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Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability

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@article{IJASEIT966,
   author = {Mohd Khairuzzaman Mohd Zamani and Ismail Musirin and Saiful Izwan Suliman and Muhammad Murtadha Othman and Mohd Fadhil Mohd Kamal},
   title = {Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {1},
   year = {2017},
   pages = {1--7},
   keywords = {particle swarm optimization technique; evolutionary programming; economic dispatch; optimization},
   abstract = {Economic dispatch is one of the important issues in power system operation and planning. Economic dispatch requires reliable technique to achieve minimal cost; otherwise, a non-optimal solution may cause non-economic electricity generation to the utility. Single area economic dispatch does not make complete electricity generation of the whole system on the electrical transmission network. Thus, multi-area economic dispatch implementation leads to complete consideration for power transmission system. This paper presents multi-area economic dispatch performance using swarm intelligence technique. In this study, swarm intelligence technique, namely the particle swarm optimization technique (PSO) is employed for solving multi-area economic dispatch problems. The algorithm is tested on a 2-area 48-bus power system with different case studies. Variation in active power loading in achieving an optimal solution is also considered in this study. Several trials were taken into consideration to assess the consistency of results. Comparative studies were performed with respect to evolutionary programming (EP) and revealed that PSO yields better results as compared to the EP.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=966},
   doi = {10.18517/ijaseit.7.1.966}
}

EndNote

%A Mohd Zamani, Mohd Khairuzzaman
%A Musirin, Ismail
%A Suliman, Saiful Izwan
%A Othman, Muhammad Murtadha
%A Mohd Kamal, Mohd Fadhil
%D 2017
%T Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability
%B 2017
%9 particle swarm optimization technique; evolutionary programming; economic dispatch; optimization
%! Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability
%K particle swarm optimization technique; evolutionary programming; economic dispatch; optimization
%X Economic dispatch is one of the important issues in power system operation and planning. Economic dispatch requires reliable technique to achieve minimal cost; otherwise, a non-optimal solution may cause non-economic electricity generation to the utility. Single area economic dispatch does not make complete electricity generation of the whole system on the electrical transmission network. Thus, multi-area economic dispatch implementation leads to complete consideration for power transmission system. This paper presents multi-area economic dispatch performance using swarm intelligence technique. In this study, swarm intelligence technique, namely the particle swarm optimization technique (PSO) is employed for solving multi-area economic dispatch problems. The algorithm is tested on a 2-area 48-bus power system with different case studies. Variation in active power loading in achieving an optimal solution is also considered in this study. Several trials were taken into consideration to assess the consistency of results. Comparative studies were performed with respect to evolutionary programming (EP) and revealed that PSO yields better results as compared to the EP.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=966
%R doi:10.18517/ijaseit.7.1.966
%J International Journal on Advanced Science, Engineering and Information Technology
%V 7
%N 1
%@ 2088-5334

IEEE

Mohd Khairuzzaman Mohd Zamani,Ismail Musirin,Saiful Izwan Suliman,Muhammad Murtadha Othman and Mohd Fadhil Mohd Kamal,"Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 1, pp. 1-7, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.1.966.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Mohd Zamani, Mohd Khairuzzaman
AU  - Musirin, Ismail
AU  - Suliman, Saiful Izwan
AU  - Othman, Muhammad Murtadha
AU  - Mohd Kamal, Mohd Fadhil
PY  - 2017
TI  - Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 1
Y2  - 2017
SP  - 1
EP  - 7
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - particle swarm optimization technique; evolutionary programming; economic dispatch; optimization
N2  - Economic dispatch is one of the important issues in power system operation and planning. Economic dispatch requires reliable technique to achieve minimal cost; otherwise, a non-optimal solution may cause non-economic electricity generation to the utility. Single area economic dispatch does not make complete electricity generation of the whole system on the electrical transmission network. Thus, multi-area economic dispatch implementation leads to complete consideration for power transmission system. This paper presents multi-area economic dispatch performance using swarm intelligence technique. In this study, swarm intelligence technique, namely the particle swarm optimization technique (PSO) is employed for solving multi-area economic dispatch problems. The algorithm is tested on a 2-area 48-bus power system with different case studies. Variation in active power loading in achieving an optimal solution is also considered in this study. Several trials were taken into consideration to assess the consistency of results. Comparative studies were performed with respect to evolutionary programming (EP) and revealed that PSO yields better results as compared to the EP.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=966
DO  - 10.18517/ijaseit.7.1.966

RefWorks

RT Journal Article
ID 966
A1 Mohd Zamani, Mohd Khairuzzaman
A1 Musirin, Ismail
A1 Suliman, Saiful Izwan
A1 Othman, Muhammad Murtadha
A1 Mohd Kamal, Mohd Fadhil
T1 Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 1
YR 2017
SP 1
OP 7
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 particle swarm optimization technique; evolutionary programming; economic dispatch; optimization
AB Economic dispatch is one of the important issues in power system operation and planning. Economic dispatch requires reliable technique to achieve minimal cost; otherwise, a non-optimal solution may cause non-economic electricity generation to the utility. Single area economic dispatch does not make complete electricity generation of the whole system on the electrical transmission network. Thus, multi-area economic dispatch implementation leads to complete consideration for power transmission system. This paper presents multi-area economic dispatch performance using swarm intelligence technique. In this study, swarm intelligence technique, namely the particle swarm optimization technique (PSO) is employed for solving multi-area economic dispatch problems. The algorithm is tested on a 2-area 48-bus power system with different case studies. Variation in active power loading in achieving an optimal solution is also considered in this study. Several trials were taken into consideration to assess the consistency of results. Comparative studies were performed with respect to evolutionary programming (EP) and revealed that PSO yields better results as compared to the EP.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=966
DO  - 10.18517/ijaseit.7.1.966