Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Bai Cui, Ahmed Zamzam, Andrey Bernstein

Research output: Contribution to conferencePaperpeer-review

5 Scopus Citations


Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

Original languageAmerican English
Number of pages6
StatePublished - 25 May 2021
Event2021 American Control Conference, ACC 2021 - Virtual, New Orleans, United States
Duration: 25 May 202128 May 2021


Conference2021 American Control Conference, ACC 2021
Country/TerritoryUnited States
CityVirtual, New Orleans

Bibliographical note

Publisher Copyright:
© 2021 American Automatic Control Council.

NREL Publication Number

  • NREL/CP-5D00-80783


  • aggregates
  • couplings
  • distributed power generation
  • simulation
  • substations
  • trajectory
  • uncertainty


Dive into the research topics of 'Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties'. Together they form a unique fingerprint.

Cite this