Adaptive frequency control in smart microgrid using controlled loads supported by real-time implementation

Area of Science:

• Electrical Engineering
• Control Systems
• Renewable Energy Integration

Background:

• Microgrid (μG) frequency stability is crucial but challenged by load variations, renewable intermittency, and parameter uncertainty.
• Existing control methods may struggle with dynamic disturbances and complex system uncertainties.

Purpose of the Study:

• To develop and evaluate a novel adaptive controller for frequency oscillation mitigation in a single-area smart microgrid.
• To enhance microgrid stability by integrating flexible loads like heat pumps (HPs) and electric vehicles (EVs) controlled via a hybrid optimization technique.

Main Methods:

• Application of a hybrid Jaya-Balloon optimizer (JBO) for an adaptive controller design.
• Utilizing the power balance equation for a dynamic output feedback controller.
• Controlling smart bidirectional loads (HPs and EVs) to regulate system frequency and power.

Main Results:

• The proposed JBO-based adaptive controller significantly improved frequency stability.
• Achieved a frequency deviation of 0.0015 Hz, well within IEEE standards.
• Demonstrated superior performance over Coefficient Diagram Method (CDM) and classical Jaya techniques in simulations and real-time tests.

Conclusions:

• The hybrid JBO adaptive controller offers a robust solution for frequency regulation in islanded microgrids.
• The technique effectively manages disturbances from load changes, solar irradiation, wind, and parameter variations.
• Real-time simulations confirmed the MATLAB findings, validating the controller's practical applicability.