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    Slides Compiled from Various Sources by TLC Engineering Solutions (Pty) Ltd

    Slides Compiled from Various Sources by TLC Engineering Solutions (Pty) Ltd

    2nd Smart Grid - Distribution Automation Conference

    Network Sensor and SystemMonitoring Technologies

    Terry CousinsDirector, TLC Engineering Solutions

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    Material Copyright This course was compiled using material from a variety of

    sources. These are listed in the reference section. The reference material includes textbooks, articles from

    various journals, national and international standards,

    utility and end user codes of practise and standards, powerresearch institute presentations and manufacturer whitepapers, presentations and datasheets

    The material is copyright as per the various authors and isprovided for personal study purposes.

    Reference material used should be cross checked foraccuracy and relevance before being used in any designs.

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    Network Sensor and SystemMonitoring Technologies Agenda

    Application of Sensor Information Sensor Technologies

    Sensor Developments Communication and Sensor Data Collection Security Power Harvesting Algorithms and Data Visualization

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    Transmission Line and SubstationChallenges

    Existing transmission lines and substations are aging while the requiredreliability is increasing and the availability of clearance to performmaintenance is decreasing.

    Need to maximize the utilization of the system, and thereby operate closerto the edge of reliability

    Need to increase the available capacity of the existing transmission system An increasing penetration of distributed generation and power electronics The shift to an intelligent grid with less traditional oil and iron-ore

    equipment and to more controllable solid-state and SF6 technologies. Thisnew fleet of components will include automated smart diagnostics andcondition assessment enabling the shift from resource-intensive time-based maintenance to more cost-effective condition-based maintenance.

    Need to integrate increasing amounts of renewable energy. These sources,especially wind, can be highly variable, intermittent and unpredictable.

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    Application of Sensor Information Operations real-time power flow especially with DG Safety - monitoring and communication of equipment conditions

    continuously Personnel Deployment to prevent or repair an outage Condition Based Maintenance - enables maintenance actions to be

    initiated at appropriate times Asset Management - improved knowledge of the condition of

    equipment and stresses that they have been subjected to Increased Asset Utilization - real time knowledge of the

    components condition allows for higher dynamic ratings Forensic and Diagnostic Analysis sensors provide the information

    needed to identify the root cause Operations Improvement - increased utilization of the grid is

    possible if contingency analyses performed probabilistically

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    Phase Shift Caused by Self-inductance(2nH / 200 Shunt)

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    Current Transformer (CT) Transformer which converts the primary current

    into a smaller secondary current. CT is the most common sensor CT can measure up to very high current and

    consumes little power CT typically have a small phase shift associated

    with it (0.1-0.3) due to the magnetizing current CT ferrite material used in the core can saturate

    at high current

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    Hysteresis Curve of a Ferrite Material

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    CT Saturation CT saturation can occur when current surges

    beyond a CTs rated current, or when there issubstantial dc component in the current (e.g.

    when driving a large half-wave rectified load) Solution to the saturation problem is to use

    ferrite material with very high permeability suchas using Mu-metal core.

    This type of CTs has inconsistent and largerphase shift compared with the conventional ironcore CTs.

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    Hall Effect Sensor There are two main types of Hall effect sensors:

    open-loop and closed-loop implementation. Most Hall effect sensors found in energy meters

    use open-loop design for lower system cost. Hall effect sensor has outstanding frequency

    response and is capable of measuring very largecurrents

    The output from Hall effect sensor has a largetemperature drift and it usually requires a stableexternal current source.

    Needs a power supply higher cost than CT

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    Current Sensing - Hall effect & Induction

    http://www.nktechnologies.com/current-sensing.html

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    Rogowski Coil A simple Rogowski coil is an inductor which has mutual

    inductance with the conductor carrying the primarycurrent.

    Rogowski coil is typically made from air-core coil so intheory there is no hysteresis, saturation, or non-linearity

    The basic operating principle of a Rogowski coil is tomeasure the primary current through mutual inductance

    The Rogowski coil relies on measuring magnetic fieldwhich makes this type of current sensor susceptible toexternal magnetic field interference compared with theCT

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    Linearity Accuracy of Rogowski Coil

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    Rogowski Coil to Measure AC or FastTransient Currents

    Simple to retro-fit - the clip-around sensor is thin,lightweight, flexible and robust Coil size is not dependant on the magnitude of the

    current Non-Intrusive Wide-bandwidth with predictable frequency response,

    ideal for power quality measurement or monitoringcomplex waveforms

    Galvanic isolation Excellent linearity Capable of huge overload currents without damage Immune to DC Currents

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    Comparison of Current Sensing Technologies

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    Magneto-Optical (MO) Effect

    Magneto-optical phenomenon is an interactionbetween light and a magnetic field.

    The Faraday effect or Faraday rotation is amagneto-optical phenomenon

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    Fibre Optic Current Sensor (FOCS) In 2013 ABB launched a 420 kV Disconnecting Circuit

    Breaker with integrated FOCS. With FOCS replacing the conventional current

    transformer the engineering and design of the

    substation is simplified, since one FOCS replaces manycurrent transformer cores. Since utilizing FOCS reduces the material needed and

    eliminates the need of additional insulation medium, a420 kV DCB with integrated FOCS can reduce asubstations footprint with over 50 % compared to aconventional solution of live tank breakers withdisconnectors and current transformers

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    DC Breaker with FOCS

    http://en.wikipedia.org/wiki/File:DCB_with_FOCS.jpg

    http://upload.wikimedia.org/wikipedia/commons/b/bf/DCB_with_FOCS.jpghttp://upload.wikimedia.org/wikipedia/commons/b/bf/DCB_with_FOCS.jpg
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    Voltage Transformer (VT / PT)

    Similar to conventional transformer with careto minimise errors and power transformed islow

    Input to output proportional to turns ratio

    Widely used

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    Equivalent Circuit Model of a VoltageTransformer

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    VT Errors

    Voltage (Ratio) errors Burden errors

    Phase angle errors Saturation Frequency Response

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    Normalized VT Voltage Ratio vs. PhaseShift Angle

    Phase Shift (degrees)

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    VT Ferroresonance

    Star connected VTs on ungrounded powersystems VT is inductive Capacitance to ground Ferroresonance can occur when X L = XC

    Causes higher VT voltages and saturation Results in higher VT currents

    Overheating VT Failure Add damping resistor

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    Resistive Potential Divider

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    Capacitive Voltage Divider

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    The Electro-Optic (EO) Effect

    The electro-optic (E-O) effect is a 2nd-ordernonlinear optical effect that results in arefractive index that is a function of theapplied electric field (voltage)

    Pockels Effect Kerr Effect

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    Optical Voltage Sensors (OVS)

    Can use conventional sensor with opticaloutput

    Use linear electro-optic (Pockels) effect essentially electric field sensors

    Various means of getting relationship betweenapplied voltage and electric field

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    170 kV CircuitBreakers with

    IntegratedOptic

    Transducers

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    Phasor

    Phasor: A sinusoidal signal can be representedby a cosine function with a magnitude A,frequency , and phase

    5

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    Phase Measurement

    Angle between voltage and current representsflow of active and reactive power

    Angle between voltage or currentmeasurement devices at various parts of thegrid can be used to detect abnormalwaveshapes or fault conditions

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    Phase Angle Difference ( ) of Voltage Sinusoidsat the Ends of a Transmission Line

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    Power Flow

    Two factors determine power flow: theimpedance of a line and the difference in theinstantaneous voltages at its two ends

    The power flow on a line varies directly withthe phase angle difference (or more preciselythe sine of the phase angle difference) and

    inversely with the lines impedance

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    Synchrophasor P,Q flow can be computed from the

    synchronized measurement of the adjacentbus voltage phasors at the same time instant

    The two voltage phasors have to be measuredat exactly the same time

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    Phasor Measurement Unit (PMU)

    PMU) has been defined by the IEEE as adevice that produces Synchronized Phasor,Frequency, and Rate of Change of Frequency

    (ROCOF) estimates from voltage and/orcurrent signals and a time synchronizing signal Phasor Measurement Unit (PMU) A

    transducer that converts three-phase analogsignal of voltage or current intoSynchrophasors

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    PMU Instrumentation

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    PMU Deployment

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    Insulation

    There could be no electrical powerdistribution without electrical insulation

    The higher the potential, the greater the levelof insulation required

    The life span and consequently the ability ofelectrical equipment to operate reliably isfundamentally determined by the condition ofthe insulation.

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    Insulation Measurement

    Offline Insulation Resistance AC and DC overvoltage testing Dissipation Factor / Loss factor / Tan Surge and impulse tests Partial Discharge (PD)

    On-line PD Current signature analysis

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    Inception and Extinction of PartialDischarge

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    On-Line PD Monitoring

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    Temperature

    Electrical equipment dissipates heat as anormal part of its operation fixed losses +load dependent losses.

    Insulation life is dependent on the operatingtemperature. (Life halves for every 10 deg Cabove rated insulation temp)

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    IR Substation Monitoring

    Infrared thermographydetects hot spotsproduced when there is

    an electrical anomaly NB - Infrared cannot

    detect the presence ofcorona discharge useultrasonicmeasurement

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    Smart Sensors

    Stand alone sensors thatare self powered oremploy energy harvesting

    and communicatewirelessly

    They can be deployed

    with minimalinfrastructure

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    Smart Sensor Examples Transformer-3D Acoustic Emissions -detection and location

    of gassing sources in power transformers and LTCs Transformer-Acoustic Fibre Optic - measurement of internal

    partial discharges using fibre optics installed in high riskregions of a transformer

    Conductor RF Temperature and Current Sensor - sensorrecords overhead transmission conductor temperaturesand current magnitudes and wirelessly transmits theinformation for rating applications. These sensors powerharvest from the magnetic field.

    Overhead Insulator RF Leakage Current Sensor- measuresthe leakage current levels and provides an indication ofwhen to wash insulation or when a high risk of flashoverexists

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    New Sensor Developments

    Ongoing R & D to

    Identify and develop new sensor technologies Improve cost effectiveness Increase reliability Understand and expand applications

    d

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    Communication and Sensor DataCollection

    Substations Wired Wireless Sensor Mesh Wireless Point to Point

    Transmission Lines Direct Communication from Sensors (Radio / Satellite,

    GSM) Acquire, store & transfer during periodic inspection Wireless Transmission Line Hub Transmission Line Robot Mesh / Daisy Chain

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    Wireless Sensor Networks (WSNs) Sensor networks capture valuable data for controlled

    networks, integral to smart grid development Wireless Multimedia Sensor Networks include various high-

    tech researched sensors, multimodal cameras (radiationdetection, sunlight, wind, temperature, etc)

    Low Cost compared to wired counterparts (wiring costincluded)

    Currently Utilized in military applications, environmentalmonitoring, commercial and human centric applications

    Smart Grid is about information sensors provide all theinformation

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    Traditional WSN

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    Smart Grid WSN Deployment topology will most likely not use a single hop

    to transmission gateway Data Processing all data should be forwarded directly to

    control station Technology advancement in energy less sensitive energy

    usage = less concern for protocols and algorithms becausebattery life significantly longer

    Remote maintenance and configuration Harsher electrical deployment environments Quality Of Service (QOS) for application specific WSNsbecomes difficult to prioritize High security requirements

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    Smart Grid WSN

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    Traditional vs. Smart WSN

    Traditional WSN Smart Grid WSN

    One hop transmissionfrom gateway

    Multiple sensor hopsbefore transmission

    Physical Reconfigurationof devices

    Remote Reconfigurationof devices

    Relay data informationthrough routers

    Data processing, QOSand delivery highlyimportant

    Secure enough toprevent information leaks(reactive)

    Highly secured,(proactive) security

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    Wireless Security (CIA)

    Data Confidentiality not possible to access /intercept and imitate sensor data

    Data Integrity - no unauthorized adjustment of

    data. Not possible to get old data or inject olddata into a new network Data Availability - not possible to destroy

    communications links in WSNs, effectivelymaking them useless. e.g. DOS attacks, jamming etc.

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    Sensor Powering

    Sensors require a power source to measureand communicate results.

    A 110/220V AC power supply is not always

    available even in many substations andcertainly not on transmission structures. Two solutions exist

    high density non-rechargeable batteries power harvesting and storage of energy from the

    environment

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    Power Harvesting Technologies

    Solar Vibration Magnetic and Electric Fields Thermal Differences Radio Frequency (RF) Energy

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    Al ith d D t Vi li ti

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    Algorithms and Data Visualization Important components for developing sensor

    applications relate to the need to output usefulinformation based on the sensor data collected and thevisualization of this information.

    This is achieved by first developing algorithms thatrelate to components condition, rating or actions, andsecond, by filtering out noise from results

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