Operating Dynamic Reserve Dimensioning Using Probabilistic Forecasts

Speaker: Dr. Miquel Oretega Vazquez
Title –Operating Dynamic Reserve Dimensioning Using Probabilistic Forecasts

Abstract: The rapid integration of variable renewable energy sources (VRES) into power grids increases variability and uncertainty of the net demand, making the power system operation challenging. Operating reserve is used by system operators to manage and hedge against such variability and uncertainty. Traditionally, reserve requirements are determined by rules-of-thumb (static reserve requirements, e.g., NERC Reliability Standards), and more recently, dynamic reserve requirements from tools and methods which are in the adoption process, such as Dynamic Assessment and Determination of Operating Reserve (DynADOR), Dynamic Reserves Dimensioning (DRD), and RESERVE, among others. While these methods/tools significantly improve the static rule-of-thumb approaches, they rely exclusively on deterministic data (i.e., best guess only).

Consequently, these methods disregard the probabilistic uncertainty thresholds associated with specific days and their weather conditions (i.e., best guess plus

probabilistic uncertainty). This work presents practical approaches to determine the operating reserve requirements leveraging the wealth information from probabilistic forecasts. Proposed approaches are validated and tested using actual data from the California Independent System Operator (CAISO) system. Results show the benefits in terms of risk reduction of considering the probabilistic forecast information in the dimensioning process of operating reserve requirements.

Bio: Miguel A. Ortega-Vazquez received his Ph.D. from The University of Manchester (formerly UMIST), in 2006. He was a Postdoctoral Scholar at he University of Manchester, until 2010, and an Assistant Professor at Chalmers University of Washington (UW) as Assistant Professor. In 2017 he joined the Electric Power Research Insitute (EPRI), where he is a Principal. Dr. Ortega- Vazquez’s research interests revolve around the development and application of methods to facilitate an efficient, secure, and sustainable operation and planning of power systems.