Adaptive power system hybrid state estimation

2014 ◽  
Author(s):  
Manikandan Padmanaban ◽  
Avinash K. Sinha
Keyword(s):  
Power System ◽  
State Estimation ◽  
Hybrid State ◽  
Adaptive Power

scholarly journals Voltage Stability Index Calculation by Hybrid State Estimation based on Multi Objective Optimal Phasor Measurement Unit Placement

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2688
Author(s):  
Matsukawa ◽  
Watanabe ◽  
Wahab ◽  
Othman
Keyword(s):  
Power System ◽  
State Estimation ◽  
Voltage Stability ◽  
Stability Index ◽  
Phasor Measurement Unit ◽  
Measurement Unit ◽  
Voltage Collapse ◽  
Hybrid State ◽  
Voltage Stability Index ◽  
Critical Boundary

Operation of a power system close to the voltage stability limit due to increasing of load demand and limited power sources may result in disastrous economic loss with voltage collapse of the entire power system. A system operator has to understand how far the system is from the critical boundary of the voltage collapse. This paper investigated the influence of State Estimation (SE) in the calculation of the Critical Boundary Index (CBI) as a voltage stability index. For SE, Hybrid State Estimation (HSE), including the measurement set of both Remote Terminal Unit (RTU) in Supervisory Control and Data Acquisition (SCADA) and Phasor Measurement Unit (PMU), is employed. Concurrently, the CBI is estimated using voltage phasor estimated by HSE based on optimal PMU location, which is selected from a Pareto optimal front obtained by the Non-dominated Sorting Genetic Algorithm II (NSGA-II). As a result of CBI estimation, HSE using PMU is relatively accurate in voltage stability index estimation compared to SCADA SE, which uses the RTU alone. However, when a mixed measurement condition in some lines affects the CBI estimation, it is suggested that it may be necessary to discard PMU measurements in some cases.

Two-level state estimation for large power system. Part 1: Algorithms

1988 ◽  
Vol 135 (4) ◽  
pp. 299 ◽  
Author(s):  
K.L. Lo ◽  
M.M. Salem ◽  
R.D. McColl ◽  
A.M. Moffatt
Keyword(s):  
Power System ◽  
State Estimation ◽  
Large Power ◽  
System Part

A Harmonic Source Location Method Based on PMU Measurements in Distribution Network

2015 ◽  
Vol 775 ◽  
pp. 409-414
Author(s):  
Bing Jun Li ◽  
Su Quan Zhou ◽  
Xiao Xiang Lun
Keyword(s):  
Power System ◽  
State Estimation ◽  
Distribution Network ◽  
Measured Data ◽  
Optimal Measurement ◽  
Location Method ◽  
Measurement Placement ◽  
Minimum Number ◽  
Harmonic Source ◽  
The Cost

It is of great importance to identify the location of the harmonic sources for the harmonic governance in the power system. Applied with optimal measurement placement (OMP) and harmonic state estimation (HSE), this paper presents a novel process based on PMU measurements to locate the harmonic sources in the distribution network. Considering the cost and the observability, the OMP can provide a scheme of the measurement placement with the minimum number of PMU measurements. In order to simplify the HSE equation, the measured data are converted to the form of voltage by the method proposed in this paper.By solving the HSE equation, the location and magnitude of the harmonic source are evaluated. The methodology is applied to the IEEE 33-bus system, and the obtained results are properly analyzed.

Power System State Estimation: Detection of Topological Errors

1981 ◽  
Vol PER-1 (1) ◽  
pp. 19-19
Author(s):  
R. L. Lugtu ◽  
D. F. Hackett ◽  
K. C. Liu ◽  
D. D. Might
Keyword(s):  
Power System ◽  
State Estimation ◽  
System State ◽  
Power System State Estimation ◽  
Topological Errors
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