On the economic value and price-responsiveness of ramp-constrained storage
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Author(s) • •
Faghih, Ali
Roozbehani, Mardavij
Dahleh, Munther A.
Alternative Title
On the value and price-responsiveness of ramp-constrained storage
Date Issued
August 2013
Journal
Energy Conversion and Management
Publisher
Elsevier
Citation
Faghih, Ali, Mardavij Roozbehani, and Munther A. Dahleh. “On the Value and Price-Responsiveness of Ramp-Constrained Storage.” Energy Conversion and Management 76 (December 2013): 472–482.
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Author's final manuscript
Abstract
The primary concerns of this paper are twofold: understanding the value of storage in the presence of ramp constraints and exogenous energy prices, and understanding the implications of the associated optimal storage management policy for qualitative and quantitative characteristics of storage response to real-time prices. The optimal policy, along with the associated finite-horizon time-averaged value of storage, are analytically characterized in this paper. An analytical upper bound on the infinite-horizon time-averaged value of storage is also derived. This bound is valid for any achievable realization of prices when the support of the distribution is fixed, and highlights the dependence of the value of storage on ramp constraints and storage capacity. It is shown that while the value of storage is a non-decreasing function of price volatility, due to the finite ramp rate, the value of storage saturates quickly as the capacity increases, regardless of volatility. To study the implications of the optimal policy, computational experiments are presented that suggest optimal utilization of storage can, in expectation, induce a considerable amount of price elasticity near the average price. Then, a computational framework is presented for characterization of the behavior of storage as a function of price and the state of charge, which illustrates a steep buy/sell phase transition in the price-state plane.
MIT Department
MIT Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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DOI of Published Version
https://doi.org/10.1016/j.enconman.2013.07.072