Document Type : Research paper


1 University of Kerbala/ College of Engineering/ Department of Electrical and Electronics Engineering/Iraq

2 Medical technical college; Al-Farahidi University, Baghdad , Iraq

3 Al-Nisour University College/Iraq

4 Department of Medical Laboratory Technics, Al-Zahrawi University College, Karbala, Iraq

5 Al-Esraa University College, Baghdad, Iraq

6 Department of biomedical engineering/ Ashur University College/Baghdad/ Iraq

7 Scientific Research Center, Al-Ayen University, Thi-Qar, Iraq


Insufficient synchronization between the operational efficiency of capacitors and tap-changer transformers in regulating voltage presents a fundamental challenge in distribution networks, which in turn hinders the control performance. This challenge is caused by the inability of these two components to synchronize their respective operations properly. In this study, a novel control strategy is presented with the objective of achieving synchronization in the functioning of capacitors and tap transformers. Depending on the load change, various devices can be used to control the distribution network voltage. On Load Tap Changers (OLTCs) and Capacitor Banks (CBs) respond slowly to voltage changes. If the voltage changes rapidly, such devices are useless and should be avoided. Keying may shorten lifespan. This study investigated a new optimal control mechanism for coordinating tap transformers and capacitors. The optimization of tap trans- and capacitor-stage operation through the use of a Genetic Algorithm (GA) results in the reduction of superfluous switching. The limits for Point of Common Coupling (PCC) bus voltage and power factor are 0.94 and 1.02 per unit, respectively. The secondary control stage regulates the voltage of the feeder bus within the range of 0.95 to 1.05 per unit. Following the second-stage regulation of the terminal buses in the N network feeder, the third stage governs the PCC bus voltage. To prevent an infinite control loop, the voltage of the PCC bus is regulated within the range of 0.95 to 1.05 per unit (PU). These findings indicate that the optimization model is capable of achieving maximum efficiency in controlling the voltage of the distribution network. In the interim, this optimization technique produces outcomes of greater accuracy, as evidenced by a voltage value that remains consistently close to unity [Root Mean Square Error (RMSE) = 0.85] across a broad spectrum of network-loading scenarios.


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