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.

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.

scholarly journals Real-Time State Estimation in the Cameroon Power System

2013 ◽  
Vol 2013 ◽  
pp. 1-10
Author(s):  
Emmanuel Tanyi ◽  
Edwin Mbinkar
Keyword(s):  
Power System ◽  
State Estimation ◽  
Real Time ◽  
Ad Hoc ◽  
Dynamic State ◽  
System State ◽  
State Variables ◽  
Power System State Estimation ◽  
Dynamic State Estimation ◽  
Measurement Units

An important tool for the energy management system (EMS) is state estimation. Based on measurements taken throughout the network, state estimation gives an estimation of the state variables of the power system while checking that these estimates are consistent with the measurements. Currently, in the Cameroon power system, state estimates have been provided by ad hoc supervisory control and data acquisition (SCADA) systems. A disadvantage is that the measurements are not synchronised, which means that state estimation is not very precise during dynamic phenomena in the network. In this paper, real-time phasor measurement units (PMUs) that provide synchronised phasor measurements are proposed for integration into the power system. This approach addresses two important issues associated with the power system state estimation, namely, that of measurement accuracy and that of optimization of the number of measurement sites, their location, and the importance given to their measurements on the dynamic state estimation.

scholarly journals State Estimation via Phasor Measurement Units for Iraqi National Super Grid Power System Network

2016 ◽  
Vol 12 (1) ◽  
pp. 12-22
Author(s):  
Husham Hussein
Keyword(s):  
Power Systems ◽  
Power System ◽  
State Estimation ◽  
Electrical Power ◽  
Estimation Method ◽  
Phasor Measurement Units ◽  
Graph Theoretic ◽  
Phasor Measurement ◽  
Measurement Units ◽  
Analysis System

In this paper describes the operation of power system networks to be nearest to stability rated values limits. State estimation for monitoring and protection power system is very important because it provides a real-time (RT) Phase angle of different nodes of accuracy and then analysis and decided to choose control way (methods). In order to detect the exact situation (instant state) for power system networks parameters. In this paper proposes a new monitoring and analysis system state estimation method integrating with MATLAB environment ability, by using phasor measurement units (PMU's) technology, by this system the estimation problem, iterations numbers, and processing time will reduce. The measurements of phasors value of voltage signal and current estimated and analyzed. Mat lab/PSAT package use as a tool to design and simulate four electrical power systems networks such as INSG 24 buses, IEEE14 bus, Diyala city 10buses (IRAQ), and IEEE6 bus and then installed and applied PMU’s devices to each system. Simulation results show that the PMU's performances effectiveness appear clearly. All results show the validation of PMU’s devices as an estimator to power system networks states and a significant improvement in the accuracy of the calculation of network status. All results achieved and discussed through this paper setting up mathematical models with Graph Theoretic Procedure algorithm.

scholarly journals Trust assessment of power system states

2020 ◽  
Vol 3 (S1) ◽  
Author(s):  
Michael Brand ◽  
Davood Babazadeh ◽  
Carsten Krüger ◽  
Björn Siemers ◽  
Sebastian Lehnhoff
Keyword(s):  
Power Systems ◽  
Power System ◽  
Data Acquisition ◽  
State Estimation ◽  
Trust Model ◽  
Proof Of Concept ◽  
Process Data ◽  
Acquisition Process ◽  
Functional Correctness ◽  
Data Acquisition Process

Abstract Modern power systems are cyber-physical systems with increasing relevance and influence of information and communication technology. This influence comprises all processes, functional, and non-functional aspects like functional correctness, safety, security, and reliability. An example of a process is the data acquisition process. Questions focused in this paper are, first, how one can trust in process data in a data acquisition process of a highly-complex cyber-physical power system. Second, how can the trust in process data be integrated into a state estimation to achieve estimated results in a way that it can reflect trustworthiness of that input?We present the concept of an anomaly-sensitive state estimation that tackles these questions. The concept is based on a multi-faceted trust model for power system network assessment. Furthermore, we provide a proof of concept by enriching measurements in the context of the IEEE 39-bus system with reasonable trust values. The proof of concept shows the benefits but also the limitations of the approach.

scholarly journals An Accurate Method for Delay Margin Computation for Power System Stability

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3466 ◽  
Author(s):  
Ashraf Khalil ◽  
Ang Swee Peng
Keyword(s):  
Time Delay ◽  
Power Systems ◽  
Power System ◽  
System Stability ◽  
Area Measurement ◽  
Power System Stabilizer ◽  
Iteration Algorithm ◽  
Measurement Units ◽  
System Stabilizer ◽  
Delay Margin

The application of the phasor measurement units and the wide expansion of the wide area measurement units make the time delay inevitable in power systems. The time delay could result in poor system performance or at worst lead to system instability. Therefore, it is important to determine the maximum time delay margin required for the system stability. In this paper, we present a new method for determining the delay margin in the power system. The method is based on the analysis in the s-domain. The transcendental time delay characteristics equation is transformed to a frequency dependent equation. The spectral radius is used to find the frequencies at which the roots cross the imaginary axis. The crossing frequencies are determined through the sweeping test and the binary iteration algorithm. A single machine infinite bus system equipped with automatic voltage regulator and power system stabilizer is chosen as a case study. The delay margin is calculated for different values of the power system stabilizer (PSS) gain, and it is found that increasing the PSS gain decreases the delay margin. The effectiveness of the proposed method has been proved through comparing it with the most recent published methods. The method shows its merit with less conservativeness and fewer computations.

Computational development of a practical educational tool for state estimation of power systems using the MATLAB optimization toolbox

2018 ◽  
Vol 56 (2) ◽  
pp. 105-123 ◽  
Author(s):  
EA Zamora-Cárdenas ◽  
A Pizano-Martínez ◽  
JM Lozano-García ◽  
VJ Gutiérrez-Martínez ◽  
R Cisneros-Magaña
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Electric Power ◽  
Smart Grids ◽  
Weighted Least Squares ◽  
Electric Power Systems ◽  
The State ◽  
Estimation Problem ◽  
Educational Tool ◽  
And Control

State estimation is one of the most important processes to perform a reliable monitoring and control of the steady-state operating condition of modern electric power systems; thus, it is currently a fundamental part in the development of research to enhance the monitoring and security of the smart grids operation. This important topic is taught in advanced courses of operation and control of power systems, for graduate and undergraduate power engineering students. However, the most used software packages for simulation and analysis of power systems by researchers, students, and educators have put little attention on the state estimation module. Due to this fact, this paper proposes an approach to develop the computational implementation of a practical educational tool for state estimation of electric power systems using the MATLAB optimization toolbox. In this proposal, the formulation of the state estimation problem consists of developing a general digital code to implement an objective function based on the weighted least squares method. While the lsqnonlin function of the MATLAB optimization toolbox solves the formulated state estimation problem. Simplifying both research and educational processes, this tool helps graduate and undergraduate students to improve learning, understanding, and the times of implementation and development of research in state estimation. Simulations of an equivalent model of the Mexican interconnected power system consisting of 190 buses and 46 machines are used to test and validate the proposal performance.

A Review of the Smart Grid Concept for Electrical Power System

2022 ◽  
pp. 1361-1385
Author(s):  
Amam Hossain Bagdadee ◽  
Li Zhang
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Smart Grids ◽  
Electrical Power ◽  
Future Generation ◽  
Electric Power Systems ◽  
Basic Information ◽  
Electrical Power System

The review this article conducts is an extensive analysis of the concept of a smart grid framework with the most sophisticated smart grid innovation and some basic information about smart grid soundness. Smart grids as a new scheme for energy and a future generation framework encourages the expansion of information and progress. The smart grid framework concord will potentially take years. In this article, the focus is on developing smart networks within the framework of electric power systems.

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