C
Cédric Josz
Researcher at University of California, Berkeley
Publications - 53
Citations - 1216
Cédric Josz is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Semidefinite programming & Optimization problem. The author has an hindex of 18, co-authored 45 publications receiving 1007 citations. Previous affiliations of Cédric Josz include Los Alamos National Laboratory & Columbia University.
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AC Power Flow Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE
TL;DR: Nine new test cases in MATPOWER format are published, the largest of which is a pan-European ficticious data set that stems from the PEGASE project and provides a MATLAB code to transform the data into standard mathematical optimization format.
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The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms
Sogol Babaeinejadsarookolaee,Adam B. Birchfield,Richard D. Christie,Carleton Coffrin,Christopher L. DeMarco,Ruisheng Diao,Michael C. Ferris,Stephane Fliscounakis,Scott Greene,Renke Huang,Cédric Josz,R. Korab,Bernard C. Lesieutre,Jean Maeght,Daniel K. Molzahn,Thomas J. Overbye,Patrick Panciatici,Byungkwon Park,Jonathan Snodgrass,Ray D. Zimmerman +19 more
TL;DR: This IEEE PES Task Force report proposes a standardized AC-OPF mathematical formulation and the PGLib-OPf networks for benchmarking AC-opF algorithms and a motivating study demonstrates some limitations of the established network datasets in the context of benchmarking ASF algorithms.
Journal ArticleDOI
Application of the Moment-SOS Approach to Global Optimization of the OPF Problem
TL;DR: In this paper, a moment-sos (sum-of-squares) approach is proposed to find a global solution to the optimal power flow (OPF) problem at the cost of higher runtime.
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Application of the Moment-SOS Approach to Global Optimization of the OPF Problem
TL;DR: In this article, a moment-sos (sum-of-squares) approach is proposed to find a global solution to the optimal power flow (OPF) problem at the cost of higher runtime.
Journal ArticleDOI
Strong duality in Lasserre’s hierarchy for polynomial optimization
TL;DR: In this paper, it was shown that there is no duality gap between primal and dual SDP problems in Lasserre's hierarchy, provided one of the constraints in the description of set K is a ball constraint.