Study and Simulation of Phasor Measurement Unit for Wide Area Measurement System Ms.Darsana M. Nair Mr. Rishi Menon Mr. Aby Joseph PG Scholar Assistant Professor Principal Engineer Dept. of EEE Dept. of EEE Power Electronics Group Saintgits College Of Engineering Saintgits College of Engineering C-DAC Kottayam, Kerala Kottayam, Kerala Trivandrum, Kerala Abstract Power system is now operating in a more complicated situation and is facing more challenges than ever before. Synchronized phasor measurements have become a prominent technology for real time monitoring of power system. At present PMU is the most sophisticated timesynchronized tool available to power engineers and system operators for wide area applications. It will improve visibility and provide real time monitoring, protection, and control of the system. This tool has been made possible by advancements in computer technology, and availability of GPS signals. This paper describes the modeling and testing of PMU in MATLAB/Simulink. Keywords: - Global positioning systems (GPS), Phasor measurement units (PMU), Wide Area Monitoring Systems (WAMS), Coordinated Universal Time (UTC). 1. INTRODUCTION The power system networks are recently being equipped with the synchrophasor based Wide Area Monitoring System (WAMS). The conventional Remote Terminal Units (RTUs), forming part of the Supervisory Control And Data Acquisition (SCADA) system, provide only unsynchronized root mean square values of the currents and the voltages. A synchrophasor based WAMS, consists of geographically placed Phasor Measurement Units (PMUs), which provide the measurements of both the magnitude and the phase angles of the voltage and the current signals. These measurements are time-synchronized using Global Positioning System (GPS) with an accuracy of 1 ms [5]. The major applications of the phasor measurements include real-time power system monitoring, protection and control. The phasors, measured at the same time instant, provide a snapshot of the power system network and by comparing the snapshots of the consecutive time instants, not only the steady state but also the dynamic states of the critical nodes in the network can be tracked. The Wide Area Monitoring System (WAMS) is primarily used for managing the grid reliability by continuously monitoring the status of the grid through PMU deployed at specific location in the transmission network. The goal of wide area monitoring systems is to make the power system less immune to catastrophic failures and to reduce the severity of such failures when they do occur. PMUs are the main building blocks in the synchrophasor based WAMS. They provide phasor data with faster refreshment rate. The information provided by them, i.e., the voltage and the current phasors, are processed at the Phasor Data Concentrators (PDCs) to extract the relevant information about the system operating condition. PMUs are devices able to sample high speed, timestamped snapshots of voltage and current in phasor format, frequency and rate of change of frequency. Being synchronized to Coordinated Universal Time (UTC) through Global Positioning System (GPS) signal, these devices are able to provide real time measurements recorded from different parts of the power system, giving this way the potential to timealign these measurements and have a precise and representative view of the power system. Phasor Data Concentrators (PDCs) are devices able to concentrate measurements from different PMUs, time-align them and communicate them as a single stream to other PDCs or to monitoring and control devices. In this paper following sections were presented. Section II describes Phasor and PMU functions. Section III focuses the simulation of PMU to perform WAM functions. WAM functions include voltage monitoring, Phase angle monitoring, Frequency monitoring, Rate of Change of Frequency monitoring etc. 1
II. PHASOR AND PMU FUNCTIONS A phasor is a vectorial representation of an ac signal with sinusoidal waveform. It is well known that a sinusoid can be written using the equation: X (t) = Xm cos (ωt + Φ) (1) And is commonly represented as the phasor as shown in Equation (2): X = (Xm/ 2) e jφ (2) = (Xm / 2) (cos Φ + j sin Φ) = X r + j X i In the above equation, ω is the angular velocity θ is the initial angle between a reference point and the positive peak. X m is the peak amplitude of the waveform. The magnitude of phasor equals to the root mean square (RMS) value of the waveform which is (X m / 2). The subscripts r and i signify real and imaginary parts of a complex value in rectangular components. The value of Φ depends on the time scale, particularly where t = 0. It is important to note this phasor is defined for the angular frequency ω; evaluation with other phasors must be done with the same time scale and frequency. A phasor representation corresponds to a pure sinusoid. However, in real world situations, ac signals are typically distorted by the presence of harmonics. As the analysis of a signal is always focused on specific frequency components, the extraction of the component of interest is important. In a digital measurement system, this is usually realized by the Discrete Fourier Transform (DFT) or the Fast Fourier Transform (FFT). A time span for the measurement is selected, which is known as the time window. PMUs continuously sample the waveform using a moving time windows and update the value of the phasor that is output on a continuous basis. A phasor is a complex number that represents both the magnitude and phase angle of the sine waves found in electricity. Phasor measurements that occur at the same time are called synchrophasors, as are the PMU devices that allow their measurement. In typical applications phasor measurement units are sampled from widely dispersed locations in the power system network and synchronized from the common time source of a global positioning system (GPS) radio clock. Synchrophasor technology provides a tool for system operators and planners to measure the state of the electrical system and manage power quality. Under this definition, Φ is the offset from a cosine function at the nominal system frequency synchronized to UTC. A cosine has a maximum at t = 0, so the synchrophasor angle is 0 degrees when the maximum of x(t) occurs at the UTC second rollover (1 PPS time signal), and 90 degrees when Fig. 1.Convention for synchrophasor representation 2 the positive zero crossing occurs at the UTC second rollover (sin waveform)[2]. Figure 1 illustrates the phase angle/utc time relationship. Phasor Measurement Unit There is no uniform structure adopted for commercially available PMUs as several companies provide such offerings. However, the functional blocks of a typical PMU are generic, and the common components are shown in figure 2. As shown in Figure.2, analogue input signals, which are derived from a scaled signal from voltage and current transformers are initially passed through anti-aliasing filters. A PMU may collect data from different locations in the system on a simultaneous basis and normally requires data from all three phases to extract the positive sequence component,
which is what is normally of interest and contains information that can be used to assess the state of the power system. PMUs are synchronized by satellites through a GPS receiver. The time accuracy of such system is typically in the order of a few hundred nanoseconds. Time stamps are created by the GPS receiver as a label of measurement and for future comparison of measurements. The other important function of the GPS receiver is that it can generate a one pulse-per-second signal to a phase-locked oscillator to synchronise and lock the phase of the sampling clock. Synchrophasors measure voltages and currents at principle intersecting locations (critical substations) on a power grid and can output accurately time-stamped voltage and current phasors. Because these phasors are truly synchronized, synchronized comparison of two quantities is possible, in real time. These comparisons can be used to assess system conditions-such as; frequency Fig 2.Functional block diagram of PMU. III. SIMULATION OF PMU. platform. The system was modeled in LABVIEW For the study of functionality of PMU, its [3][4].MATLAB/ Simulink model of PMU is model is simulated in MATLAB/ Simulink developed as shown in figure 3. Fig. 3. MATLAB/ Simulink Model for WAMS. 3
SYSTEM DESCRIPTION Here a three phase source (415V, 50 Hz) is connected to a three phase load. PMU model is placed between the source and load. It measures the voltage phasor, current phasor, frequency and rate of change of frequency. 1. Voltage Phasor Measurement Block: This subsystem receives the three phase voltage signal and extracts each phase voltages V a, V b and V c. Then it converts this voltage signal to its phasor representation, i.e., in magnitude and phase angle form. This is shown in figure.3. 2. Current Phasor Measurement Block: This subsystem receives the three phase current signal and extracts each phase current I a, I b and I c. Then it converts this current signal to its phasor representation, i.e., in magnitude and phase angle form. This is also shown in figure.3. 3. Frequency Measurement Block: This subsystem basically contains a phase locked loop which can be used to synchronize on a set of variable frequency, three-phase sinusoidal signals. It outputs the measured frequency in Hz (ω /2pi) and ramp ω.t varying between 0 and 2*pi, synchronized on zero crossings of the fundamental (positive-sequence) of phase A. This signal is the given to ROCOF block. 4. Rate of Change of Frequency Measurement Block: The output signal from the frequency measurement block is differentiated to obtain the rate of change of frequency (ROCOF). Figure 4a and b shows the subsystem for magnitude and phase angle measurement. Fig.4a. Subsystem for magnitude measurement We can measure frequency and rate of change of frequency through PMU. Change in frequency can shows the change in impedance of power system components. We are able to observe stability of system through rate of change of frequency monitoring. Fig.4b. Subsystem for phase angle measurement According to the convention for phasor representation phase angle φ is the offset from a cosine function at the nominal system frequency synchronized to UTC [2]. Thus a three phase balanced sinusoidal voltage waveform represented as: V a = V m sin ωt V b = V m sin (ωt-120 ) (3) V c = V m sin (ωt+120 ) Can be represented as phasor form (according to IEEE synchrophasor convention) as below. V a = V m / < -90 V b = V m / < 150 (4) V c = V m / < 30 4
Fig. 5. Amplitude variation with change in frequency from 50 Hz to 49.95 Hz Effect of change in frequency Here the nominal frequency of the source is 50 Hz. If there is any change in the frequency from its nominal value there will be a corresponding change in magnitude and phase angle of voltage. For verifying the effect of change in frequency, the frequency of input wave is changed to 49.95 Hz. The variation in magnitude is shown in figure 5. PMUs create a picture showing the stability status of the nodes in the monitored area. PMUs take this picture at the same reference time. Using real-time information from PMUs and automated controls to predict, identify, and respond to system problems; a smart grid can automatically avoid or diminish power outages, power quality problems and supply disruptions. The relevance of phase angle monitoring comes into picture only when we are able to compare the phase angles of two different nodes in a network. For this we have to place two PMUs at two critical points in a power system network. Then the difference in phase angles obtained from these two points will give a clear idea about the stability of the monitored area. By continuously monitoring, phase angle monitoring enables access in real time to the accurate phase angle difference between any pair of buses. With this we can monitor angle separation or rate-of change of angle separation between two buses or two parts of a grid to determine stress on the system. Another important application of phase angle monitoring is during restoration. The phase angle value of an opened tie line or an opened circuit breaker would help an operator in circuit breaker closing. Closing would take place only if the phase angle was below a preset threshold. For the study of this, a two bus system is modeled in MATLAB/Simulink. Figure 5 shows the model of such a system. Here PMUs are placed at bus 1 and 2 to measure the voltage phasors at nodes 1 and 2 respectively. V a1, V b1, V c1 and V a2,v b2,v c2 are the three phase voltages at bus 1 and 2 respectively. Under normal conditions the phase angles of two buses are as we obtained in the simulation study. If there is any abnormality in any of the buses, there will be a corresponding change in the phase angles of the affected bus. 5
Fig. 6. Simulink Model of Two bus system with PMUs placed at each bus IV.CONCLUSION Performance of PMU is simulated and verified in MATLAB/Simulink. The model developed gives phasor information i.e., information about both magnitude and phase angle of the input waveform. The time stamped information obtained from the PMU can be integrated with the conventional SCADA system to make the operation of the grid smarter and efficient. Also this information can be used for the proper selection and coordination of relays to make WAM protection and Control. REFERENCES [1] Ranjana Sodhi, S.C.Srivastava, A simple scheme for wide area detection of impending voltage instability, IEEE Transactions on Smart Grid, Vol. 3, No. 2, June 2012. [2] IEEE Standards for Synchrophasors for Power Systems, IEEE Power & Energy Society, Sponsored by the Power System Relaying Committee, IEEE Std C37.118.1-2011. [3] Vipin Krishna R, S. Ashok, Megha G Krishnan, Synchronized Phasor Measurement Unit, International Conference on Power, Signals, Controls and Computation (EPSCICON), 8 10 January 2014. [4] S. Mondal, Ch. Murty D. S. Roy, D. K. Mohanta, Simulation of Phasor Measurement Unit (PMU) Using Labview. 14th International Conference on Environment and Electrical Engineering (EEEIC- 2014), Krakow pp-164-168, 10-12 May 2014. [5] A.G. Phadke and J.S.Throp, Synchronized Phasor Measurements and their applications, Springer, 2008. 6