TY - JOUR
T1 - Distributed storage placement policy for minimizing frequency deviations
T2 - A combinatorial optimization approach based on enhanced cross-entropy method
AU - Machlev, R.
AU - Chowdhury, N. R.
AU - Belikov, J.
AU - Levron, Y.
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/1
Y1 - 2022/1
N2 - The paper addresses the well-known challenge of allocating storage units within the grid to minimize frequency deviations during transients. The current research is mainly motivated by a sequence of recent works that focus on location of inertia and storage units, considering the limitations of the transmission network, and its spatial effects. One possible drawback of these algorithms is their numerical complexity. To address this gap, this paper studies the storage distribution problem using the general framework of combinatorial optimization, and proposes algorithms to solve it. Among them, one solution is based on exhaustive search, while the others strongly rely on the cross-entropy method. We show that the latter is especially suitable for this application, since it can efficiently solve high-dimensional combinatorial optimization problems. Since the CE method may converge to sub-optimal solutions if the number of storage units increases significantly, this paper also proposes an enhanced CE method which solves the distribution problem considering the assumption that the locations of potential transients are known. In this regard, a key result is that the enhanced CE method convergences faster to the optimal solution and significantly reduces the number of computations.
AB - The paper addresses the well-known challenge of allocating storage units within the grid to minimize frequency deviations during transients. The current research is mainly motivated by a sequence of recent works that focus on location of inertia and storage units, considering the limitations of the transmission network, and its spatial effects. One possible drawback of these algorithms is their numerical complexity. To address this gap, this paper studies the storage distribution problem using the general framework of combinatorial optimization, and proposes algorithms to solve it. Among them, one solution is based on exhaustive search, while the others strongly rely on the cross-entropy method. We show that the latter is especially suitable for this application, since it can efficiently solve high-dimensional combinatorial optimization problems. Since the CE method may converge to sub-optimal solutions if the number of storage units increases significantly, this paper also proposes an enhanced CE method which solves the distribution problem considering the assumption that the locations of potential transients are known. In this regard, a key result is that the enhanced CE method convergences faster to the optimal solution and significantly reduces the number of computations.
KW - Combinatorial optimization
KW - Cross-Entropy method
KW - Distributed energy storage
KW - Droop control
KW - Frequency stability
KW - Grid supporting inverters
UR - http://www.scopus.com/inward/record.url?scp=85111043303&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2021.107332
DO - 10.1016/j.ijepes.2021.107332
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AN - SCOPUS:85111043303
SN - 0142-0615
VL - 134
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 107332
ER -