Abstract
In energy industry, generating the correct amount of electrical power is crucial. Economic load dispatch is used to compute the necessary amount of power among the generators. However, each generator in a system is limited by its physical properties that will limit its maximum potential. This prohibited zone divides the actual operation limits of a particular generator into several subdivisions. This paper proposes Differential Evolution Immunized Ant Colony Optimization (DEAINT) technique in solving economic dispatch by considering prohibited operating zones. The optimization process was conducted on IEEE 30-Bus Reliable Test System (RTS). Verification of DEIANT technique was performed by comparing it with Evolutionary Programming (EP) and Ant Colony Optimization (ACO) technique. The comparative studies indicate that DEIANT outperformed EP and ACO in terms of achieving lower operating cost and power loss.
Original language | English |
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Pages | 455-460 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 01 Jan 2014 |
Event | 2014 IEEE 8th International Power Engineering and Optimization Conference, PEOCO 2014 - Langkawi, Malaysia Duration: 24 Mar 2014 → 25 Mar 2014 |
Other
Other | 2014 IEEE 8th International Power Engineering and Optimization Conference, PEOCO 2014 |
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Country | Malaysia |
City | Langkawi |
Period | 24/03/14 → 25/03/14 |
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All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Fuel Technology
Cite this
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Differential Evolution Immunized Ant Colony Optimization Technique (DEIANT) in solving economic dispatch by considering prohibited operating zones. / Rahmat, Nur Azzammudin; Musirin, I.; Abidin, A. F.
2014. 455-460 Paper presented at 2014 IEEE 8th International Power Engineering and Optimization Conference, PEOCO 2014, Langkawi, Malaysia.Research output: Contribution to conference › Paper
TY - CONF
T1 - Differential Evolution Immunized Ant Colony Optimization Technique (DEIANT) in solving economic dispatch by considering prohibited operating zones
AU - Rahmat, Nur Azzammudin
AU - Musirin, I.
AU - Abidin, A. F.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In energy industry, generating the correct amount of electrical power is crucial. Economic load dispatch is used to compute the necessary amount of power among the generators. However, each generator in a system is limited by its physical properties that will limit its maximum potential. This prohibited zone divides the actual operation limits of a particular generator into several subdivisions. This paper proposes Differential Evolution Immunized Ant Colony Optimization (DEAINT) technique in solving economic dispatch by considering prohibited operating zones. The optimization process was conducted on IEEE 30-Bus Reliable Test System (RTS). Verification of DEIANT technique was performed by comparing it with Evolutionary Programming (EP) and Ant Colony Optimization (ACO) technique. The comparative studies indicate that DEIANT outperformed EP and ACO in terms of achieving lower operating cost and power loss.
AB - In energy industry, generating the correct amount of electrical power is crucial. Economic load dispatch is used to compute the necessary amount of power among the generators. However, each generator in a system is limited by its physical properties that will limit its maximum potential. This prohibited zone divides the actual operation limits of a particular generator into several subdivisions. This paper proposes Differential Evolution Immunized Ant Colony Optimization (DEAINT) technique in solving economic dispatch by considering prohibited operating zones. The optimization process was conducted on IEEE 30-Bus Reliable Test System (RTS). Verification of DEIANT technique was performed by comparing it with Evolutionary Programming (EP) and Ant Colony Optimization (ACO) technique. The comparative studies indicate that DEIANT outperformed EP and ACO in terms of achieving lower operating cost and power loss.
UR - http://www.scopus.com/inward/record.url?scp=84901329712&partnerID=8YFLogxK
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U2 - 10.1109/PEOCO.2014.6814472
DO - 10.1109/PEOCO.2014.6814472
M3 - Paper
AN - SCOPUS:84901329712
SP - 455
EP - 460
ER -