Identification of topology changes in power grids via reduced admittance matrix

2021 ◽  
Author(s):  
Ling Lin ◽  
Li Ding ◽  
Zhengmin Kong ◽  
Chaoyang Chen
Keyword(s):  
Power Systems ◽  
Power Grid ◽  
Measurement Data ◽  
Least Square Method ◽  
Least Square ◽  
Measurement Unit ◽  
Stable Operation ◽  
Admittance Matrix ◽  
Topology Changes ◽  
Grid Topology

Frequent changes in power grid topology bring risks to the stable operation of power systems. It is essential to identify changes in the power grid topology quickly and accurately. This paper presents a novel method named network reduction-based topology change identification (NR-TCI) algorithm to identify topology changes in multi-machine power systems. The proposed algorithm can quickly identify power grid topology changes using only phasor measurement unit (PMU) data sampled during the system’s transient process. The NR-TCI algorithm uses the network order reduction method to reduce the order of a bus admittance matrix and then uses PMU measurement data to estimate the reduced admittance matrix by least square method. Finally, the reduced admittance matrix is adopted to find topological information, and the Sherman–Morrison formula is utilized to identify the topology changes. The effectiveness of the proposed NR-TCI algorithm is verified with a case study of a 3 machine 9 bus system in Matlab. In addition, the influence of PMU sampling frequency on the effectiveness of the proposed algorithm is also studied.

Solar Tracking Device Based on Electronic Compass and Accelerometer

2014 ◽  
Vol 981 ◽  
pp. 522-525 ◽  
Author(s):  
Zhong Ran Zhang ◽  
Yuan Ma ◽  
Bo Jiao ◽  
Tong Liang Liu
Keyword(s):  
Elevation Angle ◽  
Least Square Method ◽  
Least Square ◽  
Stable Operation ◽  
Solar Tracking ◽  
High Flexibility ◽  
Tracking Device ◽  
Solar Position ◽  
Electronic Compass ◽  
The Magnetic Field

A solar tracking device was designed in this paper. First, In order to determine the initial direction of the mechanism and the east, HMC5883L was used for measuring the magnetic field of earth. Then, the mechanism began to operate according to the solar position which was confirmed though the astronomical calculation. Finally, the azimuth and the elevation angle of solar were measured and corrected by HMC5883L and MPU6050 respectively. HMC5883L was calibrated by the ellipse fitting, which was obtained though the least square method. The horizontal error of HMC5883L was compensated. The experimental study was performed. And the results show that the solar tracking device has the characteristics of stable operation, high flexibility and low requirement of installation precision.

scholarly journals System-Level Temperature Compensation Method for the RLG-IMU Based on HHO-RVR

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Hao Liang ◽  
Yumin Tao ◽  
Meijiao Wang ◽  
Yu Guo ◽  
Xingfa Zhao
Keyword(s):  
Least Square Method ◽  
Absolute Error ◽  
Performance Comparison ◽  
Compensation Method ◽  
Least Square ◽  
System Level ◽  
Measurement Unit ◽  
Error Terms ◽  
The Stability ◽  
Stability Time

The ring laser gyro inertial measurement unit has many systematic error terms and influences each other. These error terms show a complex nonlinear drift that cannot be ignored when the temperature changes, which seriously affects the stability time and output accuracy of the system. In this paper, a system-level temperature modeling and compensation method is proposed based on the relevance vector regression method. First, all temperature-related parameters are modeled; meanwhile, the Harris hawks optimization algorithm is used to optimize each model parameter. Then, the system compensation is modeled to stabilize the system output to the desired temperature. Compared with the least square method, the fitting performance comparison and the system dynamic compensation experiment prove this method’s superiority. The root mean square error, the mean absolute error, the R -squared, and the variance of residual increased by an average of 35.27%, 39.29%, 2.29%, and 30.34%, respectively.

scholarly journals Operational Reliability Assessment of an Interconnected Power System Based on an Online Updating External Network Equivalent Model with Boundary PMU

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 49 ◽  
Author(s):  
Dabo Zhang ◽  
Shuai Lian ◽  
Weiqing Tao ◽  
Jinsong Liu ◽  
Chen Fang
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Grid ◽  
Measurement Data ◽  
Operational Reliability ◽  
Equivalent Model ◽  
Interconnected Power System ◽  
Network Information ◽  
Interconnected Power Systems ◽  
Internal Network

Information between interconnected power systems is difficult to share in real time, due to trade secrets and technical limitations. The regional power grid cannot timely detect the impact of changes in the operation mode of the external power grid on the regional reliability, due to faults, load fluctuations, power generation plan adjustments, and other reasons. How to evaluate the reliability of a regional power system under the conditions of information isolation is a difficult problem for the security of interconnected power systems. Aiming at this problem, an operational reliability evaluation method for an interconnected power system is proposed herein, which does not depend on external network information directly, but only uses boundary phasor measurement unit (PMU) measurement data and internal network information. A static equivalent model with sensitivity consistency was used to simplify the external network to ensure the accuracy of the reliability calculation of interconnected power systems. The boundary PMU measurement data were used to update the external network equivalent model online. The algorithm flow of the operation reliability assessment for the interconnected power grid is given. The results of an example based on the IEEE-RTS-96 test system show that the proposed method can track the equivalent parameters of the external network without depending on the actual topological information, and calculate the reliability index of the internal network accurately.

scholarly journals Cost-Effective Placement of Phasor Measurement Units to Defend against False Data Injection Attacks on Power Grid

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3862
Author(s):  
Junhyung Bae
Keyword(s):  
Power Grid ◽  
Measurement Data ◽  
Cost Effective ◽  
Standard Test ◽  
Power Grids ◽  
Measurement Unit ◽  
False Data Injection ◽  
Injection Attacks ◽  
Phasor Measurement ◽  
Measurement Units

This study presents the phasor measurement unit (PMU) placement strategy in the presence of false data injection attacks which is one of the most serious security threats against power grid. It is focused on applications related to supervisory control and data acquisition (SCADA) systems where measurement data can be easily corrupted by adversaries without getting caught by the system. To safeguard power grids against malicious attacks, procedures have been proposed to facilitate the placement of secure PMUs to defend against false data injection attacks in a highly cost-effective way. It has formulated a method of identifying measurements that are vulnerable to false data injection attacks. It was discovered that a weak power grid can be transformed into a robust power grid by adding a few PMUs at vulnerable locations. Simulations on the IEEE standard test systems demonstrate the benefits of the proposed procedure.

Automatic Reverse Engineering Based on Reconstructing Measurement Data in 3D-Lattice

2012 ◽  
Vol 523-524 ◽  
pp. 414-419
Author(s):  
Kiyomoto Tsushima ◽  
Hideki Aoyama
Keyword(s):  
Reverse Engineering ◽  
Mathematical Models ◽  
Measurement Data ◽  
Least Square Method ◽  
Lattice Points ◽  
Least Square ◽  
Physical Models ◽  
Engineering System ◽  
Surface Data ◽  
Data Density

Reverse engineering systems are used to construct mathematical models of physical models such as clay model based on measurement data. In this study, we proposed a reverse engineering method which can construct high quality surface data automatically. This method consists of the following steps; The first globally and regionally smooths measured data based on the target shape by fitting quadric surface to measurement data. The second defines quadric surfaces and converts measurement points into 3D lattice points to obtain uniform measurement data density. As the positions of measurement data are converted from coordinate values into 3D lattice points, it is easier to find neighboring points and clarify neighboring relations between surfaces. The third acquires segment measurement data based on maximum curvatures and normals at each point. The last defines NURBS surfaces for each segment using the least square method to average positional errors. In order to validate the effectiveness of the proposed method, we developed a reverse engineering system and constructed mathematical models through basic experiments using clay car model measurement data.

500kV Substation Service Power System Modeling Research Based on Least Square Method with Parameter Optimization by SPO

2013 ◽  
Vol 860-863 ◽  
pp. 2534-2539
Author(s):  
Chang Ming Chen ◽  
Jiang Zeng ◽  
Xiang Hua Zhang
Keyword(s):  
Power System ◽  
Energy Saving ◽  
Parameter Optimization ◽  
Emission Reduction ◽  
System Modeling ◽  
Power Grid ◽  
Least Square Method ◽  
High Accuracy ◽  
Least Square ◽  
Grid Based

EHV substation service power is an important load in the power grid which is meaningful to be examined for the energy saving and emission reduction of the power grid. Based on the analysis of EHV substation service power and the improvement of the least square method, this paper get a new set of optimization which is is highly general and can reach high accuracy.

scholarly journals Identification of line status changes using phasor measurements through deep learning networks

2021 ◽  
Vol 22 (6) ◽  
pp. 55-67
Author(s):  
N. E. Gotman ◽  
G. P. Shumilova
Keyword(s):  
Deep Learning ◽  
Transmission Lines ◽  
Power Grid ◽  
Measurement Data ◽  
Transient State ◽  
Test System ◽  
Learning Networks ◽  
Status Change ◽  
Grid Topology ◽  
High Level

THE PURPOSE. To consider the problem of detecting changes in a power grid topology that occurs as a result of the power line outage / turning on. Develop the algorithm for detecting changes in the status of transmission lines in real time by using voltage and current phasors captured by phasor measurement units (PMUs) are placed on buses. Carry out experimental research on IEEE 14-bus test system. METHODS. This paper proposes a method from the field of artificial intelligence such as machine learning in particular "Deep Learning" to solve the problem. Deep Learning arises as a computational learning technique in which high level abstractions are hierarchically modelled from raw data. One of the means to effectively extract the inherent hidden features in data are Convolutional Neural Networks (CNNs). RESULTS. The article describes the topic relevance, offers to apply the method for detecting status of lines using a CNN classifier. The combination of different CNN architectures and the number of time slices from the moment of line status change are used to detect the power grid topology. The effectiveness of the joint use of PMUs and CNN in solving this problem has been proven. CONCLUSION. A solution for the line status change detection in the transient states using a CNN classifier is proposed. A high accuracy of the line status detection was obtained despite the influence of noise on measurement data. A change in the network topology is detected at the very beginning of the transient state almost instantly. It will allow the operator several times during the first seconds to identify the line state in order to make sure that the decisions made are correct.

scholarly journals Modeling and Prediction of Momentum Wheel Speed Data

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Jichao Li ◽  
Xiaxia Wang ◽  
Chaobo Chen ◽  
Song Gao
Keyword(s):  
Model Simulation ◽  
Interpolation Method ◽  
Least Square Method ◽  
Interval Data ◽  
Least Square ◽  
Ar Model ◽  
Prediction Algorithm ◽  
Model Parameters ◽  
Stable Operation ◽  
Equal Interval

To solve the problems of data loss and unequal interval of momentum wheel (MW) speed during a satellite stable operation, this paper presents a multidimensional AR model. A Lagrange interpolation method is used to convert measurements to equal interval data, and the FFT algorithm is adopted to calculate the period of MW speed variation. The long data sequence is converted into multidimensional time series, based on the equal interval data and the period. A multidimensional AR model is established, and the least square method is used to estimate the model parameters. The future data trend is predicted by the proposed model. Simulation results show that the prediction algorithm can achieve the across cycle prediction of the MW speed data.

scholarly journals Correlation effect of transformed or corrected data inversion

2021 ◽  
Author(s):  
László Balázs
Keyword(s):  
Likelihood Function ◽  
Measurement Data ◽  
Least Square Method ◽  
Estimation Procedure ◽  
Correlation Effect ◽  
Least Square ◽  
Inversion Method ◽  
Data Set ◽  
Data Inversion ◽  
Fitting Procedure

AbstractBefore performing the inversion process, the original measured data set is often transformed (corrected, smoothed, Fourier-transformed, interpolated etc.). These preliminary transformations may make the original (statistically independent) noisy measurement data correlated. The noise correlation on transformed data must be taken into account in the parameter fitting procedure (inversion) by proper derivation of likelihood function. The covariance matrix of transformed data system is no longer diagonal, so the likelihood based metrics, which determines the fitting process is also changed as well as the results of inversion. In the practice, these changes are often neglected using the “customary” estimation procedure (simple least square method) resulting wrong uncertainty estimation and sometimes biased results. In this article the consequence of neglected correlation is studied and discussed by decomposing the inversion functional to “customary” and additional part which represents the effect of correlation. The ratio of two components demonstrates the importance and justification of the inversion method modification.

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