Multi-objective electric distribution network reconfiguration solution using runner-root algorithm
被引:95
作者:
Thuan Thanh Nguyen
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机构:
HCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, Vietnam
Dong Polytech, 30 4 Str, Binh Duong, VietnamHCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, Vietnam
Thuan Thanh Nguyen
[1
,2
]
论文数: 引用数:
h-index:
机构:
Thang Trung Nguyen
[3
]
Anh Viet Truong
论文数: 0引用数: 0
h-index: 0
机构:
HCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, VietnamHCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, Vietnam
Anh Viet Truong
[1
]
Quyen Thi Nguyen
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机构:
Dong Polytech, 30 4 Str, Binh Duong, VietnamHCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, Vietnam
Quyen Thi Nguyen
[2
]
Tuan Anh Phung
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Hoa Noi Univ Sci & Technol, 1 Dai Co Viet Str, Hanoi, VietnamHCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, Vietnam
Tuan Anh Phung
[4
]
机构:
[1] HCMC Univ Technol & Educ, Fac Elect & Elect Engn, 1 Vo Ngan Str, Ho Chi Minh City, Vietnam
[2] Dong Polytech, 30 4 Str, Binh Duong, Vietnam
[3] Ton Duc Thang Univ, Fac Elect Elect Engn, Power Syst Optimizat Res Grp, 19 Nguyen Huu Tho Str, Ho Chi Minh City, Vietnam
[4] Hoa Noi Univ Sci & Technol, 1 Dai Co Viet Str, Hanoi, Vietnam
Network reconfiguration;
Runner-root;
Power loss reduction;
Load balancing;
Max-min method;
Multi-objective;
RADIAL-DISTRIBUTION SYSTEMS;
LOSS REDUCTION;
CUCKOO SEARCH;
OPTIMIZATION;
LOSSES;
D O I:
10.1016/j.asoc.2016.12.018
中图分类号:
TP18 [人工智能理论];
学科分类号:
140502 [人工智能];
摘要:
This paper presents a runner-root algorithm (RRA) for electric distribution network reconfiguration (NR) problem. The considered NR problem in this paper is to minimize real power loss, load balancing among the branches, load balancing among the feeders as well as number of switching operations and node voltage deviation using max-min method for selection of the final compromised solution. RRA is equipped with two explorative tools, which are random jumps with large steps and re-initialization strategy to escape from local optimal. Moreover, RRA is also equipped with an exploitative tool to search around the current best solution with large and small steps to ensure the obtained result of global optimization. The effectiveness of the applied RRA in both single- and multi-objective has been tested on 33-node and 70-node distribution network systems and the obtained test results have been compared to those from other methods in the literature. The simulation results show that the applied RRA can be an efficient method for network reconfiguration problems with single- and multi-objective. (C) 2016 Elsevier B.V. All rights reserved.
机构:
Univ Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, BrazilUniv Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, Brazil
Cebrian, Juan Carlos
;
Kagan, Nelson
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Univ Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, BrazilUniv Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, Brazil
机构:
Univ Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, BrazilUniv Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, Brazil
Cebrian, Juan Carlos
;
Kagan, Nelson
论文数: 0引用数: 0
h-index: 0
机构:
Univ Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, BrazilUniv Sao Paulo, Dept Elect Engn, Escola Politecn, BR-05508970 Sao Paulo, Brazil