Implementation of PMU-Based Distributed Wide Area Monitoring in Smart Grid

Abstract

Determination of accurate operating states of the power system is one of the most challenging tasks due to integration of large number of solar PVs into the power system. Since these sources of energy are inertialess generations, hence may cause instability issues if highly penetrated. Hence, precise monitoring and control of such systems with higher PV penetration is a critical issue to address both in terms of the total number of PV sources in the system and the percentage of penetration. Phasor Measurement Units (PMUs), with their time synchronizing abilities, have made this task a bit easier. However, traditional centralized data handling architecture at control centers are becoming redundant due to various limitations such as data handling, computational constraints etc. To overcome this, a distributed PMU-PDC architecture approach is utilized in this paper. Since local PDC (Phasor Data Concentrator) in an n-area power system can run separate optimization algorithms, by combining the results of these optimization algorithms of n-area PDCs, we can get a much more accurate global consensus about the current operating state of the system. The presented work is divided into two parts. First, the analysis of power system stability is performed in terms of the total number of Photovoltaic Source (PV) in the system and the percentage of PV penetration. Then, the accuracy of the method is tested both in terms of the number of PMUs in each area along with their channel capacities. Low-frequency oscillations have been simulated on IEEE-68 standard bus system using MATLAB, and the modes of oscillation are estimated using the Alternating Direction Method of Multipliers (ADMM) algorithm. INDEX TERMSWide-Area Measurement System (WAMS), Phasor Measurement Unit (PMU), Phasor Data Concentrator (PDC), Alternating Direction Method of Multipliers (ADMM)

A Low-Cost Test Platform for Performance Analysis of Phasor Measurement Units

“…The solution that emerges is the use of phasor measurement units (PMU) in distribution networks, which can improve existing supervisory control and data acquisition (SCADA) systems [10][11][12]. Generally, PMU measures the magnitude and phase of the voltage and current of a three-phase system, as well as the frequency and the rate of change of frequency (ROCOF).…”

Applying Cross-Permutation-Based Quad-Hybrid Feature Selection Algorithm on Transient Univariates to Select Optimal Features for Transient Analysis

“…Nowadays, information technology (IT) by integrating different data-driven systems, plays the pivot role in collecting a large amount of data in different sensitive industries. The raw data obtained by the IT paradigm provide the necessary conditions for conducting data-oriented actions instead of experience-based operations in all tasks and responsibilities of system operators [1]- [5]. Such restructuring in the decision-making process will be possible through data mining (DM) technology which triangulated machine learning (ML), statistical learning (SL), and dataset to discover useful patterns for predicting different phenomena [6], [7].…”

Online System for Power Quality Operational Data Management in Frequency Monitoring Using Python and Grafana

“…PMUs are used to estimate the magnitude and phase of electrical magnitudes (e.g., voltage or current) [6][7][8][9][10][11]. Synchronization features are provided via GPS or IEEE 1588 Precision Time Protocol (PTP), designed to allow real-time synchronization of several remote points in the grid.…”

“…PMUs capture samples of the power line signal and rebuild the so-called phasor quantity (magnitude and phase), which constitutes the mathematical model of the waveform under test. The result is a time-synchronized measurement quantity known as syncrophasor [10,11].…”

“…Indeed, a typical commercial PMU can report measurements with very high temporal resolution, up to 120 measurements per second (30, 60 and 120 are common reporting rates) [10]. This helps with analyzing dynamic events in the grid, which is not possible with traditional SCADAs that generate one measurement every 2 or 4 s. Therefore, PMUs with enhanced monitoring and control capabilities are considered as one of the most important measuring devices in the current and future design of power systems [7][8][9][10][11][12].…”