Reconstruction of transient waveforms from phasors sampled at the fundamental frequency

Synchrophasor technology is an emerging and developing technology for monitoring and control of wide area measurement systems (WAMS). In an elementary WAMS, two identical phasors measured at two different locations have difference in the phase angles measured since their reference waveforms are not synchronized with each other. Phasor measurement units (PMUs) measure input phasors with respect to a common reference wave based on the atomic clock pulses received from global positioning system (GPS) satellites, eliminating variation in the measured phase angles due to distant locations of the measurement nodes. This has found tremendous applications in quick fault detection, fault location analysis, accurate current, voltage, frequency and phase angle measurements in WAMS. Commercially available PMU models are often proven to be expensive for research and development as well as for grid integration projects. This research article proposes an economic PMU model optimized for accurate steady-state performance based on recursive discrete Fourier transform (DFT) and provides results and detailed analysis of the proposed PMU model as per the steady state compliance specifications of IEEE standard C37.118.1. Results accurate up to 13 digits after decimal point are obtained through the developed PMU model for both nominal and off-nominal frequency inputs in steady state.

This paper investigates two primary algorithms for estimating phasor information used in Phasor Measurement Units (PMU). Power systems behavior and responses are more complicated nowadays and subsequently their supervision, control and protection are more critical and challenging. Various supervisory systems should be employed for protective and control purposes. All these supervisory systems rely on PMU technology with data stamps synchronized by Global Positioning System (GPS). A PMU's accuracy and performance in phasor estimation during different power system working conditions to track the actual signal has an impact on the system state estimation and subsequently in the ability in fault and disturbances diagnosis. Many algorithms are proposed recently to be employed for phasor estimation in PMU devices. It is showed that Discrete Fourier based algorithms are the best methods in digital world to implement in PMU devices. Such methods are Discrete Fourier Transform (DFT) and Smart DFT that are compared and investigated in this article. Simplicity and low computational burden of these methods resulted in attracting many literatures to employ them in phasor estimation algorithms. However, their accuracy in off-nominal frequency and performance during different working condition are controversial which are studied in this article. Extensive simulations are performed in MATLAB Simulink to study and compare DFT and SDFT algorithms under different system disturbances.

The ability of data recovery during communicational failures is one of the significant advantages of the wide area measurement system (WAMS) with hierarchical structure. For this purpose, in addition to the proper partitioning of the WAMS, the relative location of phasor measurement units (PMUs) and phasor data concentrators (PDCs) should be selected so as to maximize the reliability of the communication network. The aim of this paper is to develop an organized method for partitioning the WAMS as well as proposing a new algorithm for the simultaneous optimal placement of PMUs and PDCs. In the proposed method, first it is assumed that PMUs are installed at all of the system buses. Then, redundant PMUs will be omitted sequentially to provide the system observability with the maximum communication reliability. The IEEE 30-, and 118-bus systems are used to demonstrate the proposed algorithm. Contingencies such as PMU loss and line outage are considered in power system observability achievement. Finally, to show the applicability of proposed methods to real dimensional power systems, the IEEE 300-bus power system is also analyzed in the normal operating condition.

In order to easily monitor the wide-area power system information covering many power producers, suppliers, and power companies, authors have been developed a PMU (phasor measurement unit) based WAMS (wide area measurement system). This WAMS momentarily gather information about the power oscillation affecting the stability of Japanese longitudinal power systems by signal processing of the power outlet phasor. This paper introduces the features of the PMU based WAMS, and an availability of the power outlet phasor is validated by comparing the measurements with actual power station. And as one of the applications, an estimation method of interconnected power system parameters from the monitored power oscillation information is proposed.

WAMS (Wide Area Measurement System) is a newly developed technology, which can provide a reliable guarantee to the simultaneous measurement of power system. But PMU (Phasor Measurement Unit) can not be widely used in power grid now, so it is impossible that WAMS can replace SCADA (Supervisory Control And Data Acquisition) system presently. Hence, how to incorporate WAMS measuring data into other systems including SCADA has become a hot research topic currently especially the data exchange between them. In order to solve this problem, a CIM (Common Information Model)-based information model for WAMS is proposed in this paper according both to IEC 61970: EMS-API (Energy Management System Application Program Interface) part 303 and the principle and the application of WAMS. This paper establishes a new package named WAMS in the framework of CIM and then some extended classes and their attributes along with their relationships are also defined. Finally this paper briefly describes the application of this CIM-based information model by presenting a flow diagram about information integration and utilization between WAMS and SCADA.

A wide-area measurement system (WAMS) consists of advanced measurementtechnology,thelatestcommunicationnetworkinfrastructure,andintegratedoperationalframework. The supervisory control and data acquisition (SCADA) infrastructure forenergy-management system (EMS) has been widely used in power systems for a longtime. Some of the functionalities of an EMS are system state monitoring, tie-line biascontrol,andeconomicdispatch[1].However,inrecentyears,variousdeficienciesoftheexisting SCADA-based EMS (such as quasi-steady-state calculation, non-synchronizeddataacquisition,andrelativelylowdatatransmissionrate)havebeenpointedout.Thesedefects make it impossible to sample the global state of a power system in real time.As more and more wide-area blackouts are reported, it is clear that acquiring real-timeor wide-area state information would be needed in the future. The state informationin terms of phasors of voltages and currents from a distributed wide area in real timeis therefore critical for avoiding large-area disturbances by effecting wide-area controlbased on wide-area measurements.The main enabler of WAMS is phasor measurement unit (PMU) technology. Withthe innovation of PMU, the problem of measuring the phasor quantities simultaneouslyfromawideareaofdistributedsubstations,alsocalled‘synchrophasor’,hasbeensolved.At present, the PMU technology is one of the essential enablers for WAMS. It utilizesthe availability of high-precision synchronized clock sources – extracted from globalpositioning system (GPS) receivers and samples the instantaneous analogue – quanti-ties of voltage and current magnitudes and phase angles. Many utilities are installingPMUs at very high voltage substations, but the trend is that eventually PMUs will beused to monitor all high-voltage transmission lines. There are debates as to whether thewide-area or long-distance communications that communicate phasor data, or controlaction messages, should only be done via proprietary networks, or the existing Inter-net infrastructure with quality-of-service (QoS) differentiated delivery could be used.These questions require further simulation studies as well as financial and policy deci-sions which are not considered in this chapter. We concentrate mostly on evaluatingthe network architecture, the specific network medium and technology, the appropriate

Phasor Measurement Units (PMUs) are normally used in Wide Area Measurement System (WAMS) for vast applications, such as monitoring the transmission system status over bulky areas including the control and protection. Therefore, this paper reviews the power system protection in relation to the synchronized PMUs and the applications of phasor estimation techniques. Furthermore, the paper elaborates the research works on the applications of PMU for diverse features. The structure and types of PMUs are described utilizing the mathematical modeling of simple Discrete Fourier Transform (DFT) with Recursive and Non-Recursive estimation methods. The paper also presents the results of some published studies for two algorithms (Recursive and Non-Recursive). The review has revealed that the Non-Recursive algorithm is more accurate and gives robust estimation results.

Nowadays, the increase in electrical energy consumption and power system restructuring have posed new challenges to the operation, control, and monitoring of power systems. In this situation, the supervisory control and data acquisition (SCADA) system is not enough to ensure power system security and stability. The SCADA is often unable to measure data of all buses simultaneously. In addition, the sampling rate in this system is not enough for some power system applications. Therefore, the information obtained from SCADA does not show power system dynamics properly. In order to improve the power system monitoring, wide area measurement system (WAMS) has been developed to overcome the problems of SCADA system. Phasor measurements units (PMUs) are the main part of WAMS system and it basically consists of three essential processes including collecting, transmitting, and analyzing data. WAMS receives obtained data via a high speed communication links. After data processing and extracting appropriate information, decisions are made to improve the power system performance. Efficient use of power system data to achieve a secure operation strategy is targeted using the WAMS system. Due to the effective role of WAMS and PMUs in the reliable operation of power system, it is necessary to study their concept and applications in this chapter. The history of PMU and its structure is presented in this chapter. In addition, the necessity of WAMS for future power system and its difference from SCADA system have been investigated in this chapter. Different algorithms and application of the WAMS are also introduced in this chapter which can be implemented to improve the performance of the future power system.

The design of both area-efficient and reliable VLSI arrays for computation of the complex N-point discrete Fourier transform (DFT) is considered. C.D. Thompson's VLSI model of computation (1979) is used to quantify the area required by wiring and the achievable period. Four architectures using the fast two-dimensional (2-D) algorithm for the DFT that achieve the maximum throughput per chip area are presented. The first two use N-element 2-D meshes requiring N+2N/sup 3/2/ multiplications and 1+2 square root N periods per DFT. The first uses in place data I/O and can be made systolic with Goertzel's algorithm. The second is systolic with row parallel I/O. The third and fourth architectures both use pipelined DFT blocks of length square root N connected by a pipelined matrix transposer. The third uses systolic 2-D meshes for the short DFTs with period square root N. The fourth uses pipelined butterfly networks implementing standard FFT algorithms for the short DFTs, but only N(1+log/sub 2/ N) multiplications per DFT, thus preserving maximum throughput per unit area. The technique of algorithm-based fault-tolerance applies directly to all four architectures with only fractional redundant overhead. >

To assess the insulation condition of capacitive apparatus, on-line monitoring of dielectric loss angle is an effective measure. Harmonic analysis algorithm is used to calculate dielectric loss angle traditionally, this method can effectively suppress the DC (Direct Current) offset and harmonic interference. However, when the power system frequency fluctuates, the synchronous sampling condition is difficult to meet, so, traditional harmonic analysis method can produce leakage of spectrum and picket-fence effect, which greatly affects the accuracy of dielectric loss angle measurement. In order to reduce this adverse effect, this paper proposes a method called hamming windowed interpolated DFT (Discrete Fourier Transform) algorithm based on modified ideal sampling frequency. Time series analysis based on modified ideal sampling frequency can be used to modify the time series in non-synchronous sampling condition to meet synchronous sampling condition. Hamming windowed interpolated DFT algorithm can inhibit leakage of spectrum and picket-fence effect. Firstly this paper analyzes the principle of traditional DFT algorithm and the reason that causes leakage of spectrum and picket-fence effect in non-synchronous sampling condition. Secondly, the principle of hamming windowed interpolated DFT algorithm based on modified ideal sampling frequency is elaborated. Finally this paper presents the simulation result which shows that the improved approach has higher accuracy.

Basic phasor measurement units are the sensing devices that capture power system phasors synchronously over wide geographical areas with high precision by means of global positioning system enabled time-stamping. The data obtained from phasor measurement units form the basis of all monitoring and control actions for wide-area measurement systems, and hence, phasor measurement units are the edifice of a wide-area measurement system. Within the purview of phasor measurement units, there have been diverse research contributions made in past decades. This article presents a brief review of phasor measurement units performing their functions as smart sensors. The review includes their evolution, optimal placement, applications, and reliability assessment. The main contributions pertain to segregation of research findings into broad domains with corroborations to validate phasor measurement units as the efficient sensors for the smart grid.

With the wide application of synchronized phase measurement unit (PMU) in power system, the wide-area measurement system (WAMS) has enabled the use of a combination of measured information from remote location for global control purpose. However, the impact of time delays introduced by remote information's transmission in WAMS has to be considered, and the closed-loop power systems need be modeled as time-delay nonlinear systems. Moreover, the wide-area information is incomplete when not all generators in power system are equipped with the PMU. In order to eliminate the effects of power system model's nonlinearity and wide-area information's uncertainty including time delays and incompleteness, a novel approach based on inverse system algorithm and linear matrix inequality (LMI) technique is proposed to design a nonlinear robust integrated controller. Digital simulation demonstrates that the four-machine system under the nonlinear robust integrated control has less settling time, swing times, oscillatory peak value and more critical clear time and better voltage stability performance for various time delays of remote incomplete measured information than that under PID control or nonlinear decentralized integrated control.

In today’s era, it is important to analyze and utilize various signals in industrial or laboratory applications. Measured signals provide critical information about the controlled system, which can be contained precisely within a narrow frequency range. Many methods and algorithms exist to process such signals in both the time and frequency domains. In particular, signal processing in the frequency domain is primary in industrial practice because dominant components within a specific narrow frequency band are sought. The discrete Fourier transformation (DFT) algorithm is the tool used in practice to find these frequency components. The DFT algorithm provides the full frequency spectrum with a higher number of calculation steps, and its spectrum frequency resolution is low. Therefore, research has focused on finding a method to achieve high-frequency spectrum resolution. An important factor in selecting the technique was that such an algorithm should be implementable on a microprocessor-based system under harsh industrial conditions. Research results showed that the DFT ZOOM method meets these requirements. The frequency zoom has many advantages but requires some modification. It is implemented in high-performance analyzers, but a thorough and detailed description of the respective algorithm is lacking in technical articles and literature. This article mathematically and theoretically describes the modified frequency zoom algorithm in detail. The steps of the frequency zoom, from creating an analytical signal through frequency shifting and decimation to the frequency analysis of the signal, are realized. The algorithm allows for the analysis of a signal with high-frequency resolution in a limited frequency band. A significant modification of DFT ZOOM is that of using the Hilbert transform to create an analytic signal. This resolves the aliasing issue caused by the overlap between fundamental and sideband spectra. Results from processing deterministic and stochastic signals using the modified DFT ZOOM are presented. The presented experimental results contribute to a more detailed frequency analysis of the signal. As part of this scientific research, the issues of frequency zoom were thoroughly addressed, solving the partial problems of this algorithm, both in theory and in the context of signal theory.

WAMS-based detection and early-warning of low-frequency oscillations in large-scale power systems

This paper describes the modelling of a Wide Area Measurement System (WAMS) in MATLAB/Simulink. In addition, it is simulated to determine whether the WAMS can optimize the reliability of a 110 kV distribution grid. For this purpose, the local 110 kV distribution grid, the surrounding 380 kV transmission grid and the Phasor Measurement Units (PMU) on each node of the 110 kV grid were simulated. The distribution grid was modelled on the basis of real data and the transmission grid was modelled on the basis of data from the German Federal Environment Agency. Subsequently, various scenarios have been developed (A. Failure of nearby transmission line, B. Conductor temperature determination, C. Short-circuit localization) to test if the reliability of the simulated distribution grid is increased using PMUs.