Optimal Allocation of Synchrophasor Units in the Distribution Network Considering Maximum Redundancy

  • S. Priyadarshini School of Electrical Engineering, Kalinga Institute of Industrial Technology Deemed to be University, India http://orcid.org/0000-0002-6222-7441
  • C. K. Panigrahi School of Electrical Engineering, Kalinga Institute of Industrial Technology Deemed to be University, India
Volume: 10 | Issue: 6 | Pages: 6494-6499 | December 2020 | https://doi.org/10.48084/etasr.3862

Abstract

Phasor Measurement Unit (PMU) is a smart measuring device commonly used in wide-area monitoring systems. It provides the synchronized phasor values and the magnitudes of voltages and currents in real-time for the proper state calculation of the electrical network in a common time reference frame. But in order to avoid unnecessary placements, minimize installation cost, and due to the lack of communication facilities at the substations, the placing of PMUs at every location is not possible. Therefore several optimization techniques have been developed to solve the Optimal PMU Placement (OPP) problem. The OPP problem aims to reduce the number of PMUs by achieving a completely observable network. Many solutions to the OPP problem have been proposed for the transmission networks with the use of conventional and heuristic-based approaches, but very few for distribution networks. In this paper, the Binary Grey Wolf Optimization (BGWO) algorithm is proposed to solve the OPP problem considering the measurement redundancy (MR) to achieve complete observability of the distribution network. Finally, case studies have been done by implementing the proposed algorithm on different IEEE test feeders such as the IEEE -13, -33, -37, and -123 node feeder systems. The obtained results are compared with previous studies to verify the feasibility and efficiency of the proposed technique.

Keywords: binary grey wolf optimization, measurement redundancy, observability, optimal PMU placement, phasor measurement unit

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References

A. G. Phadke, J. S. Thorp, and K. J. Karimi, "State Estimlatjon with Phasor Measurements," IEEE Transactions on Power Systems, vol. 1, no. 1, pp. 233-238, Feb. 1986. DOI: https://doi.org/10.1109/TPWRS.1986.4334878

N. V. P. Babu, P. S. Babu, and D. V. S. S. S. Sarma, "A New Power System Restoration Technique based on WAMS Partitioning," Engineering, Technology & Applied Science Research, vol. 7, no. 4, pp. 1811-1819, Aug. 2017. DOI: https://doi.org/10.48084/etasr.1197

H. Su, C. Wang, P. Li, Z. Liu, L. Yu, and J. Wu, "Optimal placement of phasor measurement unit in distribution networks considering the changes in topology," Applied Energy, vol. 250, pp. 313-322, Sep. 2019. DOI: https://doi.org/10.1016/j.apenergy.2019.05.054

Z. Zhao et al., "Optimal placement of PMUs and communication links for distributed state estimation in distribution networks," Applied Energy, vol. 256, p. 113963, Dec. 2019. DOI: https://doi.org/10.1016/j.apenergy.2019.113963

X. Chen et al., "Full Coverage of Optimal Phasor Measurement Unit Placement Solutions in Distribution Systems Using Integer Linear Programming," Energies, vol. 12, no. 8, p. 1552, Jan. 2019. DOI: https://doi.org/10.3390/en12081552

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 Systems with Applications, vol. 38, no. 6, pp. 7263-7269, Jun. 2011. DOI: https://doi.org/10.1016/j.eswa.2010.12.025

A. A. Saleh, A. S. Adail, and A. A. Wadoud, "Optimal phasor measurement units placement for full observability of power system using improved particle swarm optimisation," Transmission Distribution IET Generation, vol. 11, no. 7, pp. 1794-1800, 2017. DOI: https://doi.org/10.1049/iet-gtd.2016.1636

H. H. Müller and C. A. Castro, "Genetic algorithm-based phasor measurement unit placement method considering observability and security criteria," Transmission Distribution IET Generation, vol. 10, no. 1, pp. 270-280, 2016. DOI: https://doi.org/10.1049/iet-gtd.2015.1005

B. Milosevic and M. Begovic, "Nondominated sorting genetic algorithm for optimal phasor measurement placement," IEEE Transactions on Power Systems, vol. 18, no. 1, pp. 69-75, Feb. 2003. DOI: https://doi.org/10.1109/TPWRS.2002.807064

M. T. Mouwafi, R. A. El-Sehiemy, A. A. Abou El-Ela, and A. M. Kinawy, "Optimal placement of phasor measurement units with minimum availability of measuring channels in smart power systems," Electric Power Systems Research, vol. 141, pp. 421-431, Dec. 2016. DOI: https://doi.org/10.1016/j.epsr.2016.07.029

S. Li and Z. Meng, "Optimal PMU placement based on improved binary artificial bee colony algorithm," in 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), Harbin, China, Aug. 2017, pp. 1-6. DOI: https://doi.org/10.1109/ITEC-AP.2017.8081008

S. P. Singh and S. P. Singh, "A Multi-objective PMU Placement Method in Power System via Binary Gravitational Search Algorithm," Electric Power Components and Systems, vol. 45, no. 16, pp. 1832-1845, Oct. 2017. DOI: https://doi.org/10.1080/15325008.2017.1378775

T. Prakash, V. P. Singh, S. Singh, and S. Mohanty, "Binary Jaya algorithm based optimal placement of phasor measurement units for power system observability," Energy Conversion and Management, vol. 140, pp. 34-35, 2017.

N. C. Koutsoukis, N. M. Manousakis, P. S. Georgilakis, and G. N. Korres, "Numerical observability method for optimal phasor measurement units placement using recursive Tabu search method," IET Generation, Transmission & Distribution, vol. 7, no. 4, pp. 347-356, Apr. 2013. DOI: https://doi.org/10.1049/iet-gtd.2012.0377

A. Raj and C. Venkaiah, "Optimal PMU placement by teaching-learning based optimization algorithm," in 2015 39th National Systems Conference (NSC), Noida, India, Dec. 2015. DOI: https://doi.org/10.1109/NATSYS.2015.7489080

S. Priyadarshini and C. K. Panigrahi, "Binary Grey Wolf technique for Optimal Placement of Phasor Measurement Unit with full network observability," Journal of Engineering Science and Technology, vol. 15, no. 5, pp. 2924-2938, Oct. 2020.

N. H. A. Rahman, A. F. Zobaa, and M. Theodoridis, "Improved BPSO for optimal PMU placement," in 2015 50th International Universities Power Engineering Conference (UPEC), Stoke on Trent, UK, Sep. 2015, pp. 1-4. DOI: https://doi.org/10.1109/UPEC.2015.7339885

N. H. A. Rahman and A. F. Zobaa, "Integrated Mutation Strategy With Modified Binary PSO Algorithm for Optimal PMUs Placement," IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 3124-3133, Dec. 2017. DOI: https://doi.org/10.1109/TII.2017.2708724

R. Manam and S. R. Rayapudi, "Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2240-2250, Dec. 2017. DOI: https://doi.org/10.48084/etasr.1542

S. Mirjalili, S. M. Mirjalili, and A. Lewis, "Grey Wolf Optimizer," Advances in Engineering Software, vol. 69, pp. 46-61, Mar. 2014. DOI: https://doi.org/10.1016/j.advengsoft.2013.12.007

J. Too, A. R. Abdullah, N. Mohd Saad, N. Mohd Ali, and W. Tee, "A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification," Computers, vol. 7, no. 4, p. 58, Dec. 2018. DOI: https://doi.org/10.3390/computers7040058

M. Spitzer, C. Eerdmans, A. S. Nair, and P. Ranganathan, "Evaluation of PMU Placements with SORI and ORC Indices for IEEE Test Feeders," in 2018 IEEE International Conference on Electro/Information Technology (EIT), Rochester, MI, USA, May 2018, pp. 0687-0690. DOI: https://doi.org/10.1109/EIT.2018.8500263

V. Tran, H. Zhang, and V. Nguyen, "Optimal PMU Placement in Multi-configuration Power Distribution Networks," in Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016), Dec. 2016, pp. 508-514. DOI: https://doi.org/10.2991/iceeecs-16.2016.104

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