Quadratic Migration of Biogeography based Optimization for Short Term Hydrothermal Scheduling

被引:0
作者
Kumar, Goutham N. [1 ]
Sharma, Veena [1 ]
Naresh, K. [1 ]
Singhal, Prateek. Kr. [1 ]
机构
[1] NIT Hamirpur, Dept Elect Engn, Hamirpur 177005, HP, India
来源
2014 FIRST INTERNATIONAL CONFERENCE ON NETWORKS & SOFT COMPUTING (ICNSC) | 2014年
关键词
biogeography based optimization; quadratic migration model; short term hydrothermal scheduling; cascaded reservoir plants;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an optimal dispatch of hydro and thermal power generation in a short term hydrothermal system which is solved by quadratic migration model of biogeography based optimization (QBBO). A mathematical formulation of quadratic model is delineated how species survive from one habitat to another habitat and gets annihilated. The performance ability of the proposed QBBO approach is applied to solve complex short term hydrothermal scheduling (STHTS) optimization problem. The STHTS problem has been represented as a nonconvex, nonlinear combinatorial problem considering diverse constraints. The effectiveness of QBBO approach is examined on Our cascaded hydro plants and an equivalent thermal plant. The simulation results obtained with QBBO approach is compared with reported methods in literature. It is observed from the simulation studies that the obtained results using QBBO approach is better in terms of minimum total production cost and execution time as compared to other published methods recently.
引用
收藏
页码:400 / 405
页数:6
相关论文
共 11 条
[1]  
[Anonymous], 2013, Power generation, operation, and control
[2]   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
[3]  
Camargo M. P., 2014, SWARM EVOLU IN PRESS
[4]   HYDROELECTRIC GENERATION SCHEDULING WITH AN EFFECTIVE DIFFERENTIAL DYNAMIC-PROGRAMMING ALGORITHM [J].
CHANG, SC ;
CHEN, CH ;
FONG, IK ;
LUH, PB .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1990, 5 (03) :737-743
[5]  
Datta S, 2012, INT C EMERG TRENDS E, P38, DOI 10.1109/ICETEEEM.2012.6494441
[6]   An analysis of the equilibrium of migration models for biogeography-based optimization [J].
Ma, Haiping .
INFORMATION SCIENCES, 2010, 180 (18) :3444-3464
[7]   Two-phase neural network based solution technique for short term hydrothermal scheduling [J].
Naresh, R ;
Sharma, J .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1999, 146 (06) :657-663
[8]  
Orero S. O., 1988, IEEE T POWER SYST, V13, P201
[9]   Optimal short-term hydro-thermal scheduling using quasi-oppositional teaching learning based optimization [J].
Roy, Provas Kumar ;
Sur, Aditi ;
Pradhan, Dinesh Kumar .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2013, 26 (10) :2516-2524
[10]   Biogeography-Based Optimization [J].
Simon, Dan .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2008, 12 (06) :702-713