Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique

Authors

  • Shreya Mahajan B.E. degree in Electrical & Electron- ics Engineering from University Institute of Engineering and Technol- ogy, Panjab University, Chandigarh, India
  • Dr. Shelly Vadhera Department of Electrical Engineering, NIT Kurukshetra, Haryana, India

DOI:

https://doi.org/10.13052/dgaej2156-3306.3322

Abstract

The demand of electricity is soaring rapidly. Distributed genera-
tion (DG) is one of the most suitable alternatives to fulfill this swelling
demand of energy. DG is a small scale generation which is directly in-
stalled in the distribution network or at load centre. Optimal allocation
of DG is a vital factor in improving the voltage profile of the system and
in reduction of total power losses. In this article, a detailed study of three
different methods for DG allocation and sizing has been discussed. The
first method is based on Newton Raphson load flow based technique to
deduce the optimal location of DG in two different IEEE bus systems in
MATLAB software. The next methodology is based on particle swarm
optimization (PSO) technique where a multi-objective function is being
minimized. The objective function has been modified and PSO has been
implemented to attain optimal size and location of DG unit. The third
method considered is based on human opinion dynamics evolution-
ary multi-objective optimization technique which is used to obtain the
best possible size and location of DG unit in IEEE 14 and IEEE 30 bus
systems. The human opinion dynamics method shows superiority in
minimizing the size and location muti-objective function, over the other
methods considered herein.

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Author Biographies

Shreya Mahajan, B.E. degree in Electrical & Electron- ics Engineering from University Institute of Engineering and Technol- ogy, Panjab University, Chandigarh, India

Shreya Mahajan obtained her B.E. degree in Electrical & Electron-
ics Engineering from University Institute of Engineering and Technol-
ogy, Panjab University, Chandigarh, India in 2014. She is pursuing
M. Tech degree in Power System Engineering from NIT Kurukshetra,
Haryana, India. Her areas of interest are power systems, renewable
energy, distributed generation, artificial intelligence techniques. e-mail:
123shreya.m@gmail.com

Dr. Shelly Vadhera, Department of Electrical Engineering, NIT Kurukshetra, Haryana, India

Dr. Shelly Vadhera is currently working as Associate Professor in
the department of Electrical Engineering, NIT Kurukshetra, Haryana,
India. Her areas of interest are renewable energy, power systems, electric
machines. e-mail: shelly_vadhera@rediffmail.com

References

L. Lai and T.F. Chan, Distributed generation: Induction and permanent magnet

generators, Wiley, 2007.

T. Ackermann, G. Andersson, and L. Soder, "Distributed generation: a definition,"

Electric Power System Research, vol. 57, pp. 195-204, 2001.

W. El-Khattam and M.M.A. Salama, "Distribution generation technologies, defini-tions and benefits," Electric Power Systems Research, vol. 71, pp. 119-128, 2004.

A. Kazemi and M. Sagedhi, "A load flow based method for optimal1ocation of dis-

persed generation units," Power Systems Conference and Exposition, 2009.

N. Acharya, P. Mahat, and N. Mithu1ananthan, "An analytical approach for DG

allocation in primary distribution network," Electric Power Systems Research, vol.

, pp. 669--678, 2006.

P. Chidareja and R. Rarnkumar, "An approach to quantify the technical benefits of

distributed generation/' IEEE Trans. Energy Conversion, vo1. 19, no. 4, pp. 764-773,Dec.2004.

Ashwani Kumar and Wenzhong Gao, "Voltage profile improvement and line loss

reduction with distributed generation in deregulated electricity markets," IEEE

Region 10 Conference TENCON, 2008.

V.K. Shrivastava, O.P. Rahi, V.K. Gupta, and S.K. Singh, "Optimal location of dis-

tributed generation source in power system network," Power India Conference,

S. Ghosh, S.P. Ghoshal, and Saradindu Ghosh, "Optimal sizing and placement of

distributed generation in a network system," Electrical Power and Energy Systems,

val. 32, pp. 849-856, 2010.

C.L.T. Borges and D.M. Falcao, "Optimal distributed generation allocation for reli-

ability, losses and voltage improvement," Electrical Power and Energy Systems, val.

, pp. 413-420, 2006.

M. Sedighizadeh, M. Fallahnejad, M.R. Alerni, M. Ornidvaran, and D. Arzaghi-

haris, "Optimal placement of distributed generation using combination of PSO and

clonal algorithm," IEEE International Conference on Power and Energy, 2010.

https: I I www.ee. washington.edu I research I pstcal

Hadi Sadaat, Power System Analysis, Tata McGraw-Hill Education, 2002.

R. Eberhart and J. Kennedy, "Particle swarm optimization," IEEE International Con-

ference on Neural Networks, val. 4, pp. 1942-1948, 1995.

R.C. Eberhart and Shi Yuhui, "Particle Swarm Optimization: developments, appli-

cations and resources," Congress on Evolutionary Computation, val. 1, pp. 81-86,

R. Kaur, R. Kumar, A.P. Bhondekar, and P. Kumar, "Human opinion dynamics: An

inspiration to solve complex optimization problems," Scientific Reports 3, Nature,

no. 3008, 2013.

M. Macas and L. Lhotska, "Social theory impact based optimizer," Advances in

Artificial life, val. 4648, pp-635-644, 2007.

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Published

2018-03-18

How to Cite

Mahajan, S. ., & Vadhera, D. S. . (2018). Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique. Distributed Generation &Amp; Alternative Energy Journal, 33(2), 38–57. https://doi.org/10.13052/dgaej2156-3306.3322

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