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Distributionally robust distributed generation hosting capacity assessment in distribution systems

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Version 1 2021-01-17, 10:09
journal contribution
posted on 2022-07-27, 05:55 authored by MSS Abad, J Ma, AS Ahmadyar, Hesamoddin Marzooghi
© 2018 by the authors. Uncertainties associated with the loads and the output power of distributed generations create challenges in quantifying the integration limits of distributed generations in distribution networks, i.e., hosting capacity. To address this, we propose a distributionally robust optimization-based method to determine the hosting capacity considering the voltage rise, thermal capacity of the feeders and short circuit level constraints. In the proposed method, the uncertain variables are modeled as stochastic variables following ambiguous distributions defined based on the historical data. The distributionally robust optimization model guarantees that the probability of the constraint violation does not exceed a given risk level, which can control robustness of the solution. To solve the distributionally robust optimization model of the hosting capacity, we reformulated it as a joint chance constrained problem, which is solved using the sample average approximation technique. To demonstrate the efficacy of the proposed method, a modified IEEE 33-bus distribution system is used as the test-bed. Simulation results demonstrate how the sample size of historical data affects the hosting capacity. Furthermore, using the proposed method, the impact of electric vehicles aggregated demand and charging stations are investigated on the hosting capacity of different distributed generation technologies.

History

Volume

11

Issue

11

Start Page

1

End Page

19

Number of Pages

19

eISSN

1996-1073

Publisher

MDPI AG, Switzerland

Additional Rights

CC BY 4.0

Peer Reviewed

  • Yes

Open Access

  • Yes

Acceptance Date

2018-10-29

External Author Affiliations

University of Sydney

Era Eligible

  • Yes

Journal

Energies