A Model-Based Parameter Space in Monte Carlo Simulations for European Short-Term Adequacy Assessments

The Short-Term Adequacy (STA) assessment is crucial for raising risk awareness among stakeholders and aiding European system operations in quickly identifying potential risks. To calculate cross-border exchange capacities in European STA assessments, the flow-based (FB) approach is used to define the parameter space in Monte Carlo simulations. However, Transmission System Operators (TSOs) currently rely on data-driven methods to define the FB domain. These methods necessitate extensive historical data on import-export capacities, which may not always align with Monte Carlo samples. Issues related to Energy Not Served (ENS) can arise even when Monte Carlo samples are aligned with the FB domain. To address these challenges, this paper introduces an analytical model based on parametric programming. This model maps the decision variables to zonal total loads, ensuring a more accurate parameter space in Monte Carlo simulations, and is free from ENS issues. Additionally, the model proactively adjusts the ENS index to reflect the parameter space under specific ENS conditions, thereby enhancing the generation of accurate Monte Carlo scenarios for subsequent STA assessments.