AI iQ-F Controller based Control of Power Factor in Power System Operating with Different Sources and Loads
The quality of any load is decided by its power consumption and PF (power factor). For resistive load, the pf is always unity, and it is less than unity if the connected load is inductive or capacitive load. Nowadays, Industries are mainly focusing to control the power quality issues like mitigation of other than fundamental or multiple frequency components and maintaining the pf irrespective of the load. Today APFC (Automatic Power Factor Correcting) is used for correcting the power factor from lagging to unity. But the drawback of APFC is that uses the fixed bank of capacitors. Due to the fixed bank size capacitors, the desired value of power factors is not maintained at all the time. Smoothening control of power factor is not achieved in the conventional APFC method. If the connected sources are exceedingly more than one, then it is difficult to sense the input current and phase angle values from each phase. In ordered to overcome the above-mentioned drawbacks, the AI compact controller-based power factor control method is introduced. AI compact controller uses the high-speed Input and Outputs which senses the current without any measuring delay. The phase angle is accurately measured by this compact controller. The fixed inductor and capacitor bank are converted into the dynamic inductor and capacitive bank by installing the power electronics switches like IGBT. By controlling the PWM pulses applied to the IGBT, the effective value of L and C are controlled. Thereby, the amount of magnetizing power fed into the system or grid is controlled.
Authors
- Sandip Kanase (ORCID: https://orcid.org/0000-0002-1211-0536)
- Shubhangi Gurav
- Girish Madhaorao Lonare
- Deelip Bhagwatrao Radkar (ORCID: https://orcid.org/0000-0002-2446-7727)
- Prathamesh Patil
- W. Rajanbabu
Institutions
- Sri Eshwar College of Engineering
- Bharati Vidyapeeth (Deemed to be University) (IN)
Publication Details
- Published
- 2024-10-23
- DOI
- https://doi.org/10.1109/icssas64001.2024.10760593
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00