Most Valuable Player Algorithm Based State Estimation for Energy Systems

Authors

  • S. Shanmugapriya Dept. of EEE, SRM Institute of Science and Technology, Kattankulathur, Chennai, India
  • D. Maharajan Dept. of EEE, SRM Institute of Science and Technology, Kattankulathur, Chennai, India

DOI:

https://doi.org/10.13052/dgaej2156-3306.3543

Keywords:

Estimation, most valuable player algorithm.

Abstract

State estimation (SE) processes the real-time measurements and provides
database to energy control centre for safety control of energy systems. Tradi-
tionally Weighted Least Square (WLS) and Weighted Least Absolute Value
(WLAV) based algorithms have been suggested for SE but the development
of very fast computers and parallel processing enable the system engineers to
think of employing the computationally inefficient evolutionary algorithms,
which are known to be robust and stable, in solving SE problems. This
paper suggests a most valuable player algorithm based SE involving WLS
and WLAV objectives one at a time, and presents results on four IEEE test
systems for illustrating its superiority.

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Author Biographies

S. Shanmugapriya, Dept. of EEE, SRM Institute of Science and Technology, Kattankulathur, Chennai, India

S. Shanmugapriya received the B.E. and M.E. degrees in Electrical and
Electronics Engineering and Power Systems Engineering from Annamalai
University, India in 2003 and 2005 respectively, and is presently working
towards her Ph.D Degree. She is presently working as an Assistant Professor,
Department of Electrical & Electronics Engineering, SRM Institute of Sci-
ence and Technology, India since 2006. Her research interests are in the area
of state estimation, evolutionary algorithms and power system analysis.

D. Maharajan, Dept. of EEE, SRM Institute of Science and Technology, Kattankulathur, Chennai, India

D. Maharajan was born in India in 1980. He received B.E Degree in
Electrical and Electronics Engineering from Bharathiyar University in 2002.
He obtained M.E degree in Power Systems Engineering and Ph.D in Electri-
cal Engineering from Anna University in 2007 and 2019 respectively. He is
currently working as an Assistant professor at SRM Institute of Science and
Technology (Formerly SRM University). He is specialized in the area of
Power System Dynamics, Wind Energy Conversion system, and Flexible AC
Transmission system.

References

D. Singh, R. Misra, V. Singh and R. Pandey, ‘Bad data pre-filter

for state estimation’, International Journal of Electrical Power &

Energy Systems, vol. 32, no. 10, pp. 1165–1174, 2010. Available:

1016/j.ijepes.2010.06.016.

D. Singh, J. Pandey and D. Chauhan, ‘Topology identification, bad data

processing, and state estimation using Fuzzy Pattern Matching’, IEEE

Transactions on Power Systems, vol. 20, no. 3, pp. 1570–1579, 2005.

Available: 10.1109/tpwrs.2005.852086.

Most Valuable Player Algorithm Based State Estimation for Energy Systems 303

H. Singh, F. Alvarado and W. Liu, ‘Constrained LAV state estimation

using penalty functions’, IEEE Transactions on Power Systems, vol. 12,

no. 1, pp. 383–388, 1997. Available: 10.1109/59.575725.

P. Aravindhababu and R. Neela, ‘A reliable and fast-decoupled weighted

least square state estimation for power systems’, Electric Power Com-

ponents and Systems, vol. 36, no. 11, pp. 1200–1207, 2008. Available:

1080/15325000802084687.

N. Cherkaoui et al., ‘Reactive and active power output optimization in

a wind farm using the particle swarm optimization technique’, Interna-

tional Journal of Advanced Engineering Research and Science, vol. 4,

no. 3, pp. 15–19, 2017. Available: 10.22161/ijaers.4.3.2.

R. Pires, L. Mili and F. Lemos, ‘Constrained robust estimation of power

system state variables and transformer tap positions under erroneous

zero-injections’, IEEE Transactions on Power Systems, vol. 29, no. 3,

pp. 1144–1152, 2014. Available: 10.1109/tpwrs.2013.2284734.

P. Tripathi, J. Rahul and N.A. Radhamohan, ‘A review of power system

state estimation by weighted least square technique’, International Jour-

nal of Advance Engineering and Research Development, vol. 3, no. 02,

Available: 10.21090/ijaerd.ncrretee27.

A. Sharma, S. Srivastava and S. Chakrabarti, ‘A multi-agent-based

power system hybrid dynamic state estimator’, IEEE Intelligent Systems,

vol. 30, no. 3, pp. 52–59, 2015. Available: 10.1109/mis.2015.52.

C. Lin and S. Huang, ‘Integral state estimation for well-conditioned

and ill-conditioned power systems’, Electric Power Systems Research,

vol. 12, no. 3, pp. 219–226, 1987. Available: 10.1016/0378-7796(87)

-6.

S. Goleijani and M. Ameli, ‘A multi-agent based approach to power

system dynamic state estimation by considering algebraic and dynamic

state variables’, Electric Power Systems Research, vol. 163, pp. 470–

, 2018. Available: 10.1016/j.epsr.2018.07.019.

M. Kabiri, N. Amjady, M. Shafie-khah and J. Catal ao, ‘Enhancing

power system state estimation by incorporating equality constraints

of voltage dependent loads and zero injections’, International Journal

of Electrical Power & Energy Systems, vol. 99, pp. 659–671, 2018.

Available: 10.1016/j.ijepes.2018.02.016.

S. Shanmugapriya and R. Jegatheesan, ‘Artificial bee colony based

static state estimation for power systems’, International Journal of

Recent Technology and Engineering, vol. 8, no. 3, pp. 6200–6202, 2019.

Available: 10.35940/ijrte.c5614.098319.

S. Shanmugapriya and D. Maharajan

J. Kim, H. Lee and J. Park, ‘A modified particle swarm optimization for

optimal power flow’, Journal of Electrical Engineering and Technology,

vol. 2, no. 4, pp. 413–419, 2007. Available: 10.5370/jeet.2007.2.4.413.

V. Basetti and A. Chandel, ‘Power system static state estimation using

a least winsorized square robust estimator’, Neurocomputing, vol. 207,

pp. 457–468, 2016. Available: 10.1016/j.neucom.2016.05.023.

H. Bouchekara, ‘Most Valuable Player Algorithm: a novel optimization

algorithm inspired from sport’, Operational Research, vol. 20, no. 1,

pp. 139–195, 2017. Available: 10.1007/s12351-017-0320-y.

‘News from Washington’, IEEE Spectrum, vol. 20, no. 2, pp. 16–16,

Available: 10.1109/mspec.1983.6368994.

Published

2021-04-28

How to Cite

Shanmugapriya, S. ., & Maharajan, D. . (2021). Most Valuable Player Algorithm Based State Estimation for Energy Systems. Distributed Generation &Amp; Alternative Energy Journal, 35(4), 295–306. https://doi.org/10.13052/dgaej2156-3306.3543

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