scholarly journals Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

2017 ◽  
Vol 7 (6) ◽  
pp. 2240-2250
Author(s):  
R. Manam ◽  
S. R. Rayapudi
Keyword(s):  
Linear Programming ◽  
Power System ◽  
State Estimation ◽  
Optimal Allocation ◽  
Estimation Methods ◽  
Programming Approach ◽  
Measurement Units ◽  
The Mean ◽  
Protection And Control ◽  
And Control

In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs) in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB) are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

scholarly journals State Estimation in Electric Power Systems Leveraging Graph Neural Networks

2022 ◽  
Author(s):  
Ognjen Kundacina ◽  
Mirsad Cosovic ◽  
Dejan Vukobratovic
Keyword(s):  
Power Systems ◽  
Power System ◽  
State Estimation ◽  
Electric Power Systems ◽  
State Variables ◽  
Evaluation Phase ◽  
Measurement Units ◽  
Synthetic Datasets ◽  
Graph Neural Networks ◽  
Test Scenarios

The goal of the state estimation (SE) algorithm is to estimate complex bus voltages as state variables based on the available set of measurements in the power system. Because phasor measurement units (PMUs) are increasingly being used in transmission power systems, there is a need for a fast SE solver that can take advantage of PMU high sampling rates. This paper proposes training a graph neural network (GNN) to learn the estimates given the PMU voltage and current measurements as inputs, with the intent of obtaining fast and accurate predictions during the evaluation phase. GNN is trained using synthetic datasets, created by randomly sampling sets of measurements in the power system and labelling them with a solution obtained using a linear SE with PMUs solver. The presented results display the accuracy of GNN predictions in various test scenarios and tackle the sensitivity of the predictions to the missing input data.

Machine learning for power system protection and control

2021 ◽  
Vol 34 (1) ◽  
pp. 106881
Author(s):  
Hanyu Yang ◽  
Xubin Liu ◽  
Di Zhang ◽  
Tao Chen ◽  
Canbing Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Power System ◽  
Power System Protection ◽  
System Protection ◽  
Protection And Control ◽  
And Control

scholarly journals An Adaptive Differential Protection and Fast Auto-Closing System for 10 kV Distribution Networks Based on 4G LTE Wireless Communication

2019 ◽  
Vol 12 (1) ◽  
pp. 2 ◽  
Author(s):  
Wen An ◽  
Jun Jie Ma ◽  
Hong Yang Zhou ◽  
Hong Shan Chen ◽  
Xu Jun ◽  
...  
Keyword(s):  
Control System ◽  
Wireless Communication ◽  
Power System ◽  
Power Supply ◽  
Distribution Networks ◽  
Fault Isolation ◽  
Differential Protection ◽  
Current Differential Protection ◽  
Protection And Control ◽  
And Control

With the development of wireless communication technology and computer technology, more and more smart technologies have been applied in electricity distribution networks. This paper presents an adaptive current differential protection and fast auto-closing system for application in 10 kV distribution networks in China Southern Power Grid. The current differential protection can adaptively change its settings according to the topology change of the primary distribution networks, thus the system effectively reduces the operation and maintenance cost of the power distribution network. In order to restore the power supply for the healthy part of the 10 kV networks quickly after a power system fault is cleared, the protection and control system provides wide area control function for automatic fault isolation and automatic switching. The traditional overcurrent protection and control system have no fault location function, it may take several minutes or even hours to manually locate a fault and then restore the power supply. Compared with the protection and control system of the traditional 10 kV distribution networks, the system developed can locate and isolate faults within 900 ms (assuming that the operating time of the load switch is 700 ms), and can quickly restore power supply in less than one second after a power system fault is cleared.

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