Quantification of operational flexibility from a portfolio of flexible energy resources

• Published in: International journal of electrical power & energy systems 2022-10, Vol.141, p.107466, Article 107466
• Main Authors: Gusain, Digvijay, Cvetković, Milos̆, Palensky, Peter
• Format: Article
• Language: English
• Subjects: Flexibility quantification; Flexibility service provider; Power systems; Statistical methods
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2021.107466

Flexibility will be required as more renewable generation is integrated in the power system. Therefore, entities such as Flexibility Service Providers (FSPs) have emerged who can control a diverse set of resources in their portfolio to provide requested flexibility. An accurate and reliable assessment of the amount of dispatchable flexibility in FSP’s portfolio considering demand response activation, ramp rate, and post-activation rebound effects, etc. is important. In case FSP portfolio cannot fulfill the flexibility request, it must be known beforehand to avoid imbalance penalties. In this paper, we propose three flexibility quantification metrics: Expected Unserved Flexible Energy (EUFE), Expected Duration of Insufficient Flexibility (EDIF), and Expected Flexibility Index (EFI). These metrics are calculated using scenario-based simulations. The three metrics provide the FSP with quantifiable as well as graphical information on the magnitude and the duration of insufficient flexibility well ahead of gate closure time. This helps the FSP to design appropriate demand response programs (DRPs) and formulate their operational policy. These metrics account for uncertainty in forecasts of flexibility requests by evaluating multiple scenarios by conducting an operational simulation. With a representative case study, it is shown how an FSP can use the metrics to design DRPs, and when needed, schedule intraday market participation. •Three flexibility metrics are proposed to quantify operational flexibility in multi-energy system.•Metrics are inspired from long term power system adequacy metrics.•Metrics provide graphical and quantifiable information on operational flexibility of a portfolio.•A scenario-based simulation approach is used to derive the flexibility metrics.•Demand response programs are formulated using the proposed metrics.