TY - JOUR
T1 - A Mathematical Programming Solution for Automatic Generation of Synthetic Power Flow Cases
AU - Schweitzer, Eran
AU - Scaglione, Anna
N1 - Funding Information:
This work was supported in part by the Advanced Research Projects Agency-Energy (ARPA-E), and in part by the US Department of Energy under Award Number DE-AR0000714.
Funding Information:
Manuscript received March 18, 2018; revised June 3, 2018 and July 11, 2018; accepted July 31, 2018. Date of publication August 6, 2018; date of current version December 19, 2018. This work was supported in part by the Advanced Research Projects Agency–Energy (ARPA-E), and in part by the US Department of Energy under Award Number DE-AR0000714. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Paper no. TPWRS-00389-2018. (Corresponding author: Eran Schweitzer.) The authors are with the School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 USA (e-mail:, eran.schweitzer@asu.edu; anna.scaglione@asu.edu).
Publisher Copyright:
© 2018 IEEE.
PY - 2019/1
Y1 - 2019/1
N2 - A shortage of large power system data sets, as well as the frequent restrictions on sharing such models, have led to newfound interest in creating synthetic data that can be easily shared among researchers. This paper considers the problem of forming a power system test case from the constituent parts of realistic power grid samples. Starting from a topology, and samples of generation, load, and branches, we assemble systems while respecting the constraints imposed by a typical Optimal Power Flow problem. Expressed in this manner, the problem involves solving for permutations of the input data. Since permutations matrices are binary, the problem is linearized, allowing for a Mixed Integer Linear Problem formulation. The problem is further decomposed using the Alternating Direction Method of Multipliers as well as an Evolutionary Algorithm to facilitate scaling to larger system sizes. A post processing step is used to add shunt elements for reactive power planning. The resulting systems demonstrate statistically similar power flow behavior to reference systems. Finally, new analysis avenues, opened by synthesizing test cases according to the proposed method, are briefly introduced by creating fictitious systems with different topology models and examining how these affect power flow behavior.
AB - A shortage of large power system data sets, as well as the frequent restrictions on sharing such models, have led to newfound interest in creating synthetic data that can be easily shared among researchers. This paper considers the problem of forming a power system test case from the constituent parts of realistic power grid samples. Starting from a topology, and samples of generation, load, and branches, we assemble systems while respecting the constraints imposed by a typical Optimal Power Flow problem. Expressed in this manner, the problem involves solving for permutations of the input data. Since permutations matrices are binary, the problem is linearized, allowing for a Mixed Integer Linear Problem formulation. The problem is further decomposed using the Alternating Direction Method of Multipliers as well as an Evolutionary Algorithm to facilitate scaling to larger system sizes. A post processing step is used to add shunt elements for reactive power planning. The resulting systems demonstrate statistically similar power flow behavior to reference systems. Finally, new analysis avenues, opened by synthesizing test cases according to the proposed method, are briefly introduced by creating fictitious systems with different topology models and examining how these affect power flow behavior.
KW - Assignment problem
KW - linearized power flow
KW - mixed integer linear problem MILP
KW - synthetic test cases
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U2 - 10.1109/TPWRS.2018.2863266
DO - 10.1109/TPWRS.2018.2863266
M3 - Article
AN - SCOPUS:85051019238
SN - 0885-8950
VL - 34
SP - 729
EP - 741
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 1
M1 - 8425770
ER -