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Online Modified Greedy Algorithm for Storage Control Under Uncertainty

delete2016-05-01
delete47
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OA
AI
J
Junjie Qin
Y
Yinlam Chow
J
Jiyan Yang *
R
Ram Rajagopal *
DOI:10.1109/TPWRS.2015.2440355delete
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摘要

摘要

En 中文
This paper studies the general problem of operating energy storage under uncertainty. Two fundamental sources of uncertainty are considered, namely the uncertainty in the unexpected fluctuation of the net demand process and the uncertainty in the locational marginal prices. We propose a very simple algorithm termed Online Modified Greedy (OMG) algorithm for this problem. A stylized analysis for the algorithm is performed, which shows that comparing to the optimal cost of the corresponding stochastic control problem, the sub-optimality of OMG is controlled by an easily computable bound. This suggests that, albeit simple, OMG is guaranteed to have good performance in cases when the bound is small. Meanwhile, OMG together with the sub-optimality bound can be used to provide a lower bound for the optimal cost. Such a lower bound can be valuable in evaluating other heuristic algorithms. For the latter cases, a semidefinite program is derived to minimize the sub-optimality bound of OMG. Numerical experiments are conducted to verify our theoretical analysis and to demonstrate the use of the algorithm.
Keyword:
Approximation algorithms
energy storage operation
online algorithms
renewable integration
stochastic control
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期刊

IEEE Transactions on Power Systems 封面图
IEEE Transactions on Power Systems
IF:
7.2
论文数:
1.1W
被引数:
5.0W

机构

S
Stanford University
学者数:
9.6W
论文数: 8.2W
被引数: 17.0W
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