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Abstract
This paper is concerned with assessing the contribution of grid-scale storage to generation capacity adequacy. Results are obtained for a utility-scale exemplar involving the Great Britain power system. All stores are assumed, for the purpose of capacity adequacy assessment, to be centrally controlled by the system operator, with the objective of minimising the Expected Energy Not Served over the peak demand season. The investigation is limited to stores that are sufficiently small such that discharge on one day does not restrict their ability to support adequacy on subsequent days. We argue that for such stores, the central control assumption does not imply loss of generality for the results.
Since it may be the case that stores must take power export decisions without the benefit of complete information about the state of the system, a methodology is presented for calculating bounds on the value of such information for supporting generation adequacy. A greedy strategy is proven to be optimal for the case where decisions can be made immediately after a generation shortfall event has occurred, regardless of the decision maker’s risk aversion. The adequacy contribution of multiple stores is examined, and algorithms for coordinating their responses are presented.
Since it may be the case that stores must take power export decisions without the benefit of complete information about the state of the system, a methodology is presented for calculating bounds on the value of such information for supporting generation adequacy. A greedy strategy is proven to be optimal for the case where decisions can be made immediately after a generation shortfall event has occurred, regardless of the decision maker’s risk aversion. The adequacy contribution of multiple stores is examined, and algorithms for coordinating their responses are presented.
Original language | English |
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Pages (from-to) | 69-81 |
Number of pages | 13 |
Journal | Sustainable Energy, Grids and Networks |
Volume | 12 |
Early online date | 16 Oct 2017 |
DOIs | |
Publication status | Published - Dec 2017 |
Projects
- 1 Finished
Profiles
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Chris Dent
- School of Mathematics - Personal Chair of Industrial Mathematics
Person: Academic: Research Active (Teaching)