TY - GEN
T1 - Maximizing hosting capacity of distributed generation by network reconfiguration in distribution system
AU - Takenobu, Yuji
AU - Kawano, Shunsuke
AU - Hayashi, Yasuhiro
AU - Yasuda, Norihito
AU - Minato, Shin Ichi
N1 - Funding Information:
This research was supported by the Japan Science and Technology Agency (JST), CREST.
Publisher Copyright:
© 2016 Power Systems Computation Conference.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/8/10
Y1 - 2016/8/10
N2 - The maximization of distributed generation (DG) hosting capacity that takes into account network configuration is a complex, non-linear combinatorial optimization problem. The search space of the configurations becomes massively large in practical-size networks with several hundreds of switches. For this reason, no existing method can handle such large-scale networks. In this paper, we propose a novel exact solution method. Our method consists of two stages. In the first stage, the method divides the entire problem into a set of small subproblems. In the second stage, it converts all subproblems into a compressed data structure called a zero-suppressed binary decision diagram (ZDD), which expresses the combinatorial sets compactly. The proposed method avoids any combinatorial explosion by using the ZDD to enable operations of the weighted combinatorial item sets. We conducted experiments on a large-scale network with 235 switches. As a result, our method obtained the global optimal solution in 49 hours.
AB - The maximization of distributed generation (DG) hosting capacity that takes into account network configuration is a complex, non-linear combinatorial optimization problem. The search space of the configurations becomes massively large in practical-size networks with several hundreds of switches. For this reason, no existing method can handle such large-scale networks. In this paper, we propose a novel exact solution method. Our method consists of two stages. In the first stage, the method divides the entire problem into a set of small subproblems. In the second stage, it converts all subproblems into a compressed data structure called a zero-suppressed binary decision diagram (ZDD), which expresses the combinatorial sets compactly. The proposed method avoids any combinatorial explosion by using the ZDD to enable operations of the weighted combinatorial item sets. We conducted experiments on a large-scale network with 235 switches. As a result, our method obtained the global optimal solution in 49 hours.
KW - Distributed generation
KW - network reconfiguration
KW - second-order cone programming (SOCP)
KW - zero-suppressed binary decision diagram (ZDD)
UR - http://www.scopus.com/inward/record.url?scp=84986563703&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84986563703&partnerID=8YFLogxK
U2 - 10.1109/PSCC.2016.7540965
DO - 10.1109/PSCC.2016.7540965
M3 - Conference contribution
AN - SCOPUS:84986563703
T3 - 19th Power Systems Computation Conference, PSCC 2016
BT - 19th Power Systems Computation Conference, PSCC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th Power Systems Computation Conference, PSCC 2016
Y2 - 20 June 2016 through 24 June 2016
ER -