TY - JOUR
T1 - Probabilistically robust AC optimal power flow
AU - Chamanbaz, Mohammadreza
AU - Dabbene, Fabrizio
AU - Lagoa, Constantino M.
N1 - Funding Information:
This work was supported in part by the CNR International Joint Lab COOPS, in part by the National Science Foundation under Grant CNS-1329422, and in part by the Singapore National Research Foundation (NRF) grant under the ASPIRE project under Grant NCR-NCR001-040.
Funding Information:
Manuscript received February 15, 2019; revised February 15, 2019 and February 17, 2019; accepted May 26, 2019. Date of publication June 5, 2019; date of current version September 17, 2019. This work was supported in part by the CNR International Joint Lab COOPS, in part by the National Science Foundation under Grant CNS-1329422, and in part by the Singapore National Research Foundation (NRF) grant under the ASPIRE project under Grant NCR-NCR001-040. Recommended by Associate Editor L. Wehenkel. (Corresponding author: Fabrizio Dabbene.) M. Chamanbaz is with the iTrust Center for Research in Cyber Security, Singapore University of Technology and Design, Singapore 487372 (e-mail:,Chamanbaz@sutd.edu.sg).
Publisher Copyright:
© 2014 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - The increasing penetration of renewable energy resources, paired with the fact that load can vary significantly, introduce a high degree of uncertainty in the behavior of modern power grids. Given that classical dispatch solutions are 'rigid,' their performance in such an uncertain environment is in general far from optimal. For this reason, in this paper, we consider ac optimal power flow (AC-OPF) problems in the presence of uncertain loads and (uncertain) renewable energy generators. The goal of the AC-OPF design is to guarantee that controllable generation is dispatched at minimum cost, while satisfying constraints on generation and transmission for almost all realizations of the uncertainty. We propose an approach based on a randomized technique recently developed, named scenario with certificates, which allows us to tackle the problem without the conservative parameterizations on the uncertainty used in currently available approaches. The proposed solution can exploit the usually available probabilistic description of the uncertainty and variability, and provides solutions with a priori probabilistic guarantees on the risk of violating the constraints on generation and transmission.
AB - The increasing penetration of renewable energy resources, paired with the fact that load can vary significantly, introduce a high degree of uncertainty in the behavior of modern power grids. Given that classical dispatch solutions are 'rigid,' their performance in such an uncertain environment is in general far from optimal. For this reason, in this paper, we consider ac optimal power flow (AC-OPF) problems in the presence of uncertain loads and (uncertain) renewable energy generators. The goal of the AC-OPF design is to guarantee that controllable generation is dispatched at minimum cost, while satisfying constraints on generation and transmission for almost all realizations of the uncertainty. We propose an approach based on a randomized technique recently developed, named scenario with certificates, which allows us to tackle the problem without the conservative parameterizations on the uncertainty used in currently available approaches. The proposed solution can exploit the usually available probabilistic description of the uncertainty and variability, and provides solutions with a priori probabilistic guarantees on the risk of violating the constraints on generation and transmission.
UR - http://www.scopus.com/inward/record.url?scp=85077368730&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077368730&partnerID=8YFLogxK
U2 - 10.1109/TCNS.2019.2921300
DO - 10.1109/TCNS.2019.2921300
M3 - Article
AN - SCOPUS:85077368730
SN - 2325-5870
VL - 6
SP - 1135
EP - 1147
JO - IEEE Transactions on Control of Network Systems
JF - IEEE Transactions on Control of Network Systems
IS - 3
M1 - 8731710
ER -