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A Reliable Wide-Area Measurement System Using Hybrid Genetic Particle Swarm Optimization (HGPSO)

N. V. Phanendra Babu(1*), P. Suresh Babu(2), D. V. S. S. Siva Sarma(3)

(1) Department of Electrical Engineering, National Institute of Technology Warangal, India
(2) Department of Electrical Engineering, National Institute of Technology Warangal, India
(3) Department of Electrical Engineering, National Institute of Technology Warangal, India
(*) Corresponding author



The state of the power system has to be estimated continuously and accurately by means of operating parameters i.e. voltage and current phasors. Phasor measurement unit (PMU) is becoming a most prominent tool for monitoring, control and protection of electric networks, and hence it is required to employ them for the present and future power system networks. Hence an Optimal PMU Placement (OPP) is quite important during the planning studies for both existing and future power networks. So, when a new state estimator is commissioned, or an existing estimator is up-graded, the problems of minimizing the number of PMUs and their optimal location for system with complete observability will come into scenario. This paper presents a novel Hybrid Genetic Particle Swarm Optimization (HGPSO) method based approach for a power system to have complete observability based optimal PMU placement problem subjected to all possible contingencies and PMU communication channel limitations. The proposed method is tested with some of standard IEEE test systems and also practiced on some Inter Regional Power Grids (IRPGs) of the Indian power system using MATLAB. The results obtained were also compared with existing techniques that have been already applied on the test systems said above, were proved to be the best and effective.
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Optimal Puma Placement (OPP); Hybrid Genetic Particle Swarm Optimization (HGPSO); Power System Obsrevability; Line/PMU Outage and Channel Limits

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Baldwin, T.L., Mili, L., Boisen, M.B., Adapa, R.: ‘Power system observability with minimal phasor measurement placement’, IEEE Trans. Power Syst., 1993, 8, (2), pp. 707–715.

Marın, F.J., Garcıa-Lagos, F., Joya, G., Sandoval, F.: ‘Genetic algorithms for optimal placement of phasor measurement units in electric networks’, Electron. Lett., 2003, 39, (19), pp. 1403–1405.

Hajian, M., Ranjbar, A.M., Amraee, T., Shirani, A.R.: ‘Optimal placement of phasor measurement units: particle swarm optimization approach’. Proc. Int. Conf. Intelligent Systems Application Power Systems, November 2007, pp. 1–6.

Xu, B., Abur, A.: ‘Observability analysis and measurement placement for system with PMUs’. Proc. IEEE Power Systems Conf. Exposition, October 2004, vol 2, pp. 943–946.

Gou, B.: ‘Optimal placement of PMUs by integer linear programming’, IEEE Trans. Power Syst., 2008, 23, (3), pp. 1525–1526.

Gou, B.: ‘Generalized integer linear programming formulation for optimal PMU placement’, IEEE Trans. Power Syst., 2008, 23, (3),pp. 1099–1104.

S. Chakrabarti, E. Kyriakides, and D. G. Eliades, “Placement of synchronized measurements for power system observability,” IEEE Trans. Power Del., vol. 24, no. 1, pp. 12–19, Jan. 2009.

Caro, E., Singh, R., Pal, B.C., Conejo, A.J., Jabr, R.A.: ‘Participation factor approach for phasor measurement unit placement in power system state estimation’, IET Gener. Transm. Distrib., 2012, 6, (9), pp. 922–929.

S. Chakrabarti and E. Kyriakides, “Optimal placement of phasor measurement units for power system observability,” IEEE Trans. Power Syst., vol. 23, no. 3, pp. 1433–1440, Aug. 2008.

N V Phanendra Babu, Dr. P Suresh Babu, Prof. D V S S SivaSarma, “Importance of Phasor Measurements In Wide Area Protection of Power System: A Review”, National Conference On Power System Protection, pp 83-89, February 2015.

N V Phanendra Babu, Dr, P Suresh Babu, Prof. D V S S SivaSarma, “A Wide-Area Prospective On Power System Prtection: A State-of-Art”, Presented for International Conference on Energy, Power and Environment (ICEPE 2015), India, June 2015.

Sodhi, R., Srivastava, S.C., Singh, S.N.: ‘Optimal PMU placement to ensure system observability under contingencies’. Proc. Power and Energy Society General Meeting, July 2009, pp. 1–6.

Y. M. Park, Y. H. Moon, J. B. Choo, and T. W. Kwon, “Design of reliable measurement system for state estimation,” IEEE Trans. Power Syst., vol. 3, no. 3, pp. 830–836, Aug. 1988.

A. Abur and F. H. Magnago, “Optimal meter placement for maintaining observability during single branch outage,” IEEE Trans. Power Syst., vol. 14, no. 4, pp. 1273–1278, Nov. 1999.

F. H. Magnago and A. Abur, “A unified approach to robust meter placement against loss of measurements and branch outages,” IEEE Trans. Power Syst., vol. 15, no. 3, pp. 945–949, Aug. 2000.

C. Rakpenthai, S. Premrudeepreechacharn, S. Uatrongjit, and N. R. Watson, “An optimal PMU placement method against measurement loss and branch outage,” IEEE Trans. Power Del., vol. 22, no. 1, pp.101–107, Jan. 2007.

Gopakumar P, Chandra G S, Reddy M J B, Mohanta D K. Optimal placement of PMUs for the smart grid implementation in Indian power grid — A case study. Frontiers in Energy, 2013, 7(3): 358–372.

Pathirikkat gopakumar, g. surya chandra, m. jaya bharata reddy, dusmata kumar mohanta,"Optimal redundant placement of PMUs in Indian power grid— northern, eastern and north-eastern regions". Frontiers in Energy 2013, 7(4): 413–428.

A. G. Phadke, J. S. Thorp, “History And Applications of Phasor Measurements”, IEEE Conference, 2006.

H. B. You, V. Vittal, Z. Yang, "self-healing in power systems: an approach using islanding and rate of change of frequency de-line based load shedding", IEEE transaction on power system, vol. 18, no.1, pp174-181, 2003.

Reynaldo F N, Phadke A G. Phasor measurement unit placement techniques for complete and incomplete observability. IEEE Transactions on Power Delivery, 2005, 20(4): 2381–2388.

Gou B. Generalized integer linear programming formulation for optimal PMU placement. IEEE Transactions on Power Systems, 2008, 23(3): 1099–1104.

Haupt R.L., Haupt S.E. Practical Genetic Algorithms (2ed., Wiley, 2004).

Xin-SheYang, Nature-Inspired Optimization Algorithms.

Mizumoto, M. (1996). Product-sum-gravity method = fuzzy singleton-type reasoning method = simplified fuzzy reasoning method. In The Proceedings of the Fifth IEEE International Conference on Fuzzy Systems, September 8–11, 1996, New Orleans (pp. 2098–2102).

Power Grid Corporation of India,

Aruljeyaraj kulanthaisamy, rajasekaran vairamani, nandha kumar karunamurthi, chandrasekaran koodalsamy," Multi-objective PMU Placement method Considering Observability and measurement Redundancy using ABC Algorithm". Advances in Electrical and Computer Engineering Volume 14, Number 2, 2014.

B.K. Saha Roy, A.K. Sinha, A.K. Pradhan An optimal PMU placement technique for power system observability, Electrical Power and Energy Systems 42 (2012) 71–77.

A. Ahmadi, Y. Alinejad-Beromi and M. Moradi, “Optimal PMU placement for power system observability using binary particle swarm optimization and considering measurement redundancy”,Expert System Applications, vol.38, pp. 7263-7269, May 2011.

R. Kavasseri, and S. K. Srinivasan, “Joint placement of phasor and power flow measurements for observability of power systems”, IEEE Trans. Power Systems, vol.26, pp. 1929-1936, Nov. 2011.


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