ONLINE MONITORING OF MAXIMUM ALLOWABLE LOAD AT DIFFERENT BUSES USING ABC ALGORITHM AND ARTIFICIAL NEURAL NETWORK
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Mar 30, 2020
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Abstract
The power demand is increasing day by day. It is
essential to determine the maximum load that can be imposed at
each load bus. The maximum allowable load is the maximum
load that can be applied at different load buses without violating
the voltage at these buses. In this paper, the maximum
loadability limit that can be imposed at different buses of power
system is determined by using Artificial Bee Colony algorithm
(ABC). The loadability limit is calculated with and without line
outages. The results obtained using the proposed hybrid
algorithm is compared with the results obtained by existing
algorithms. Even though the algorithm provides better results
than the existing algorithms, it cannot be applied for on line
application. For online monitoring and loading, Artificial
Neural Network (ANN) is used. The trained ANN is used for the
online monitoring of the buses. The proposed work is validated
by testing on IEEE30 bus system.
essential to determine the maximum load that can be imposed at
each load bus. The maximum allowable load is the maximum
load that can be applied at different load buses without violating
the voltage at these buses. In this paper, the maximum
loadability limit that can be imposed at different buses of power
system is determined by using Artificial Bee Colony algorithm
(ABC). The loadability limit is calculated with and without line
outages. The results obtained using the proposed hybrid
algorithm is compared with the results obtained by existing
algorithms. Even though the algorithm provides better results
than the existing algorithms, it cannot be applied for on line
application. For online monitoring and loading, Artificial
Neural Network (ANN) is used. The trained ANN is used for the
online monitoring of the buses. The proposed work is validated
by testing on IEEE30 bus system.
Article Details
References
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[2] Irisarri GD, Wang X, Tong J, Mokhtari S, Maximum loadability of power systems using interior point non-linear optimization methods. , IEEE Trans Power Syst 1997;12(1):162–72
[3] M. Ganesh Kumari, K. Gnanambal, Analysis and comparison PSO and DE based on optimized DVR for mitigation of short duration voltage variation., Journal of Eleectrical Engineering volume 18/2018 – Edition 2.
[4] Amgad A EL-Dib, Hosam KM Youssef, EL-Metwally MM, Osrnan Z, Maximum loadability of power systems using hybrid particle swarm ptimization. , Electr Power Syst Res 2006;76:485–92.
[5] Shunmugalatha A, Mary Raja Slochanal S, Maximum loadability of a power system using multi agent-based hybrid particle swarm optimization. , Electric Power Compon Syst 2008;36:575–86.
[6] K. Gnanambal, C.K. Babulal, Maximum loadability limit of power system using hybrid differential evolution with particle swarm optimization , Electrical Power and Energy Systems 43 (2012) 150–155
[7] D. Karaboga, B. Basturk, On the performance of artificial bee colony (ABC) algorithm , Applied Soft Computing 8 (2008) 687 – 697
[8] E. Bonabeau, M. Dorigo, G. Theraulaz, Swarm Intelligence , From Natural to Artificial Systems, New York, NY: Oxford University Press, 1999
[9] D. Karaboga , B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , J Glob Optim (2007) 39:459– 471
[10] Dervis Karboga, Bahriye Akey, A modified Artificial Colony (ABC) algorithm for constrained optimization problems, Applied Soft Computing 11 (2011) 3021 – 3031, Applied Soft Computing 11 (2011) 3021 – 3031
[11] Wei-feng Gao, Ling-ling Haung, Jue Wang, San-yang Liu, Chuan-dong Qin, Enhanced artificial bee colony algorithm through differential evaluation , Applied Soft Computing 48 (2016) 137 – 150
[12] Laurene.V.Fausette, Fundamentals of Neural Network: Architectures, Algorithms, and Applications Prentice Hall,1993., Architectures, Algorithms, and Applications Prentice Hall,1993
[13] Natick MA, Simulink User’s Guide , The Mathworks
[14] Howard Demuth Mark Beale, Neural Network Toolbox , For Use with MATLAB®, users guide.
[2] Irisarri GD, Wang X, Tong J, Mokhtari S, Maximum loadability of power systems using interior point non-linear optimization methods. , IEEE Trans Power Syst 1997;12(1):162–72
[3] M. Ganesh Kumari, K. Gnanambal, Analysis and comparison PSO and DE based on optimized DVR for mitigation of short duration voltage variation., Journal of Eleectrical Engineering volume 18/2018 – Edition 2.
[4] Amgad A EL-Dib, Hosam KM Youssef, EL-Metwally MM, Osrnan Z, Maximum loadability of power systems using hybrid particle swarm ptimization. , Electr Power Syst Res 2006;76:485–92.
[5] Shunmugalatha A, Mary Raja Slochanal S, Maximum loadability of a power system using multi agent-based hybrid particle swarm optimization. , Electric Power Compon Syst 2008;36:575–86.
[6] K. Gnanambal, C.K. Babulal, Maximum loadability limit of power system using hybrid differential evolution with particle swarm optimization , Electrical Power and Energy Systems 43 (2012) 150–155
[7] D. Karaboga, B. Basturk, On the performance of artificial bee colony (ABC) algorithm , Applied Soft Computing 8 (2008) 687 – 697
[8] E. Bonabeau, M. Dorigo, G. Theraulaz, Swarm Intelligence , From Natural to Artificial Systems, New York, NY: Oxford University Press, 1999
[9] D. Karaboga , B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , J Glob Optim (2007) 39:459– 471
[10] Dervis Karboga, Bahriye Akey, A modified Artificial Colony (ABC) algorithm for constrained optimization problems, Applied Soft Computing 11 (2011) 3021 – 3031, Applied Soft Computing 11 (2011) 3021 – 3031
[11] Wei-feng Gao, Ling-ling Haung, Jue Wang, San-yang Liu, Chuan-dong Qin, Enhanced artificial bee colony algorithm through differential evaluation , Applied Soft Computing 48 (2016) 137 – 150
[12] Laurene.V.Fausette, Fundamentals of Neural Network: Architectures, Algorithms, and Applications Prentice Hall,1993., Architectures, Algorithms, and Applications Prentice Hall,1993
[13] Natick MA, Simulink User’s Guide , The Mathworks
[14] Howard Demuth Mark Beale, Neural Network Toolbox , For Use with MATLAB®, users guide.