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Developing an algorithm for the adaptive neural network for direct online speed control of the three-phase induction motor Al-Mahasneh, Ahmad J.; Salah, Samer Z.; Ghaeb, Jasim A.; Baniyounis, Mohammed
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1499-1510

Abstract

In this paper, an online adaptive general regression neural network (OAGRNN) is presented as a direct online speed controller for a three-phase induction motor. To keep the induction motor running at its rated speed in real-time and under a variety of load conditions, the speed error and its derivative are continuously measured and fed back to the OAGRNN controller. The OAGRNN controller provides the inverter with the control signal it needs to produce the proper frequency and voltage for the induction motor instantly. Notably, the OAGRNN controller demonstrated remarkable performance without the need for a learning mode; it was able to track the desired motor speed, starting its operation from scratch. A setup utilizing a three-phase induction motor has been developed to show the high capacity of OAGRNN for tracking the desired speed of the motor while subjected to the varied load torque. The performance of OAGRNN is examined in two phases: the MATLAB simulation and the experimental setup. Furthermore, when the OAGRNN performance is compared with that of the proportional integral (PI) controller, it demonstrates its outstanding ability and superiority for online adjustments related to the three-phase induction motor's speed control.
A new approach for optimal sizing and allocation of distributed generation in power grids Alkashashneh, Hudefah; Agha, Ayman; Baniyounis, Mohammed; Al-Rousan, Wasseem
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1598-1607

Abstract

This paper presents a methodology for optimizing the allocation and sizing of distributed generators (DG) in electrical systems, aiming to minimize active power losses on transmission lines and maintain bus voltages within permissible limits. The approach consists of two stages. First, a sensitivity based analysis is used to identify the optimal candidate bus or buses for DG placement. In the second stage, a new random number generation method is applied to determine the optimal DG sizing. Moreover, a ranking for the optimal locations and sizes is given in case the optimal location is unavailable in real-world scenarios. The proposed methodology is demonstrated through a straightforward algorithm and tested on the IEEE 14-bus and IEEE 30-bus networks. Numerical simulations in MATLAB illustrate the effectiveness of the proposed approach in finding the optimal allocation of DG and the amount of active power to be allocated at the candidate buses, considering the inequality constraints regarding voltage limits and DG allowable power. The paper concludes with results, discussions, and recommendations derived from the proposed approach.