Access the full text.
Sign up today, get DeepDyve free for 14 days.
Abdelkader Laouid, Mohamedi Djamel, A. Kouzou, M. Rezaoui (2018)
Optimal PMU Placement in Power System Based on Multi-objective Particle Swarm Optimization2018 15th International Multi-Conference on Systems, Signals & Devices (SSD)
(2011)
Optimal PMU placement considering contingencies by using a hybrid discrete particle swarm optimization technique
(2020)
Optimal PMUs placement to ensure power system observability under various contingencies
R. Saravanan, S. Subramanian, S. Sooriyaprabha, S. Ganesan (2018)
Generation scheduling with large-scale integration of renewable energy sources using grey wolf optimizationInternational Journal of Energy Sector Management
Kiarash Khajeh, E. Bashar, A. Rad, G. Gharehpetian (2017)
Integrated Model Considering Effects of Zero Injection Buses and Conventional Measurements on Optimal PMU PlacementIEEE Transactions on Smart Grid, 8
A. Pal, A. Vullikanti, S. Ravi (2017)
A PMU Placement Scheme Considering Realistic Costs and Modern Trends in RelayingIEEE Transactions on Power Systems, 32
Sen Zhang, Yongquan Zhou, Junmin Song, Chengyan Zhao (2016)
Using Orthogonal Grey Wolf Optimizer with Mutation for Training Multi-Layer Perceptron Neural NetworkJournal of Computational and Theoretical Nanoscience, 13
Lei Huang, Yuanzhan Sun, Jian Xu, Wenzhong Gao, Jun Zhang, Ziping Wu (2014)
Optimal PMU Placement Considering Controlled Islanding of Power SystemIEEE Transactions on Power Systems, 29
K. Deepika, Dr. Kumar, D. Rao (2017)
Optimal Placement of PMUs using Binary Particle Swarm Optimization with Reduced Search Space
B. Roy, A. Sinha, A. Pradhan (2012)
An optimal PMU placement technique for power system observabilityInternational Journal of Electrical Power & Energy Systems, 42
B. Gou (2008)
Optimal Placement of PMUs by Integer Linear ProgrammingIEEE Transactions on Power Systems, 23
(2019)
Optimal placement of phasor measurement unit in power system using meta-heuristic algorithms
K. Jamuna, K. Swarup (2012)
Multi-objective biogeography based optimization for optimal PMU placementAppl. Soft Comput., 12
T. Maji, P. Acharjee (2017)
Multiple Solutions of Optimal PMU Placement Using Exponential Binary PSO Algorithm for Smart Grid ApplicationsIEEE Transactions on Industry Applications, 53
Kaduvettykunnal Sajan, Akhilesh Mishra, Vishal Kumar, B. Tyagi (2016)
Phased Optimal PMU Placement Based on Revised Analytical Hierarchy ProcessElectric Power Components and Systems, 44
S. Mazhari, H. Monsef, H. Lesani, A. Fereidunian (2013)
A Multi-Objective PMU Placement Method Considering Measurement Redundancy and Observability Value Under ContingenciesIEEE Transactions on Power Systems, 28
M. Hajian, A. Ranjbar, T. Amraee, B. Mozafari (2011)
Optimal placement of PMUs to maintain network observability using a modified BPSO algorithmInternational Journal of Electrical Power & Energy Systems, 33
R. Babu, B. Bhattacharyya (2019)
Strategic placements of PMUs for power network observability considering redundancy measurementMeasurement
Ali Enshaee, R. Hooshmand, F. Fesharaki (2012)
A new method for optimal placement of phasor measurement units to maintain full network observability under various contingenciesElectric Power Systems Research, 89
S. Singh, S. Singh (2015)
Optimal Placement of Phasor Measurement Units Using Gravitational Search MethodInternational Journal of Energy and Power Engineering, 9
Junjian Qi, K. Sun, W. Kang (2015)
Optimal PMU placement for power system dynamic state estimation by using empirical observability Gramian2015 IEEE Power & Energy Society General Meeting
H. Bentarzi (2010)
Improving monitoring, control and protection of power grid using wide area synchro-phasor measurements
F. Aminifar, A. Khodaei, M. Fotuhi‐Firuzabad, M. Shahidehpour (2010)
Contingency-Constrained PMU Placement in Power NetworksIEEE Transactions on Power Systems, 25
S. Mirjalili, S. Mirjalili, A. Lewis (2014)
Grey Wolf OptimizerAdv. Eng. Softw., 69
Chengchao Lu, Zhongjie Wang, Ming Ma, Runjie Shen, Yang Yu (2018)
An Optimal PMU Placement With Reliable Zero Injection ObservationIEEE Access, 6
International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 9
N. Babu, P. Babu, D. SivaSarma (2018)
Binary cuckoo search based optimal PMU placement scheme for united Indian grid - A case studyInternational Journal of Engineering, Science and Technology
Abdelkader Laouid, Mohamed Rezaoui, A. Kouzou, R. Mohammedi (2019)
Optimal PMUs Placement Using Hybrid PSO-GSA Algorithm2019 4th International Conference on Power Electronics and their Applications (ICPEA)
IEEE Transactions on Power Systems, 30
S. Mirjalili (2015)
How effective is the Grey Wolf optimizer in training multi-layer perceptronsApplied Intelligence, 43
J. Aghaei, Amir Baharvandi, A. Rabiee, Mohammad-Amin Akbari (2015)
Probabilistic PMU Placement in Electric Power Networks: An MILP-Based Multiobjective ModelIEEE Transactions on Industrial Informatics, 11
L. Mech (1999)
Alpha Status, Dominance, and Division of Labor in Wolf PacksCanadian Journal of Zoology, 77
R. Babu, B. Bhattacharyya (2018)
An Approach for Optimal Placement of Phasor Measurement Unit for Power Network Observability Considering Various ContingenciesIranian Journal of Science and Technology, Transactions of Electrical Engineering, 42
V. Becejac, P. Stefanov (2020)
Groebner bases algorithm for optimal PMU placementInternational Journal of Electrical Power & Energy Systems, 115
(2016)
Free, open-source tools for electric power system simulation and optimization
J. Aghaei, Amir Baharvandi, Mohammad-Amin Akbari, K. Muttaqi, M. Asban, Alireza Heidari (2015)
Multi-objective Phasor Measurement Unit Placement in Electric Power Networks: Integer Linear Programming FormulationElectric Power Components and Systems, 43
This paper aims to find the minimum possible number of phasor measurement units (PMUs) to achieve maximum and complete observability of the power system and improve the redundancy of measurements, in normal cases (with and without zero injection bus [ZIB]), and then in conditions of a single PMU failure and outage of a single line.Design/methodology/approachAn efficient approach operates adequately and provides the optimal solutions for the PMUs placement problem. The finest function of optimal PMUs placement (OPP) should be mathematically devised as a problem, and via that, the aim of the OPP problem is to identify the buses of the power system to place the PMU devices to ensure full observability of the system. In this paper, the grey wolf optimizer (GWO) is used for training multi-layer perceptrons (MLPs), which is known as Grey Wolf Optimizer (GWO) based Neural Network (“GW-NN”) to place the PMUs in power grids optimally.FindingsFollowing extensive simulation tests with MATLAB/Simulink, the results obtained for the placement of PMUs provide system measurements with less or at most the same number of PMUs, but with a greater degree of observability than other approaches.Practical implicationsThe efficiency of the suggested method is tested on the IEEE 14-bus, 24-bus, New England 39-bus and Algerian 114-bus systems.Originality/valueThis paper proposes a new method for placing PMUs in the power grids as a multi-objective to reduce the cost and improve the observability of these grids in normal and faulty cases.
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering – Emerald Publishing
Published: Jan 11, 2022
Keywords: Particle swarm optimization; Power transmission systems; Multi-objective optimization; Phasor measurement units (PMUs); Zero injection bus (ZIB); Grey wolf optimizer (GWO) for training multi-layer perceptron (MLP); Redundancy of measurement
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.