Robust Optimization Research of Cyber-Physical Power System Considering Wind Power Uncertainty and Coupled...

Area of Science:

• Electrical Engineering
• Complex Networks
• Optimization Theory

Background:

• Power systems face challenges from intermittent wind power and the intricate coupling between power and communication networks.
• Existing models often fail to adequately address the combined impact of these factors on system robustness.

Purpose of the Study:

• To develop a bi-level mixed-integer robust optimization strategy to enhance power system resilience.
• To mitigate the effects of wind power uncertainty and power-communication coupling on system stability and reliability.

Main Methods:

• Constructed a coupled network model using complex network theory to represent interdependencies between power and communication systems.
• Developed a bi-level robust optimization model with fuzzy chance constraints for the upper level (load shedding minimization) and a topology-function-constrained traffic model for the lower level (traffic load shedding minimization).
• Utilized a modified IEEE 39-bus test system for case studies and simulations, including random attack scenarios.

Main Results:

• The proposed strategy effectively reduces load shedding by optimizing DC power flow under wind power fluctuations.
• The lower-level model enhances information network efficiency by minimizing traffic load shedding.
• Simulations showed a 23.6% reduction in load loss ratio and a 5.3% improvement in node survival ratio compared to a baseline model under high-stress conditions.

Conclusions:

• The bi-level robust optimization strategy significantly improves power system resilience against wind power uncertainty and network coupling.
• The integrated approach provides a robust framework for managing complex power and communication network interactions.
• Findings offer valuable insights for designing more reliable and stable future power grids.