International Transaction of Electrical and Computer Engineers System
ISSN (Print): 2373-1273 ISSN (Online): 2373-1281 Website: http://www.sciepub.com/journal/iteces Editor-in-chief: Dr. Pushpendra Singh, Dr. Rajkumar Rajasekaran
Open Access
Journal Browser
Go
International Transaction of Electrical and Computer Engineers System. 2014, 2(2), 67-72
DOI: 10.12691/iteces-2-2-4
Open AccessArticle

A Novel Approach for Optimal Allocation of a Distributed Generator in a Radial Distribution Feeder for Loss Minimization and Tail End Node Voltage Improvement during Peak Load

Maruthi Prasanna. H. A.1, , Likith Kumar. M. V.2 and T. Ananthapadmanabha3

1Assistant Engineer (Ele), Karnataka Power Transmission Corporation Limited (KPTCL), Bangalore, India

2Research Scholar, Department of Electrical Engineering, The National Institute of Engineering, Mysore, India

3Professor, Department of Electrical Engineering, The National Institute of Engineering, Mysore, India

Pub. Date: March 14, 2014

Cite this paper:
Maruthi Prasanna. H. A., Likith Kumar. M. V. and T. Ananthapadmanabha. A Novel Approach for Optimal Allocation of a Distributed Generator in a Radial Distribution Feeder for Loss Minimization and Tail End Node Voltage Improvement during Peak Load. International Transaction of Electrical and Computer Engineers System. 2014; 2(2):67-72. doi: 10.12691/iteces-2-2-4

Abstract

This paper proposes a novel approach for optimal allocation of a distributed generator in a radial distribution feeder for loss minimization and tail end node voltage improvement during peak load. A multi objective optimization method is proposed to determine optimal allocation of a distributed generation (DG) unit in a radial distribution feeder. The DG allocation problem has been formulated as multi objective function which includes two objectives: viz Power Loss Reduction and Tail End Node Voltage Improvement with associated weights. The proposed methodology uses Genetic Algorithm to optimize the multi objective function. This method is tested on standard IEEE 33 bus radial distribution system using MATLAB 8.0. The results show that the proposed method yields significant reduction in line losses and considerable tail end node voltage improvement during peak load.

Keywords:
distribution system distributed generation TENVD Index PLR Index genetic algorithm

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  W. El-Khattam and M. M. A. Salma, “Distributed Generation technologies, definitions and benefits”, Electrical Power System Research. 71 (2004), 119-128.
 
[2]  T. Ackermann, G. Andersson and L. Soder, “Distributed generation: a definition”, Electrical Power System Research. 2001, 57 (3): 195-204.
 
[3]  P. Chiradeja and R. Ramkumar. “An approach to quantify the technical benefits of distributed generation”, IEEE Transaction on Energy Conversion. 2004, 19 (4): 764-773.
 
[4]  G. Pepermans et. al, “Distributed Generation: Definition, Benefits and Issues”, Working paper series, Energy Transport and Environment of K U Lewen Energy Institute, August 2003.
 
[5]  H. Khan and M.A. Choudhry, “Implementation of distributed generation algorithm for performance enhancement of distribution feeder under extreme load growth”, International Journal of Electrical Power and Energy Systems. 2010, 32 (9): 985-997.
 
[6]  D.Q. Hung, N. Mithulanathan and R.C. Bansal, “Multiple distributed generators placement in primary distribution networks for loss reduction”, IEEE Transactions on Industrial Electronics, Vol 60, Issue 4, 1700-1708, April 2013.
 
[7]  R.M. Kamel and B. Karmanshahi, “Optimal size and location of DGs for minimizing power losses in a primary distribution network”, Transaction on Computer Science and Electrical and Electronics Engineering. 2009, 16 (2): 137-144.
 
[8]  Mithulananthan, T. Oo, L. Van Phu, “Distributed generator placement in power distribution system using genetic algorithm to reduce losses”, Thammasat International Journal of Science and Technology, Vol. 9, No. 3, July-September 2004.
 
[9]  M. Sedighizadeh, and A. Rezazadeh, “Using Genetic Algorithm for Distributed Generation Allocation to Reduce Losses and Improve Voltage Profile”, World Academy of Science, Engineering and Technology, 37, 2008, 251-256.
 
[10]  I. Pisică, C. Bulac, and M. Eremia, “Optimal Distributed Generation Location and Sizing using Genetic Algorithms”, 15th International Conference on Intelligent System Applications to Power Systems, Curitiba, Brazil, 8-12 November 2009, 978-1-4244-5098-5/09 IEEE Digital Explore.
 
[11]  A.A. Abou El-Ela a, S.M. Allama, M.M. Shatlab, “Maximal optimal benefits of distributed generation using genetic algorithms”, Electric Power Systems Research, 80 (2010) 869–877. Ruifeng Shi, Can Cui, Kai Su, Zaharn Zain,
 
[12]  Dr.T.Ananthapadmanabha, Maruthi Prasanna.H.A, Veeresha.A.G, Likith Kumar. M. V, “A new simplified approach for optimum allocation of a distributed generation unit in the distribution network for voltage improvement and loss minimization”, International Journal of Electrical Engineering and Technology – IJEET, p. no 165-178, Volume 4, Issue 2, March-April (2013).
 
[13]  “Comparison Study of Two Meta-heuristic Algorithms with their Applications to Distributed Generation Planning”, ICSGCE 2011: 27-30 September 2011, Chengdu, China, Energy Procedia 12 (2011), 245-252.
 
[14]  “Genetic Algorithms for Optimization – Application in Controller Design Problems”. Andrey Popov. TU-Sofia. 2003.
 
[15]  Randy. L. Haupt and Sue Ellen Haupt, Practical Genetic Algorithms, 2nd ed., John Wiley & Sons, Inc., Publication, 2004.
 
[16]  M.H. Haque. “Efficient load flow method for distribution systems with radial or mesh configuration”, IET Proc. On Generation, Transmission and Distribution. 1996, 143 (1): 33-38.
 
[17]  KashemMA, Ganapathy V, JasmonGB, Buhari MI. A novel method for loss minimization in distribution networks. In: Proceedings of international conference on electric utility deregulation and restruc-turing and power technologies, 2000. p. 251-5.
 
[18]  Baran ME, Wu FF. Optimum sizing of capacitor placed on radial distribution systems. IEEE Trans PWRD 1989; 4: 735-43.
 
[19]  Naresh Acharya, Pukar Mahat, N. Mithulananthan, “An analytical approach for DG allocation in primary distribution network”, Electrical Power and Energy Systems 28 (2006) 669-678.
 
[20]  Wichit Krueasuk, Weerakorn Ongsakul, “Optimal Placement of Distributed Generation Using Particle Swarm Optimization”, In proceedings of the 2006 Australian Universities Power Engineering Conference (AUPEC), Melbourne, Victoria, Australia.
 
[21]  T. N. Shukla, S.P. Singh, K. B. Naik, “Allocation of optimal distributed generation using GA for minimum system losses in radial distribution networks”, International Journal of Engineering, Science and Technology, Vol. 2, No. 3, 2010, pp. 94-106.
 
[22]  K. Varesi, “Optimal Allocation of DG Units for Power Loss Reduction and Voltage Profile Improvement of Distribution Networks using PSO Algorithm”, World Academy of Science, Engineering and Technology, Vol: 60, 2011-12-26.