Optimizing power generation in a hybrid solar wind energy system using a DFIG-based control approach.

Area of Science:

• Renewable Energy Systems
• Electrical Engineering
• Control Systems

Background:

• Growing demand for renewable energy drives innovation in hybrid systems.
• Hybrid Solar Wind Energy Systems (HSWES) combine solar and wind power for enhanced reliability.
• Grid integration of HSWES requires advanced modeling and control strategies.

Purpose of the Study:

• To develop and validate effective modeling and control techniques for grid-connected HSWES.
• To optimize power tracking efficiency in integrated solar photovoltaic and wind systems.
• To enhance the integration of HSWES with electrical grids.

Main Methods:

• Utilized vector control for rotor and grid converters in a back-to-back converter setup.
• Applied Maximum Power Point Tracking (MPPT) techniques for both solar and wind components.
• Employed Perturb and Observe (P & O) and Particle Swarm Optimization (PSO) for solar MPPT.
• Implemented hybrid Indirect Speed Controller MPPT for wind energy conversion.

Main Results:

• Validated the effectiveness of optimization techniques in enhancing control strategies.
• Demonstrated swift and precise monitoring of optimal power output for HSWES.
• Simulation results confirm the proposed system's efficacy in achieving optimal efficiency and stability.

Conclusions:

• The proposed control strategy effectively optimizes power extraction and hybrid system integration.
• Optimization algorithms significantly enhance the performance of solar photovoltaic systems.
• The developed techniques provide a robust solution for advancing sustainable energy integration.