Development of a Boundary Assigned Animal Migration Optimization algorithm and its application to optimal power flow study

被引：17
作者：
Dash, Stita Pragnya [1 ]
Subhashini, K. R. [1 ]
Chinta, Pridvi [1 ]
机构：
[1] Natl Inst Technol, Dept Elect Engn, Sundergarh 769008, Odisha, India
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2022年 / 200卷
关键词：
Animal Migration Optimization; Boundary Assigned Animal Migration; Optimization; Optimal power flow; Fuel cost; Voltage deviation; Active power loss; BEE COLONY ALGORITHM;
D O I：
10.1016/j.eswa.2022.116776
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new variant of Animal Migration Optimization (AMO) algorithm known as Boundary Assigned AnimalMigration Optimization (BA-AMO) has been conceptualized to study the optimal power flow problem relatingto IEEE bus systems with reference to fuel cost minimization of generators, total voltage deviation minimizationat buses and power loss minimization in lines. The proposed method is validated against few benchmarkfunctions and then applied to some case studies in the power system domain. The performance of the proposedtechnique is compared with quite a number of well established nature inspired meta-heuristic algorithms andsignificant improvement in results have been obtained. This clearly justifies the capability of the proposedstrategy to be an efficient competitor in optimization domain
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页数：17
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共 53 条
[11]   Solution of multi-objective optimal power flow using gravitational search algorithm [J].
Bhattacharya, A. ;
Roy, P. K. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2012, 6 (08) :751-763
[12]   Biogeography-Based Optimization for Different Economic Load Dispatch Problems [J].
Bhattacharya, Aniruddha ;
Chattopadhyay, Pranab Kumar .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (02) :1064-1077
[13]   Optimal power flow solutions using differential evolution algorithm integrated with effective constraint handling techniques [J].
Biswas, Partha P. ;
Suganthan, P. N. ;
Mallipeddi, R. ;
Amaratunga, Gehan A. J. .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 68 :81-100
[14]   Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission [J].
Bouchekara, H. R. E. H. ;
Chaib, A. E. ;
Abido, M. A. .
ELECTRICAL ENGINEERING, 2018, 100 (01) :151-165
[15]   Optimal power flow using an Improved Colliding Bodies Optimization algorithm [J].
Bouchekara, H. R. E. H. ;
Chaib, A. E. ;
Abido, M. A. ;
El-Sehiemy, R. A. .
APPLIED SOFT COMPUTING, 2016, 42 :119-131
[16]   Optimal power flow using the league championship algorithm: A case study of the Algerian power system [J].
Bouchekara, H. R. E. H. ;
Abido, M. A. ;
Chaib, A. E. ;
Mehasni, R. .
ENERGY CONVERSION AND MANAGEMENT, 2014, 87 :58-70
[17]   Optimal power flow using black-hole-based optimization approach [J].
Bouchekara, H. R. E. H. .
APPLIED SOFT COMPUTING, 2014, 24 :879-888
[18]   Optimal power flow using Teaching-Learning-Based Optimization technique [J].
Bouchekara, H. R. E. H. ;
Abido, M. A. ;
Boucherma, M. .
ELECTRIC POWER SYSTEMS RESEARCH, 2014, 114 :49-59
[19]   Optimal Power Flow Using Differential Search Algorithm [J].
Bouchekara, Houssem Rafik El-Hana ;
Abido, Mohamed Ali .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2014, 42 (15) :1683-1699
[20]   Swarm Intelligence Algorithms for Feature Selection: A Review [J].
Brezocnik, Lucija ;
Fister, Iztok, Jr. ;
Podgorelec, Vili .
APPLIED SCIENCES-BASEL, 2018, 8 (09)
123456