CONTENTS

Objectives of Project

Abstract

Chapter – 1

1.1 Introduction1.2 Underlying motivation for synchronized measurements to be performed on a PMU1.3 Use of Synchrophasor(PMU)data1.4 Challenge faced in implementation of PMU

Chapter – 2 -

2.1 Block diagram of PMU

2.2 Performance measures for PMU

2.3 Synchro pahsor data collection

Chapter – 3 -

3.1 Equipment used in PMU

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OBJECTIVES OF THE PROJECT

To design a PMU architecture comprises of 5 major blocks

i. Noise eliminationii. Phase estimation iii. Frequency estimationiv. Fundamental component estimationv. Phase shift estimation

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Abstract:

In this project we are going to design architecture of PMU for measurement of voltage

and currents of 3 phase lines of substation. With the help of pmu we can continuously

monitor signal of various substation with synchronization of pmu with GPS.

The last decade has seen an intensified effort towards an improved, technologically advanced

electric grid. This effort is largely in part to the need for cleaner and renewable sources of

energy. Another motivator for this “smarter grid” is the need for a more reliable and

efficiently operated of the wide scale electric infrastructure. The impact of these changes can

expect to be seen at both the transmission and distribution level. At the transmission level

Phasor Measurement Units(PMU) also known as synchrophasor data has emerged as one of

the most enabling technologies for the smart grid movement. These devices measure and time

synchronize, the magnitude and phase angle of the electrical quantities over wide areas of an

electric grid. These measurements are then made available to utilities and system operators to

facilitate new and improved applications that foster enhanced grid reliability, security and

efficiency.

Synchrophasor data provides increased visibility into the phenomenon occurring within the

electric grid, as measurements are taken at rates up to 60 Hz. This is a significance

improvement compared to traditional Supervisory Control and Data Acquisition

systems(SCADA) which operate at a rate of once every 2 to 5 seconds. This increased data

rate therefore allows measurement of frequency estimation, voltage, current phasor

estimation, which is not possible in SCADA . These applications can vary from real-time

operation to offline applications for post-event analysis and planning. Some of the more well

known of these applications are state estimation, inter-area oscillation, and wide area

monitoring and control.

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Chapter-1

1.1 INTRODUCTION

Phasor Measurement Unit (PMU)

A PMU is a unit that monitors phasor measurements on a 3 phase system- line voltages, line

currents, at specific time points in a power system. The PMU outputs measurements at 60

times per second. Such devices have been used in Power systems for Transmission and

Distribution for myriad applications. Its primary purpose is to act as a distributed sensor in a

power system. PMUs make real time monitoring possible at many points in a distribution

system.

The formal Definition of PMU in accordance with IEEE1334 –

A device that produces Synchronized Phasor, Frequency and Rate of change of

Frequency(ROCOF) estimates from voltage and current signals and a time synchronizing

signal.

The time synchronizing signal was recognized early as the GPS clock signal. Any PMU

deployed in areas where the GPS signals are unavailable will have to fall back on the highly

accurate IEEE 1588 signals. In its early days the PMU units were also referred to as

Synchrophasor units – especially in USA/Canada- Synchrophasor- Synchronized Phasor.

This is not the case India- where the term is restricted to PMU.

Format of PMU produce :

the PMUs produce an IEEE standard format of data (IEEE-1344 or C37.118). The output is

written out at 60samples/sec with 6 vectors of 2 bytes each corresponding to a data rate of 6

KBPS which is time-stamped with UTC (universal time code signal). PMU generated data

will always have a real and an imaginary part. PMUs capture data at a far greater rate than

traditional SCADA units and due to the synchronization mechanism applied the data

collected by PMUs is more realistic than using estimates such as Kalman filter estimates. The

control algorithms for stability and reactive power delivery which requires P(Real Power) ,

Q(Reactive Power) and V(Line Voltage) have more real-time data to available from multiple

PMUs work with.

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Advantages of PMUs over traditional SCADA system:

SCADA outputs data every 2 seconds and does not include phase information.

Synchrophasor produces a 6 vector output 60 times / second and includes phase information.

A PMU picture of a grid is at far greater level of detail compared to a SCADA picture of a

grid hence it has been started that a useful analogy between PMU and SCADA is like a

MRI(PMU) versus and X-ray(SCADA) of the network

1.2 Underlying motivation for synchronized measurements to be performed on a PMU:

In practice the phasors measured by PMUs in widely different locations are best sampled at

the exact same instant even thought the PMUs are widely separated. Without an excellent

synchronization algorithm, the measurement vectors produced by an array of PMUs are less

reliable and not very useful. With a proper synchronization mechanism the simultaneous

measurements from multiple widely separated PMUs are used to detect perturbations in the

distribution system such as a frequency disturbance and the level of reactive power being

injected at a given point in the power grid. Synchronization is what make PMUs very useful

in power systems management and load dispatch.

Figure 1: Synchronization between widely separated PMUs

Measurements made in substation A will never be exactly synchronized with those made in

substation B unless they are taken deliberately at the same exact time instant – using a

common high resolution reference clock allows perfect synchronization between the two

measurements.

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1.3 Use of Synchrophasor (PMU)Data

One of the greatest advantages of synchrophasor measurement is availability of time

synchronized data obtained from various grid stations spread across a wide geographical area

covering thousands of square kilometers. The synchrophasor data is being extensively used

for real time and post event analysis. This envisages the use of the synchrophasor data for

event detection and event analysis for the purpose of development of analytics and tools to

monitor the event. The whole chapter has been divided into various categories of analysis for

which the data was used. Various grid events have been analyzed using the synchrophasor

data along with other data like Station Disturbance recorder (DR), Event logger (EL),

SCADA Sequence of Event (SOE) etc.

the following categories:

1. Fault detection, classification and analysis

- Faults in Transmission Line, power station/grid substation- Tripping due to lack of protection co-ordination/Instrument error.- Faults involving high impedance- Faults cleared by back up protections

2. Low Frequency Oscillation

- Inter Area Oscillation- Inter & Intra Plant Oscillation

3. Detection of Coherent Group of Generators

4. Islanding Detection and their resynchronization with the grid

5. Dynamic Model Validation Using Synchrophasor data

6. Visualization of PSS testing.

7. Monitoring of Natural disasters.

These are the major categories of various types of events in the Indian grid which are

analyzed with the help of Synchrophasor data.

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1.4 Challenge faced in implementation of PMU

Synchrophasor technology has many advantages, however implementing it on a large scale

also poses many challenges. In India, the project was first started on a obtain initial

experience of the technology and now it is being scaled up in the upcoming scheme known as

Unified Real Time Dynamic State Measurement Scheme (URTDSM Scheme). During the

execution of projects many challenges were faced, which include:

_ Selecting locations for PMU placements

_ Type of architecture required

_ Setting up of standards and compliances

_ Ensuring interoperability of PMUs

_ Availability and setting up of communication infrastructure

_ Developing tools for in-depth post facto analysis

_ Event Detection

_ Developing lucid visualizations for system operators

_ Integration of Synchrophasor technology with SCADA

_ Cyber Security Management & Compliance

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Chapter – 2

2.1 BLOCK DIAGRAMS OF PMU ARCHITECTURE

Typically a PMU comprises of 6 blocks:

Current and potential transformers

Analog front end – signal conditioning , noise filtering

Analog to digital converters – 1 KSPS(Kilo samples per second) is sufficient

for most PMUs

A master clock reference – GPS or IEEE 1588

A synchronization mechanism, usually a Phase –Locked Loop(PLL) to

synchronize the ADC clock and microprocessor clock with a GPS reference

clock

A Embedded controller i.e Zybo board of sufficient processing power to

compute FFTs and perform real time frequency and phase shift computation.

This can involve fast Digital Signal Processor computations.

A wireless or wired interface to send the phasor data in packets to a PMU

aggregation unit or to a central control room. The final packetized data from a

PMU is sent to a control engine which prepares the data for sending over a

USB port, a Wi-Fi interface , a Wide Area network(WAN).

Detail block Diagram of a PMU with Frequency , Phase Estimation and filtering

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Figure : Block diagram of a more detailed PMU implementation with estimators

Figure provides an alternative but far more sophisticated SW architecture. The difference

between Figure 4 and Figure 6 is the following.

CIC filter: the Cascaded Integrator Comb – CIC filter provides a high throughput low power

FIR filter replacement which will filter noise at the ADC output. CIC filters do not requires

any multiplication compared to a FIR or IIR filters and are widely used in digital radio

receivers.

Guard-filter: This is an additional harmonic filter which can filter out harmonics and filter out

and further unwanted spurs at ADC output.

PHASE ESTIMATOR: One way to estimate phase and frequency would be to apply a

Kalman filter to smoothen out the observations or an optimal Weinert-Desai type smoother.

Decimator: The rate at which the estimators work is still much higher than the rate required

the output of the PMU. A rate decimation module which comprises of a CIC filter with a

decimation stage

2.2 Performance measures for PMUs

The common performance measure for PMUs seems to be TVE- total vector error. TVE is a

measure between the instantaneous vector measurement and the actual error free value.

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TVE(n )=√ (Xr (n )−X̂ r( n))2+(X i(n )−X̂ i (n))

2

(Xr (n))2+(X i(n ))2

Where,

X r(n) = Real part of the phasor measurement performed by a given PMU

X i(n) = Imaginary part of the phasor measurement performed by a given PMU

The TVE is a Euclidian distance measure of the value measured by a PMU with the actual

error free value.

The typical PMU (Level 1) must operate at less than 1% TVE when the frequency deviation

is +/-1 Hz with 10% harmonics.

The typical performance requirements of a synchrophasor (Level 1) include the ability to

operate at less than 1% TVE when the frequency deviation is +/-5 Hz with 10% harmonics

and additional 10% out of band signal distortion.

Frequency Disturbance detector using PMU

Figure 7 A frequency disturbance estimator

The PMU produces instantaneous frequency estimates, a frequency deviation can be measured as ,

∆ f=f k−2 f k+1+f k+2

2 τ

Where

f k ,2 f k+1 , f k +2 are the frequency estimates at instants k, k+1 and k+2

τ=¿ The time interval between two frequency estimates

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When the estimate ∆ f exceeds a programmed threshold of say 0.5Hz the PMU will generate

a signal back to the control room. This signal captured a transient occurring in the system.

The PMUs can be used to capture transients including imbalances, circuit breaker tripping ,

voltage disturbances within the transmission grid.

Frequency Estimation

Frequency estimation is an essential part of what is performed by PMUs. The second the

phase estimation. The two estimations are interrelated. The frequency estimator usually

works using a demodulation as illustrated in Figure 6.

Demodulator for Frequency and phase shift determination

Demodulator utilizes a synthesized phasor rotating in the opposite direction to generate

frequency deviation and phase shifts in real time. The advantage is that no higher frequency

filters are necessary.

2.3 Snchrophasor Data Collection:

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Figure 8: Phasor Measurement Unit Data Aggregation

The phasor estimate was originally provided by Phadke as a combination of values one being the Fourier coefficient itself multiplied by the factor P and the second the conjugate of the Fourier coefficient multiplied by Q, this is taken at then nomimal frequency . The True fourier coefficient X is related to the obtained FFT value through the following equation.

X̂=PX+Q X¿

Where, X=¿ computed Fourier Coefficient

X , X¿ = true Fourier coefficient and its complex conjugate

P=sinN (ω−ω0)Δt

2

Nsin(ω−ω0)Δt

2

ej(N−1)

N (ω−ω0 )Δ t2

(1)

Q=sinN (ω+ω0)Δt

2

Nsin(ω+ω0)Δt

2

e− j(N−1)

N (ω−ω0 )Δ t2

(2)

The true Fourier coefficients can be obtained from the observations as follows,

ℜ (X )= ℜ ( X̂ )[P+Q ]

(3)

ℑ ( X )= ℑ ( X̂ )[P+Q ]

(4)

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TESTING OF THE PROPOSED ALGORITHM COMPARED TO QPS-DFT ALGORITHM

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Chapter – 3

3.1 Equipment used in PMU

Global Positioning System (GSP)

The synchronized time is given by GPS uses the high accuracy clock from satellite

technology. The first GPS system was developed by United States, Department of Defense.

Without GPS providing the synchronized time, it is hard to monitor whole grid at the same

time.

The GPS satellites provide a very accurate time synchronization signal, available, via an

antenna input, throughout the power system. This means that that voltage and current

recordings from different substations can be directly displayed on the same time axis and in

the same phasor diagram. Fig shows how GPS works to organize the synchronization time.

Figure

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