TY - JOUR
T1 - Distributionally Robust Distribution Network Configuration under Random Contingency
AU - Babaei, Sadra
AU - Jiang, Ruiwei
AU - Zhao, Chaoyue
N1 - Funding Information:
Manuscript received August 28, 2018; revised April 16, 2019 and September 4, 2019; accepted October 12, 2019. Date of publication February 13, 2020; date of current version August 24, 2020. This work was supported in part by the National Science Foundation CMMI-1662774, CMMI-1662589. Paper no. TPWRS-01322-2018. (Corresponding author: Ruiwei Jiang.) Sadra Babaei is with the School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK 74074 USA (e-mail: sadra.babaei@okstate.edu).
Publisher Copyright:
© 1969-2012 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - Topology design is a critical task for the reliability, economic operation, and resilience of distribution systems. This paper proposes a distributionally robust optimization (DRO) model for designing the topology of a new distribution system facing random contingencies (e.g., imposed by natural disasters). The proposed DRO model optimally configures the network topology and integrates distributed generation to effectively meet the loads. Moreover, we take into account the uncertainty of contingency. Using the moment information of distribution line failures, we construct an ambiguity set of the contingency probability distribution, and minimize the expected amount of load shedding with regard to the worst-case distribution within the ambiguity set. As compared with a classical robust optimization model, the DRO model explicitly considers the contingency uncertainty and so provides a less conservative configuration, yielding a better out-of-sample performance. We recast the proposed model to facilitate the column-and-constraint generation algorithm. We demonstrate the out-of-sample performance of the proposed approach in numerical case studies.
AB - Topology design is a critical task for the reliability, economic operation, and resilience of distribution systems. This paper proposes a distributionally robust optimization (DRO) model for designing the topology of a new distribution system facing random contingencies (e.g., imposed by natural disasters). The proposed DRO model optimally configures the network topology and integrates distributed generation to effectively meet the loads. Moreover, we take into account the uncertainty of contingency. Using the moment information of distribution line failures, we construct an ambiguity set of the contingency probability distribution, and minimize the expected amount of load shedding with regard to the worst-case distribution within the ambiguity set. As compared with a classical robust optimization model, the DRO model explicitly considers the contingency uncertainty and so provides a less conservative configuration, yielding a better out-of-sample performance. We recast the proposed model to facilitate the column-and-constraint generation algorithm. We demonstrate the out-of-sample performance of the proposed approach in numerical case studies.
KW - contingency
KW - Distribution network
KW - distribution-ally robust optimization (DRO)
KW - power system resilience
UR - http://www.scopus.com/inward/record.url?scp=85089431177&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85089431177&partnerID=8YFLogxK
U2 - 10.1109/TPWRS.2020.2973596
DO - 10.1109/TPWRS.2020.2973596
M3 - Article
AN - SCOPUS:85089431177
SN - 0885-8950
VL - 35
SP - 3332
EP - 3341
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 5
M1 - 8998220
ER -