Robust Optimization of Storage Investment on Transmission Networks
File(s) IEEE-Rabih-Izudin-Bikas-2014-Storage.pdf (1.18 MB)
Accepted version
Author(s)
Jabr, RA
Dzafic, I
Pal, BC
Type
Journal Article
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.
Date Issued
2014-01-01
Citation
IEEE Transactions on Power Systems, 2014, 30 (1), pp.531-539
ISSN
0885-8950
Publisher
IEEE
Start Page
531
End Page
539
Journal / Book Title
IEEE Transactions on Power Systems
Volume
30
Issue
1
Copyright Statement
© 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Description
03.03.15 KB. Ok to add accepted version to spiral
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000346734000052&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
energy storage
power system planning
optimization methods
integer linear programming
Publication Status
Published
Coverage Spatial
USA
