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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66744
Volume:
10 |
8 |
Aug 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Elecrical and Electronics Engineering
KLR College Of Engineering and Technology
Elecrical and Electronics Engineering
KLR College Of Engineering and Technology
Elecrical and Electronics Engineering
KLR College Of Engineering and Technology
This research lays forth a new approach to adaptive neuro-fuzzy inference systems (ANFIS) and Ant Lion optimisation (ALO) for standalone hydro power devices. Uneven current and voltage profiles occur in a hydropower generation system when it is fed non-linear loads. The important and sensitive loads are greatly affected by these imbalanced power levels, which last for an extended period of time. However, imbalanced load voltage and currents occur when hydro power producers, more often than not, use squirrel cage induction engines (SCIG), which often provide less voltage than needed. From this point of view, a unified electrical performance controller (UPQC) is used in this study to prevent these undesirable power quality concerns. Topologies that compensate for power quality are essential for achieving it. Voltage sag/swell is compensated for by the series regulator of UPQC, while harmonics of current & reactive power compensation are handled by the shunt controller. In this study, a hybrid ALO-ANFIS controller is used to effectively operate the series controller and shunt regulator of UPQC. As a hybrid smart system, ANFIS uses fuzzy logic to make accurate estimations of the compensation voltage. Optimising the ANFIS tuning settings, the ALO algorithm keeps a constant eye on the system's performance to make sure it's running at peak efficiency. This research examines hydropower production in relation to non-linear loads in order to verify the suggested control framework simulation.
KEYWORDS
In this study, a new ALO-ANFIS method is used to improve the electrical performance of independent hydropower systems, which is essential for the efficient running of a UPQC. Hydropower producing systems encounter voltage and current imbalances when irregular loads are linked to them. In order to correct the distorted voltages, the SeVSC of the UPQC injects the required voltage in the power supply network. To maintain peak performance, the ALO algorithm keeps tabs on the system and tweaks the ANFIS settings as needed. Then the ShVSC reduces the current's harmonics. Moving forward, the overall quality of the electricity is enhanced. The simulation results show that the UPQC based on ALO-ANFIS successfully controls the DC-link voltage and keeps the load current and voltage constant. Sustainable and dependable power production is within reach with the help of the suggested control method
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Publication Date
8/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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