148 research outputs found

    Synchrophasor Assisted Efficient Fault Location Techniques In An Active Distribution Network

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    Reliability of an electrical system can be improved by an efficient fault location identification for the fast repair and remedial actions. This scenario changes when there are large penetrations of distributed generation (DG) which makes the distribution system an active distribution system. An efficient use of synchrophasors in the distribution network is studied with bidirectional power flow, harmonics and low angle difference consideration which are not prevalent in a transmission network. A synchrophasor estimation algorithm for the P class PMU is developed and applied to identify efficient fault location. A fault location technique using two ended synchronized measurement is derived from the principle of transmission line settings to work in a distribution network which is independent of line parameters. The distribution systems have less line length, harmonics and different sized line conductors, which affects the sensitivity of the synchronized measurements, Total Vector Error (TVE) and threshold for angular separation between different points in the network. A new signal processing method based on Discrete Fourier Transform (DFT) is utilized to work in a distribution network as specified in IEEE C37.118 (2011) standard for synchrophasor. A specific P and M classes of synchrophasor measurements are defined in the standard. A tradeoff between fast acting P class and detailed measurement M class is sought to work specifically in the distribution system settings which is subjected to large amount of penetrations from the renewable energy

    Parallel detrended fluctuation analysis for fast event detection on massive PMU data

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    ("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment

    Survey on synchrophasor data quality and cybersecurity challenges, and evaluation of their interdependencies

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    Synchrophasor devices guarantee situation awareness for real-time monitoring and operational visibility of smart grid. With their widespread implementation, significant challenges have emerged, especially in communication, data quality and cybersecurity. The existing literature treats these challenges as separate problems, when in reality, they have a complex interplay. This paper conducts a comprehensive review of quality and cybersecurity challenges for synchrophasors, and identifies the interdependencies between them. It also summarizes different methods used to evaluate the dependency and surveys how quality checking methods can be used to detect potential cyberattacks. This paper serves as a starting point for researchers entering the fields of synchrophasor data analytics and security

    Parallel detrended fluctuation analysis for fast event detection on massive PMU data

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    ("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment

    Cloud Computing Strategies for Enhancing Smart Grid Performance in Developing Countries

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    In developing countries, the awareness and development of Smart Grids are in the introductory stage and the full realisation needs more time and effort. Besides, the partially introduced Smart Grids are inefficient, unreliable, and environmentally unfriendly. As the global economy crucially depends on energy sustainability, there is a requirement to revamp the existing energy systems. Hence, this research work aims at cost-effective optimisation and communication strategies for enhancing Smart Grid performance on Cloud platforms

    Visualization And Mining Of Phasor Data From Optimally Placed Synchrophasors In A Smart-Grid

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    Synchrophasors, or also known as Phasor Measurement Units (PMUs), are the state- of-the-art measurement sensor that gather key sensor parameters such as voltage, frequency (f), current (i), and phase angle (ϕ) to monitor the state of an electric grid. The significant feature of a synchrophasor is in its ability to provide real-time streaming data from smart grid. The sampling rate of PMUs ranges from 30 samples to a maximum of 120 samples per second. With such large date-rate, the operations of the power-grid is known with high granularity. However, utilities face certain challenges with synchrophasor measurements. One of the common challenge with synchrophasor is the selection of location to place them in the grid. A synchrophasor placed on a bus is capable of measuring currents, voltages, phasor and frequency information on the entire transmission line incident to that bus. Furthermore, neighboring buses also become observable (i.e. adjacent bus voltage equations are solvable) using Ohm’s law, Kirchhoff’s Voltage Law (KVL) and Kirchhoff’s Current Law (KCL). Thus, it is not necessary to place PMUs on every single bus of the power-grid. Synchrophasors are expensive units and depending on vendor type, the number of measurement channels and features, the cost per unit can increase. There are several optimal solutions proposed to minimize the cost function to place the synchrophasors. Studies often ignored other metrics such as reliability, and security. This can jeopardize the reliability of the power-grid. Thus, this thesis work focus on a multi-objective problem that include reliability, cost, energy, and distance. This research proposes a criteria called as Optimal Redundancy Criterion (ORC) based on Linear Programming (LP) methods to find an optimal solution for the placement problem. Although, synchrophasors provide real-time information about the grid, the system operators need to identify, classify and analyze fault or anomalies in the power-grid. Such detection of the faults will improve the situational awareness of the power-grid. This research addresses such challenges by developing data mining algorithms for effective visualization and control of data. The secondary goal is accomplished by implementing a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to IEEE test system and phasor data from openPDC framework. The scalability and decision making process for large scale utility test systems using DBSCAN is also investigated

    Synchrophasor-based predictive control considering optimal phasor measurement unit placements methods

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    A blackout is the total collapse of an electric power grid, due to the inability to balance load demand and power generation. Blackouts generally develop from a series of unattended voltage stability problems, stemming from a combination of human and operational errors, and may have fatal consequences. The report on the blackout incident of August 14 2003, which affected parts of the United States and Canada, particularly emphasised the need for improved wide area monitoring of the grid. In the United Kingdom, the recent blackout of August 9 2019 has reinforced the need for increased grid visibility and data recording. These have led to an ever-increasing interest in a family of measurement devices known as Wide Area Monitoring Systems (WAMS). The most popular device in this family is the Phasor Measurement Unit (PMU), which report voltage and current phasors at rates up to 60 samples/second. PMUs may be used to monitor all or part of the grid to prevent future blackouts with timely control actions. The goal is to ’See it fast: Keep it calm’. Wide-area monitoring enhances the possibility of visualizing the electric grid as a single system. This has led to the extension of the application of WAMS from mainly monitoring to wide-area control in relatively recent research efforts. This work explores how predictive control technique may be used to automate the control of power systems voltages at secondary level using an array of synchrophasors. The intuition is to develop a model-free (or synchrophasor-based) control algorithm, which reduces, as much as possible, the need for human interventions in the mitigation of voltage problems, and is fast enough to be applied online in real-time. Although model-based techniques can be applied online, they may not be fast enough for real-time applications. In addition, this method may depend on components’ parameters, which may not be available in practice. The work is split into two parts. First, novel WAMS deployment algorithms —using multi-variable, multi-objective optimization set-ups, which return optimal placement solutions —are presented. Formulations are described for multi-stage deployments given a limited budget and for application-focused cases. Practical issues which may develop are anticipated and addressed. The formulations were shown to return optimal solutions with qualitative placement specifications. In the second part, methods of realizing models from input-output relationships are developed and described. The first involved a method numerical derivatives based on data that are sampled at PMU rates. This may be seen as a viable alternative to the use of trajectory sensitivity, especially for real-time control design. In the second, subspace algorithm are used to realise models. The process is comprehensively described for secondary voltage regulation in normal and emergency situations. The approach is demonstrated on a number of IEEE test cases and the controller’s performance were found to be satisfactory for non-viable voltage regulations. This research work is particularly relevant in a number of ways. Chief among these is that voltage control problems may be handled in real-time without a knowledge of the model parameters. The model-free approach particularly desired since increasing integration of renewable energy sources means that the electric grid is becoming increasingly complex. Another is that the placement algorithms describe all various practical issues around the measurement-based design, which utilities may found useful, especially when they wish to address budget limitation and device compatibility issues
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