In restructured Electrical Power network the transmission line gets congested by multiple transactions over the line. In such scenario the operator must analyze optimum value of ATC for said transaction. When the transactions between the transmission lines are carried out for a specific destination node/source node pair in a system, the Independent System operator (ISO) must calculate the available transfer capacity (ATC) of that node/source pair. This paper proposes a comprehensive approach to find out the optimized value of ATC for given transaction using Genetic Algorithm. With the help of Genetic algorithm transactions between pair of node can be generated randomly and can be used to calculate optimized value of ATC for each transaction. With the help of this method ISO can declare the value of transacted power from source to destination bus for optimum value of ATC. The objective function is to maximize the power flow capability of transmission line with safest transaction. The solution to the optimization problem gives the amount of accepted requests and available capability of transmission line that could result in a safe and reliable transmission system. The proposed method is applied to an IEEE 30 bus test system.
| Published in |
International Journal of Energy and Power Engineering (Volume 4, Issue 5-1)
This article belongs to the Special Issue Energy Systems and Developments |
| DOI | 10.11648/j.ijepe.s.2015040501.17 |
| Page(s) | 43-47 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Available Transfer Capability (ATC), OASIS, ISO, Open Access, PTCDF, Genetic Algorithm
| [1] | A.R Abhayankar and prof.S.A.Khaparde, “Introduction to deregulation in power industry” |
| [2] | G.C.Ejebe, j.Tong, J.G.Waight, J.G.Frame, X. Wang and W.F. Tinney , “Available transfer capability Calculations” PE-321-PWRS-0-10-97, IEEE [3] Mark H. Gravener, Chika Nwankpa, Tai-sim Yeoh , ATC computational issues, Proceedings of 32nd Hawali International Conference on system Sciences-1999 |
| [3] | R.D.Christie, B.F.Wollenberg and I.Wangensteen, “Transmission Management in deregulated environment, Proceeding of IEEE, 88, No.2, pp. 449-451, Feb 2000. |
| [4] | G. Hamoud, “Assessment of Available Transfer capability of transmission system”, IEEE transaction on Power system vol-15, No-1, pp. 27-32, February, 2000. |
| [5] | Mohamed Shaaban, Yaxin Ni and Felix F.Wu, “Transfer Capability Computation in Deregulated Power systems”, Proceddings of 32nd Hawali International Conference on system Sciences-2000. |
| [6] | Sarika Kushalani, S.A Khaparde and S.A. Soman, “Congestion management in the Emerging Energy Market Structure” , Cigre Regional Meeting on Bulk Power Transmission System Integration in Developing countries, pp. VII-16 to 24 New Delhi Nov.2001 |
| [7] | Dr Sanjay Gupta Senior Consultant Energy and Utilities Group Infosys Technologies Limited Bangalore , India , “Formation of Independent System Operator (ISO)” , India |
| [8] | Abhijit chakravarti and Sunita Haldar, “Power system Analysis” |
| [9] | Ashwani Kumar and S. C. Srivastav , “Power Transaction Allocation in a Deregulated Market using AC Power Transfer Distribution Factors” , Cigre Regional Meeting on Bulk Power Transmission System Integration in Developing countries, pp. VIII-9 to 17 New Delhi Nov.2001 |
| [10] | N.P. Padhy, “Artificial Intelligence and Intelligent Systems”, Oxford University Press, 2005 |
| [11] | Kalyanmoy Deb, “Multiobjective Optimization Using Evolutionary Algorithms”, John Wiley & Sons, 2013 |
| [12] | E. Zitzler, K. Deb, and L. Thiele, “Comparison of multiobjective evolu-tionary algorithms: Empirical results,”Evol. Comput., vol. 8, no. 2, pp. 173–195, Summer 2000 |
| [13] | Biman Chakraborty, Probal Chaudhuri, “On The Use of Genetic Algorithm with Elitism in Robust and Nonparametric Multivariate Analysis”, Austrian Journal of statistic, Volume 32 (2003), Number 1&2, pp. 13–2. |
APA Style
Makwana Umesh L., Joshi S. K. (2015). Optimal Evaluation of Available Transfer Capability of Transmission Line Using Bio-inspired Algorithm for Multiple Transactions in Deregulated Electrical Power Network. International Journal of Energy and Power Engineering, 4(5-1), 43-47. https://doi.org/10.11648/j.ijepe.s.2015040501.17
ACS Style
Makwana Umesh L.; Joshi S. K. Optimal Evaluation of Available Transfer Capability of Transmission Line Using Bio-inspired Algorithm for Multiple Transactions in Deregulated Electrical Power Network. Int. J. Energy Power Eng. 2015, 4(5-1), 43-47. doi: 10.11648/j.ijepe.s.2015040501.17
AMA Style
Makwana Umesh L., Joshi S. K. Optimal Evaluation of Available Transfer Capability of Transmission Line Using Bio-inspired Algorithm for Multiple Transactions in Deregulated Electrical Power Network. Int J Energy Power Eng. 2015;4(5-1):43-47. doi: 10.11648/j.ijepe.s.2015040501.17
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ijepe.s.2015040501.17,
author = {Makwana Umesh L. and Joshi S. K.},
title = {Optimal Evaluation of Available Transfer Capability of Transmission Line Using Bio-inspired Algorithm for Multiple Transactions in Deregulated Electrical Power Network},
journal = {International Journal of Energy and Power Engineering},
volume = {4},
number = {5-1},
pages = {43-47},
doi = {10.11648/j.ijepe.s.2015040501.17},
url = {https://doi.org/10.11648/j.ijepe.s.2015040501.17},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.s.2015040501.17},
abstract = {In restructured Electrical Power network the transmission line gets congested by multiple transactions over the line. In such scenario the operator must analyze optimum value of ATC for said transaction. When the transactions between the transmission lines are carried out for a specific destination node/source node pair in a system, the Independent System operator (ISO) must calculate the available transfer capacity (ATC) of that node/source pair. This paper proposes a comprehensive approach to find out the optimized value of ATC for given transaction using Genetic Algorithm. With the help of Genetic algorithm transactions between pair of node can be generated randomly and can be used to calculate optimized value of ATC for each transaction. With the help of this method ISO can declare the value of transacted power from source to destination bus for optimum value of ATC. The objective function is to maximize the power flow capability of transmission line with safest transaction. The solution to the optimization problem gives the amount of accepted requests and available capability of transmission line that could result in a safe and reliable transmission system. The proposed method is applied to an IEEE 30 bus test system.},
year = {2015}
}
TY - JOUR T1 - Optimal Evaluation of Available Transfer Capability of Transmission Line Using Bio-inspired Algorithm for Multiple Transactions in Deregulated Electrical Power Network AU - Makwana Umesh L. AU - Joshi S. K. Y1 - 2015/09/02 PY - 2015 N1 - https://doi.org/10.11648/j.ijepe.s.2015040501.17 DO - 10.11648/j.ijepe.s.2015040501.17 T2 - International Journal of Energy and Power Engineering JF - International Journal of Energy and Power Engineering JO - International Journal of Energy and Power Engineering SP - 43 EP - 47 PB - Science Publishing Group SN - 2326-960X UR - https://doi.org/10.11648/j.ijepe.s.2015040501.17 AB - In restructured Electrical Power network the transmission line gets congested by multiple transactions over the line. In such scenario the operator must analyze optimum value of ATC for said transaction. When the transactions between the transmission lines are carried out for a specific destination node/source node pair in a system, the Independent System operator (ISO) must calculate the available transfer capacity (ATC) of that node/source pair. This paper proposes a comprehensive approach to find out the optimized value of ATC for given transaction using Genetic Algorithm. With the help of Genetic algorithm transactions between pair of node can be generated randomly and can be used to calculate optimized value of ATC for each transaction. With the help of this method ISO can declare the value of transacted power from source to destination bus for optimum value of ATC. The objective function is to maximize the power flow capability of transmission line with safest transaction. The solution to the optimization problem gives the amount of accepted requests and available capability of transmission line that could result in a safe and reliable transmission system. The proposed method is applied to an IEEE 30 bus test system. VL - 4 IS - 5-1 ER -
Email: