The Reliability Value of Storage in a Volatile Environment
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Dahleh_The reliability.pdf
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Author(s)
ParandehGheibi, Ali
Roozbehani, Mardavij
Ozdaglar, Asuman E.
Dahleh, Munther A.
Date Issued
June 2012
Journal
Proceedings of the 2012 American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
ParandehGheibi, A.; Roozbehani, M.; Ozdaglar, A.; Dahleh, M.A., "The reliability value of storage in a volatile environment," American Control Conference (ACC), 2012, 2934-2939, 27-29 June 2012.
Version
Author's final manuscript
Abstract
This paper examines the value of storage in securing reliability of a system with uncertain supply and demand, and supply friction. The storage is frictionless as a supply source, but it cannot be filled up instantaneously. The focus is on application to an energy network in which the nominal supply and demand are assumed to match perfectly, while deviations from the nominal values are modeled as random shocks with stochastic arrivals. Due to friction, the random shocks cannot be tracked by the main supply sources. Storage, when available, can be used to compensate, fully or partially, for the surge in demand or sudden drop in supply. The problem of optimal utilization of storage with the objective of maximizing system reliability is formulated as minimization of the expected discounted cost of blackouts over an infinite horizon. It is shown that when the stage cost is linear in the size of the blackout, the optimal policy is myopic in the sense that all shocks will be compensated by storage up to the available level of storage. However, when the stage cost is strictly convex, it may be optimal to curtail some of the demand and allow a small blackout in the interest of maintaining a higher level of reserve, which may help avoid a large blackout in the future. The value of storage capacity in improving reliability, as well as the effects of the associated optimal policies under different stage costs on the probability distribution of blackouts are examined.
Description
Author's final manuscript: September 29, 2011
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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DOI of Published Version
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6315380
