Enhancing power quality of pv grid-connected system through mantis shrimp optimization algorithm for optimal Dc bus...

Area of Science:

• Electrical Engineering
• Power Systems
• Renewable Energy

Background:

• Photovoltaic (PV) systems exhibit nonlinear and intermittent behavior, causing dynamic disturbances to DC bus voltage (Vdc) stability.
• Shunt active power filters (SAPFs) struggle with fluctuating Vdc, especially when the reference voltage (Vdc*) is static.
• Maximum Power Point Tracking (MPPT) algorithms like Perturb and Observe (P&O) further contribute to Vdc variability.

Purpose of the Study:

• To propose a real-time optimization strategy for dynamic Vdc* adjustment in PV systems with SAPFs.
• To enhance harmonic mitigation and maintain Vdc stability under varying operating conditions.
• To improve the overall power quality of the power grid.

Main Methods:

• Implementation of a Mantis Shrimp Optimization Algorithm (MShOA) for real-time Vdc* optimization.
• Utilizing real-time Total Harmonic Distortion (THD) feedback for adaptive voltage control.
• Comparative analysis with the Whale Optimization Algorithm (WOA) and conventional methods.

Main Results:

• The MShOA approach reduced THD from 3.59% to 2.33% before PV injection and maintained 4.19% after injection, within IEEE 519-92 standards.
• MShOA demonstrated superior performance compared to WOA, which resulted in 2.65% THD before and 5.78% after PV injection.
• The proposed method confirmed higher accuracy, faster convergence, and better adaptability for voltage regulation.

Conclusions:

• The MShOA-based real-time optimization strategy effectively addresses DC bus voltage instability in PV systems.
• This approach significantly improves harmonic mitigation and ensures robust voltage regulation under PV injection.
• MShOA offers a superior solution for enhancing power quality in grid-connected PV systems compared to existing methods.