Optimal model of PDIG based microgrid and design of complementary stabilizer using ICA

Area of Science:

• Electrical Engineering
• Control Systems
• Renewable Energy Systems

Background:

• Microgrids are increasingly incorporating renewable energy sources like photovoltaic (PV) systems.
• Integrating diverse energy sources (PV, diesel) and loads (induction motors) presents stability challenges.
• Existing models may not fully capture the dynamic behavior of complex microgrids with high renewable penetration.

Purpose of the Study:

• To develop and validate a generalized Heffron-Phillips model (GHPM) for a PV-diesel-induction motor-governor (PDIG) microgrid.
• To enhance microgrid stability and maximize PV power output through advanced control strategies.
• To investigate the effectiveness of a complementary stabilizer for mitigating electromechanical oscillations.

Main Methods:

• Linearization of the PDIG system around a specific loading condition to derive the GHPM.
• Sliding Mode Control (SMC) for Maximum Power Point Tracking (MPPT) of the PV system.
• Imperialist Competitive Algorithm (ICA) for optimizing the gains of a complementary stabilizer using a multi-objective function.
• Eigenvalue analysis and nonlinear time-domain simulations for stability assessment.

Main Results:

• The developed GHPM accurately represents the low-voltage microgrid dynamics.
• SMC effectively maximizes PV output power.
• The proposed complementary stabilizer, designed with ICA, significantly improves microgrid stability and damps electromechanical modes.
• Simulations demonstrate the robustness of the controllers under mechanical torque disturbances.

Conclusions:

• The proposed control strategies and GHPM provide an effective solution for enhancing the stability and performance of PV-diesel microgrids.
• The study validates the benefits of advanced control techniques for integrating higher percentages of renewable energy.
• The findings contribute to the reliable operation of microgrids with nonlinear loads and dynamic disturbances.