Scenario-Based Optimal Power Flow Evaluation for Wind Power Allocation Capacity in Modern Power Systems

Integrating wind power into modern energy grids presents significant challenges due to its unpredictable nature. This study introduces a scenario-based optimal power flow model with Wind Farms Optimal Capacity in Grid (SOPF-WOCG) to enhance system flexibility and minimize curtailment. By leveraging the Generalized Dynamic Factor Model (GDFM), we improve wind power and load forecasts, filtering out noise and capturing key dependencies. Our findings demonstrate that this approach leads to better reserve management, fewer constraint violations, and improved system performance. Case studies show tangible benefits, including a 2.9% reduction in operational costs, a 2.7% decrease in ancillary costs, a 5.8% drop in curtailment expenses, and a 2.1% increase in the grid’s capacity to accommodate wind power. These results highlight the effectiveness of the proposed method in optimizing renewable energy integration while ensuring grid stability. Future work will explore real-time applications and integration with advanced forecasting and optimization techniques to further enhance grid reliability and efficiency.