Multi-Factor-Coupled, Ahead-of-Time Aggregation of Power Flexibility Under Forecast Uncertainty

Shengyi Wang, Liang Du, Bai Cui, Yan Li

Research output: Contribution to journalArticlepeer-review

Abstract

The increasing penetration of distributed energy resources (DERs) is significantly reshaping the role of distribution systems under active energy management. To aggregate the active-reactive power flexibility of DERs dispersed at the feeder and provide capacity support to the transmission system, it is essential to efficiently identify feasible substation power injection trajectories. This paper introduces a novel ahead-of-time flexibility characterization method to address it. First, a polyhedral non-feeder-level power flexibility region (PFR) is constructed, accounting for various time-dependent, power-coupled, and forecast error uncertainties. Then, a polyhedral feeder-level PFR is analytically derived through a coordinate transformation, which can reveal the uncertainty propagation path, i.e., how uncertainty applies to the feeder-level PFR. To facilitate the high-level application, a tractable chance-constrained Chebyshev centering optimization model is further developed to find a ball -shaped inner approximation of the feeder-level PFR. Finally, the proposed method is validated on a modified IEEE 123- bus test system. Both theoretical and experimental results show that, with appropriate robustness parameter settings, the proposed method can make the approximated PFR less conservative with abundant robustness against forecast error uncertainty.

Original languageEnglish (US)
JournalIEEE Transactions on Sustainable Energy
DOIs
StateAccepted/In press - 2024

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment

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