DocumentCode :
31766
Title :
Robust Optimization of Storage Investment on Transmission Networks
Author :
Jabr, Rabih A. ; Dzafic, Izudin ; Pal, B.C.
Author_Institution :
Dept. of Electr. & Comput. Eng., American Univ. of Beirut, Beirut, Lebanon
Volume :
30
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
531
Lastpage :
539
Abstract :
This paper discusses the need for the integration of storage systems on transmission networks having renewable sources, and presents a tool for energy storage planning. The tool employs robust optimization to minimize the investment in storage units that guarantee a feasible system operation, without load or renewable power curtailment, for all scenarios in the convex hull of a discrete uncertainty set; it is termed ROSION-Robust Optimization of Storage Investment On Networks. The computational engine in ROSION is a specific tailored implementation of a column-and-constraint generation algorithm for two-stage robust optimization problems, where a lower and an upper bound on the optimal objective function value are successively calculated until convergence. The lower bound is computed using mixed-integer linear programming and the upper bound via linear programming applied to a sequence of similar problems. ROSION is demonstrated for storage planning on the IEEE 14-bus and 118-bus networks, and the robustness of the designs is validated via Monte Carlo simulation.
Keywords :
IEEE standards; Monte Carlo methods; convergence; integer programming; investment; linear programming; power transmission planning; IEEE 118-bus networks; IEEE 14-bus networks; Monte Carlo simulation; ROSION; column-and-constraint generation algorithm; computational engine; convergence; convex hull; discrete uncertainty set; energy storage planning; lower bound; mixed-integer linear programming; optimal objective function value; renewable sources; robust optimization of storage investment on networks; two-stage robust optimization problems; upper bound; Discharges (electric); Energy storage; Investment; Optimization; Planning; Robustness; Vectors; Design optimization; energy storage; integer linear programming; optimization methods; power system planning;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2014.2326557
Filename :
6824272
Link To Document :
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