Most Valuable Player Algorithm Based State Estimation for Energy Systems
State estimation (SE) processes the real-time measurements and provides database to energy control centre for safety control of energy systems. Traditionally 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.
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: 10.1016/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.
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 Components and Systems, vol. 36, no. 11, pp. 1200-1207, 2008. Available: 10.1080/15325000802084687.
N. Cherkaoui et al., ‘Reactive and Active Power Output Optimization in a Wind Farm Using the Particle Swarm Optimization Technique’, International 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 Journal of Advance Engineering and Research Development, vol. 3, no. 02, 2015. 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)90021-6.
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. 470-481, 2018. Available: 10.1016/j.epsr.2018.07.019.
M. Kabiri, N. Amjady, M. Shafie-khah and J. Catalão, ‘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.
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, 1983. Available: 10.1109/mspec.1983.6368994.