A hybrid probabilistic assessment using different renewable penetration scenarios in the North American bulk power system

This paper provides an analysis on the challenges to reliability introduced by increased penetration of Variable Energy Resources (VER) on the North American Bulk Power System (BPS). This paper highlights the importance of addressing VER availability, their inconsistent impacts to total system load, and the associated risks for system planning and operations. Further presented are risk-based approaches focusing on modeling VER with net demand uncertainties at peak intervals. The included work is part of a larger effort by the North American Electric Reliability Corporation (NERC) to demonstrate the benefits of applying probabilistic approaches for a better understanding of emerging BPS trends and to promote reliable operation and planning efforts. Hourly demand, VER (i.e., wind and solar) profiles along with their associated statistical characterization are presented for a California Independent System Operator (CAISO) case study. Peak analysis is applied to construct peak shapes using high VER penetration scenarios with differently assigned peak intervals (or signal partitions) to investigate the volatility impacts of increased wind and solar power to support further operational risk and resource adequacy assessments. The paper then proposes a hybrid model by combining these constructed peak shapes at different intervals with a risk-based, probabilistic approach using a Monte-Carlo simulation method to assign VER and net load probability distributions. Findings suggest that the amount of MW operating reserves needed at shorter peak intervals are slightly higher than longer termed intervals due to the stochastic nature of wind and solar at small timescales. In addition, this hybrid model can be used to further support operational risk and resource adequacy assessments in addressing reliability and emerging issues in a probabilistic purview. The paper concludes that balancing high VER penetration with reliability will require changes in system operation and planning measures.