Estimation of low‐frequency modes in power system using robust modified Prony

This letter presents a robust generalized correlation approach for monitoring of power system oscillatory modes. Due to the non-Gaussian nature of measurement noise, and presence of impulsive outliers, the wide-sense stationarity assumption of power system measurement data is violated even under ambient conditions thus limiting the effectiveness of conventional autocorrelation based approaches in mode metering. The fundamental definition of correlation function for power system measurements is extended to a generalized correlation function in order to incorporate higher order statistics into existing modal estimation technique. Simulations on synthetic and real-life test signals have been conducted to demonstrate the robustness of the proposed method.

This chapter presents the small‐signal stability of power systems operating in “steady state,” that is, the system stability of an equilibrium point. The ability of the power system to track the load changes requires the power system to be small‐signal stable, that is, a power system can stably move from one operating condition to a slightly different operating condition. The chapter discusses electromechanical modes in power systems and techniques to compute and identify the frequency and damping of these modes. The approach used is to develop linearized system models that are valid in a region about the equilibrium operating point. Electromechanical modes in a practical power system can be divided into three types: intraplant modes; local modes; and interarea modes. The chapter provides an overview of the development of linear models for nonlinear systems. There are two methods commonly used for generating linearized models: using analytical expressions, and using a numerical perturbation method.

Several major blackouts in the past have shown the need for advanced wide‐area monitoring and control (WAMC) techniques. Advanced synchrophasor visualization and monitoring can be realized with time‐referenced power system data that are collected by phasor measurement units (PMUs) using synchronized clocks. Presently, PMUs are being deployed around the world at a rapid rate for various power system applications. When a necessary number of PMUs are installed at optimal locations throughout the network, the complete state of the system can be observed. PMUs take real‐time measurements to determine the state of the power system and can be used to enhance state estimation efficiency. With PMUs in place, there are many control and protection schemes that can be implemented successfully to take preventive and corrective actions. These remedial action schemes (RASs) are classified by the IEEE Power System Relaying Committee (PSRC) as system integrity protection schemes (SIPSs). This work involved the development of a real‐time hardware test bed in order to analyze the transient stability of a simulated power system by using synchrophasors to visualize system stress across a transmission line with and without load‐shedding schemes. The real time digital simulator (RTDS®) was used to model the power system in real time. PMUs, a satellite‐synchronized clock, and a synchrophasor vector processor (SVP) were used to test the synchrophasor application. Copyright © 2010 John Wiley & Sons, Ltd.

Phasor measurement units (PMUs) are power system devices placed at various locations in electrical power network that provide the measurement of phasors of voltages and currents from the respective meters or instruments placed at locations. Data provided by the PMUs are used for system analysis and also help to analyze the sequence of events that may have contributed to the failure of the power system. The presence of bad data in PMUs is increasing in today’s power system due to the system complexity and associated issues. This will lead to inaccurate measurement of voltage magnitude and phase angle. Hence, it is important to detect the presence of bad data and identify the PMU which contains the error. In order to identify the bad data, state estimation is carried out to obtain the true state variables by the application of Load Flow Analysis (LFA). The application of Engineering Optimization is called into this work for improving the detection of bad data and its correction. Firefly optimization and particle swarm optimization techniques are developed for the above problem, and later results are compared with respect to the accuracy of results. The system is modeled in MATLAB platform.

Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions. To be specific, an adaptive weight assignment function to dynamically adjust the measurement weight based on the distance of big unwanted disturbances from the PMU measurements is proposed to increase algorithm robustness. Furthermore, a statistical test-based interpolation matrix ${H}$ updating judgment strategy is proposed. The processed and resynced PMU information are used as priori information and incorporated to the modified weighted least square estimation to address the measurements imperfect synchronization between supervisory control and data acquisition and PMU measurements. Finally, the innovation analysis-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track the system real-time states with good robustness and can address several kinds of BD.

Time synchronized phasors obtained using Phasor Measurement Units (PMU) spread across wide areas have revolutionized power system monitoring and control. These synchronized measurements must be accurate and fast in order to comply with the latest IEEE standards for synchrophasor measurements. The speed at which a PMU provides an output depends on the group delay associated with that PMU and the permissible group delay in-turn decides the utility of a PMU for either control or measurement application. Based on the group delay compensation techniques, in the literature, two individual types of PMUs, such as causal and non-causal PMUs have been introduced. This paper presents an approach where both causal and non-causal PMUs are combined in an integrated PMU architecture. This method not only illustrates the group delay performance of two PMUs in a single module, but also can be used for multiple functions. In this environment several PMU algorithms have been compared with respect to their group delays and their effect on the response time. Application of the integrated PMU architecture to a four-machine 10-bus power system has been demonstrated using a six-input PMU with three-phase voltage and current signals as inputs. Different causal compensation schemes are introduced due to the availability of voltage and current-based frequency and ROCOF signals. Impact of these compensation schemes on PMU accuracy is evaluated through the Total Vector Error (TVE) index. The influence of these compensation schemes on measurements like power and impedance is also investigated. Finally, outputs from the integrated PMU architecture are fed into a Power System Stabilizer (PSS) to control the small-signal stability performance of a power system during dynamic conditions.

The electrical power system is becoming more and more complex with the increasing demand of the electricity across the world, as the world is becoming the global village. The electrical power system must be reliable and safe enough to fulfil the energy requirements with the continuous supply of energy. The chances of power system's blackouts and outages are increasing with its increased complexity. So, there is a need of an efficient control system to make the power system more safe, efficient and reliable. Wide Area Monitoring, Protection and Control system (WAMPAC) is becoming an emerging technology for an efficient monitoring, protection and control of power system. Phasor measurement unit (PMU) is an integrated part of wide area monitoring, protection and control (WAMPAC) system, which can be used for monitoring, protection and control of complex electrical power systems. PMU gives the synchronized phasor measurements of voltage and current and can easily monitor and control even small disturbances in power system to protect the power system from any blackouts and outages before any fault occurs. In the proposed paper a PMU model is designed in MATLAB/Simulink and then PMU is used for power system protection and the comparative analysis are done with the conventional protection technique for an interconnected two-area network power system.

This paper proposes a method of selecting and/or locating phasor measurement unit (PMU) signals for monitoring critical oscillation modes in large power systems. A robust indicator, modal participation ratio, is introduced to identify critical PMU locations and signal channels, in order to monitor modes of interest to power system operators. This indicator is easy to compute in practice, and is theoretically rigorous based on linear control theory and spectral analysis. This indicator can suggest location and/or selection of PMUs in order to most effectively observe modes of interest to power system operators. The effectiveness and robustness of the algorithm is illustrated in both modified 68-bus system and 140-bus system.

ANALYSIS OF BAD DATA IN POWER SYSTEM STATE ESTIMATION UNDER NON-GAUSSIAN MEASUREMENT NOISE

The widespread implementation of Phasor Measurement Units (PMUs) on power systems has facilitated the development of accurate and fast dynamic state estimators (DSE), which helps to reliably achieve the real-time monitoring and control of the power systems dynamics. Dynamic state estimators are used by the investigators to estimate and identify the state variables and other parameters associated with the nonlinear dynamic models within the power systems, by using the measurements which are mainly provided by the PMUs. This paper primarily tries to present an innovative and robust dynamic state estimation approach when the PMU data are missing due to various reasons. The highly efficient Unscented Kalman Filter (UKF) algorithm is used to formulate the DSE. The simulation results on IEEE 14 bus system shows that the proposed algorithm remains robust and produce accurate estimates during the missing of PMU data coming from generator buses.

The widespread deployment of Phasor Measurement Units (PMUs) on power systems has facilitated the real-time monitoring of the power systems dynamics. Dynamic State Estimators (DSEs) are used by the investigators to estimate and identify the state variables and parameters of the nonlinear dynamic models within the power systems by using the measurements which are mainly provided by the PMUs. This dissertation addresses fundamental research on dynamic state estimation of the power systems and presents innovative and robust dynamic state estimation approaches for estimation/identification of the state variables/parameters associated with the nonlinear dynamic models within the power systems.

The relative phase position of AC voltages and currents in different parts of an electric power system determines the stability and the dynamic performance of the system. The introduction of phasor measurement units (PMUs) in power systems significantly improves the possibilities for monitoring and analyzing power system dynamics. In this paper a Recursive DFT algorithm is adopted for the development of PMU design with the help of Digital Signal Processor (DSP), Global Positioning System (GPS), voltage & current transformers and additional circuitry to get the benefits like reduced manufacturing cost, improved measurement accuracy and increased timely information. Once the desired functionality has been captured and simulated, using MATLAB/Simulink/Embedded Target for TI C2000 DSP environment code can be generated for the DSP. The developed Phasor Measurement Unit (PMU) provides phasor information (both magnitude and phase angle) in real time.

Operational practices of both power transmission and distribution grids are impacted by the increasing connection of renewable energy resources, electric vehicles and energy storage systems. A timely and accurate knowledge of the system state, coupled with a level of automation able to protect or control the system, enables a better operation of the electrical grids. In this respect, synchrophasor networks, might provide system operators with wide-area, synchronized, low latency, high refresh-rate measurements from phasor measurement units (PMUs). This thesis focuses on the design and validation of resilient synchrophasor networks in order to address some of the challenges that are preventing the adoption in real-fields of what proposed by the literature. First, the architectural layers of synchrophasor networks are described with particular focus on the time dissemination techniques suitable for phasor measurement units. Then, we propose a new data-pushing logic able to minimize the latency introduced at the concentration point without increasing the data incompleteness. The data-pushing logic is validated in three real synchrophasor networks adopting different telecom infrastructures (i.e., 4G-LTE, optical fiber links and twisted pairs). In the context of reliable operation of synchrophasor networks, we propose an algorithm able to deal with intentional or unintentional bad data measurements. We also impersonate an attacker and we show that it is possible to forge delay attacks undetectable by state-of-the-art bad-data detection algorithms that can lead to physical grid damage. We use the proposed bad data algorithm as an effective way of neutralizing these attacks. The IEEE C37.118 Class-P Std compliant synchrophasor extraction algorithm adopted in the real-fields is also implemented and validated in a GPS-synchronized real-time simulator. The simulated PMUs are used to validate two applications for the real-time protection and control of electrical networks by means of synchrophasor technology. The first one is a protection scheme that relies on PMU-based real-time state estimation processes to detect a fault and identify the faulted line. Then, we validate in a real-time hardware-in-the-loop (HIL) setup, the Grid Explicit Congestion Notification (GECN) voltage control mechanism for distribution networks, already presented in the literature. We show that, by leveraging on the accurate knowledge of the system state, GECN is able to control the state of the system in time-scales of seconds, in order to maintain its voltage level within predefined limits.

Population of Phasor Measurement Units (PMUs) in power systems are increasing day by day as PMUs measure the electrical quantities more accurately with time-stamping. The measurements done by PMU can be used for monitoring, controlling and for state estimation of the power system. Since the installation of PMUs demand high capital cost, their number and location to be chosen optimally is by minimizing investment without losing observability of the system. In this paper Integer Programming techniques used to solve Optimal Placement of PMU (OPP) problem. The OPP problem is solved for normal power system as well as for a few contingency conditions like one PMU outage, considering zero injection bus, outage of single line on various standard IEEE Bus Systems. The work is also trying to place PMUs under planned islanding in certain standard networks.

The Phasor Measuring Units provide synchronized measurements for monitoring and control of Power System State for Power System protection. The high PMU cost and installation cost are main reasons for minimizing the number of PMUs and their optimal placement should ensure Power System full Observability. This paper presents the investigation of Optimal placement of Phasor Measuring Units (PMU) and the use of reduced number of PMUs for ensuring Power system full observability. The Optimal PMU Placement (OPP) problem has been tackled considering different cases like with and without conventional measurements and zero injection buses. The OPP is considered for different contingencies such as single PMU or line outage to ensure full system observability. The PMU Channels, which limit the number of measurements at the installed bus is also taken into account in OPP formulation. MAT LAB Simulations are carried out by Binary Integer Linear programming (BILP) method and tested on standard IEEE 14-bus, IEEE 30-bus, IEEE 57-bus and IEEE 118-bus systems. The results presented were compared with the recent literature and found the effectiveness of proposed method with regard to number of PMUs and execution time is appreciable.