Coordinated Multi-Scenario Optimization Strategy for Park Photovoltaic Storage Based on Master-Slave Game

Area of Science:

• Renewable Energy Systems
• Energy Economics
• Optimization Theory

Background:

• Photovoltaic (PV) systems face challenges in meeting load demands due to intermittency and fluctuations.
• Efficient operation of PV storage systems is vital for economic viability and reducing energy curtailment.
• Integrating energy storage systems (ESS) is key to stabilizing PV output and enhancing grid services.

Purpose of the Study:

• To develop a multi-scenario collaborative optimization strategy for PV storage systems.
• To maximize park operator profits while minimizing user electricity costs.
• To improve the economic efficiency and reliability of PV storage parks.

Main Methods:

• Implementation of a master-slave game model for collaborative optimization.
• Design of three distinct ESS application scenarios: PV stabilization, load transfer compensation, and frequency regulation (FR) market participation.
• Integration of a load response mechanism to reduce curtailment.

Main Results:

• Achieved a 25.8% increase in economic benefits for park operators.
• Reduced user electricity expenditures by 5.27%.
• Significantly lowered PV energy curtailment through the proposed strategy.

Conclusions:

• The proposed multi-scenario collaborative optimization strategy effectively enhances the economic performance of PV storage systems.
• The master-slave game model provides a robust framework for balancing operator profits and user costs.
• This approach promotes the sustainable development and widespread adoption of PV storage parks.