Resource management with kernel-based approaches for grid-connected solar photovoltaic systems.

Area of Science:

• Electrical Engineering
• Power Systems Engineering
• Renewable Energy Integration

Background:

• High penetration of photovoltaic (PV) power generation causes grid issues like reverse power flow, voltage instability, and power loss.
• Existing grid management strategies struggle to effectively integrate large-scale PV systems.

Purpose of the Study:

• To develop a resource management strategy for grid-connected PV systems using smart inverters.
• To minimize voltage deviations and power losses in distribution grids with high PV penetration.
• To enhance grid stability and accommodate increased renewable energy sources.

Main Methods:

• Utilized smart inverters with active and reactive power injection capabilities.
• Proposed a kernel-based approach to learn optimal control policies for reactive power injection.
• Implemented nonlinear control policies for inverter coordination based on anticipated load and generation scenarios.

Main Results:

• Demonstrated significant minimization of power losses in the grid.
• Achieved effective voltage regulation, maintaining safe operating voltage limits.
• Validated the approach through numerical simulations on a single-phase grid-connected PV system (IEEE bus system).

Conclusions:

• The proposed kernel-based resource management strategy effectively mitigates challenges associated with high PV penetration.
• Smart inverter coordination using learned policies enhances grid performance by reducing losses and improving voltage stability.
• The approach offers a viable solution for stable and efficient integration of PV systems into distribution grids.