DocumentCode :
3577240
Title :
Optimization of economic load dispatch problems using biogeography based optimization technique
Author :
Singh, Jitendra ; Goyal, Sunil Kumar
Author_Institution :
Deptt. of Electr. Eng., Apex Inst. of Eng. & Technol., Jaipur, India
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
This paper presents a Biogeography Based Optimization (BBO) technique to solve the Economic Load Dispatch problem even as considered the generator and transmission constraints and satisfying it. Biogeography basically is the study of the geographical distribution of the biological organism. Biogeography based optimization is a comparatively new approach. Mathematical models of biogeography explain how an organism arises and how to migrate from one habitat to another habitat, or get died out. In BBO algorithm, solutions are sharing the good features between solutions that are immigration and emigration process. This algorithm looks for the overall optimum solution mostly through two steps - Migration and Mutation. Results are obtained on the different-different population size and different-different number of trials. The Results of the proposed method have been compared with results of IEEE 30-bus, 6 generator system and got the better quality of the obtained solution. This method is one of the important approaches for solving the Economic Load Dispatch problems under practical conditions.
Keywords :
optimisation; power generation dispatch; power generation economics; BBO algorithm; biogeography based optimization; economic load dispatch problem optimisation; emigration process; generator constraint satisfaction; geographical biological organism distribution; immigration process; mathematical model; transmission constraint satisfaction; Biogeography; Economics; Fuels; Generators; Optimization; Sociology; Statistics; BBO; ELD; HSI; IEEE 30-bus standard load flow test system; Migration; Mutation; SIVs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy Economics and Environment (ICEEE), 2015 International Conference on
Print_ISBN :
978-1-4673-7491-0
Type :
conf
DOI :
10.1109/EnergyEconomics.2015.7235067
Filename :
7235067
Link To Document :
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