Optimal sizing and placement of distributed generation in a network system

With ever-increasing demand of electricity consumption and increasing open access particularly in restructured environment, transmission line congestion is quite frequent. For maximum benefit and mitigation of congestion, proper sizing and position of distributed generators are ardently necessary. This paper presents a simple method for optimal sizing and optimal placement of generators. A simple conventional iterative search technique along with Newton Raphson method of load flow study is implemented on modified IEEE 6 bus, IEEE 14 bus and IEEE 30 bus systems. The objective is to lower down both cost and loss very effectively. The paper also focuses on optimization of weighting factor, which balances the cost and the loss factors and helps to build up desired objectives with maximum potential benefit.

[1]  H. Sasaki,et al.  Multiobjective optimal generation dispatch based on probability security criteria , 1988 .

[2]  Kyu-Ho Kim,et al.  Dispersed generator placement using fuzzy-GA in distribution systems , 2002, IEEE Power Engineering Society Summer Meeting,.

[3]  Rafael Cossent,et al.  Improvements in current European network regulation to facilitate the integration of distributed generation , 2009 .

[4]  B. Mozafari,et al.  Optimal operation of distribution system with regard to distributed generation: a comparison of evolutionary methods , 2005, Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005..

[5]  Hans B. Puttgen,et al.  Distributed generation: Semantic hype or the dawn of a new era? , 2003 .

[6]  Nadarajah Mithulananthan,et al.  Optimal DG placement in deregulated electricity market , 2007 .

[7]  F. Pilo,et al.  A multiobjective evolutionary algorithm for the sizing and siting of distributed generation , 2005, IEEE Transactions on Power Systems.

[8]  K. Tomsovic,et al.  Placement of dispersed generation systems for reduced losses , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[9]  Y. Kishinevsky,et al.  Coming clean with fuel cells , 2003 .

[10]  Saifur Rahman,et al.  Green power: What is it and where can we find it? , 2003 .

[11]  G. Martin Renewable energy gets the "green" light in Chicago , 2003 .

[12]  Caisheng Wang,et al.  Analytical approaches for optimal placement of distributed generation sources in power systems , 2004 .

[13]  Hadi Saadat,et al.  Power System Analysis , 1998 .

[14]  P. Chiradeja,et al.  Benefit of Distributed Generation: A Line Loss Reduction Analysis , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[15]  W. Kling,et al.  Is the answer blowing in the wind , 2003 .

[16]  J. Steury,et al.  Distributed asset insight , 2004, IEEE Power and Energy Magazine.

[17]  Chanan Singh,et al.  Dispersed generation planning using improved Hereford ranch algorithm , 1998 .

[18]  N. S. Rau,et al.  Optimum location of resources in distributed planning , 1994 .

[19]  Yasuhiro Hayashi,et al.  Application of tabu search to optimal placement of distributed generators , 2001, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[20]  A. Keane,et al.  Optimal allocation of embedded generation on distribution networks , 2005, IEEE Transactions on Power Systems.

[21]  C.J. Andrews,et al.  Visions of a hydrogen future , 2004, IEEE Power and Energy Magazine.

[22]  Swapan Kumar Goswami,et al.  Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction, and voltage improvement including voltage rise issue , 2010 .

[23]  N. Mithulananthan,et al.  Distributed Generator Placement in Power Distribution System Using Genetic Algorithm to Reduce Losses , 2004 .