSPMSM lumped parameter model is applicable to estimating the successfulness of starting and further synchronization. The parameters of such a model can be determined using computer-aided identification algorithms applied to real motor transient processes’ curves. This problem demands significant computational time. A comparison between two algorithms, differential evolution and Nelder–Mead, is presented in this article. The algorithms were used for 0.55 kW, 1500 rpm LSPMSM parameter identification. Moreover, to increase computational speed, it is proposed to stop and restart the algorithms’ procedures, changing their parameters after a certain number of iterations. A significant advantage of the Nelder–Mead algorithm is shown for the solving of the considered problem.

Synchronous Generator Stability Characterization for Gas Power Plants Using Load Rejection Tests

“…(1) In the first step, the model is simulated under no-load conditions in order to change the controllers' set point (steady-state parameters) of the AVR and speed governor in an idle move. In order to achieve more accurate solutions, heuristic fitting algorithms should be implemented in the iterative processes of GAST and SEXS models, such as genetic [27,28] or evolutionary algorithms [29]. They would be good candidates for this application, as the computation time is not a critical variable in the characterization process and they avoid the effect of local minimum solutions.…”

“…The iterative process used to fit the parameters of the GAST and SEXS models has been carried out manually in order to adjust the first transient oscillation, which is the most important for stability studies. However, other fitting tools such as evolutionary algorithms could be used to solve the problem [27][28][29].…”

“…Finally, a schematic flowchart that sums up the power plant characterizatio odology using load rejection tests is plotted in Figure 7. The iterative process us the parameters of the GAST and SEXS models has been carried out manually in adjust the first transient oscillation, which is the most important for stability studie ever, other fitting tools such as evolutionary algorithms could be used to solve th lem [27][28][29].…”