Adaptive frequency estimation method for ROCOF islanding ...

Norwegian University of Science and Technology

Adaptive frequency estimation method

for ROCOF islanding detection relay

Maciej Grebla

14.05.19 Vaasa

Norwegian University of Science and Technology 2

Introduction

SMART GRID

MICROGRID

LV or MV network of load clusters with

distributed energy resources, both

generator and storage systems, able

to operate in grid-connected or

islanded mode

An electricity supply network that uses

digital communications technology to

detect and react to local changes in

usage


Introduction

Frequency estimation

ROCOF calculation

>Relay Setting

β

LPF #1

LPF #3

LPF #2

Trip

Voltage

ROCOF relay model [1]

Methods

Local passive

O/U frequency O/U voltage VVS ROCOF

‒ big NDZ‒ nuissance trippings

Local active

Sandia frequency shift Sandia voltage shift

Remote

DTT Synchrophasors PLC

[1] Motter, D., Vieira, J.C.M. and Coury, D.V., „Development of frequency-based anti-islanding protection models for synchronous distributed generators suitable for real-time simulations”, IET Generation, Transmission and Distribution, vol. 9, no. 8, pp. 708 – 718, 2015.


State-of-the-art methods

• Zero Crossing• Fourier

𝑋 𝑛 =2

𝑁

𝑘=0

𝑁−1

𝑥 𝑛 − 𝑘 𝑒−𝑗𝜋𝑓𝑏𝑇𝑘

𝑓 =𝛼𝑛 − 𝛼𝑛−1

𝑇∙𝑁

2𝜋∙ 𝑓𝑏

0

/2

3 /2

d/dt

𝑓 =1

2 𝑡𝑧𝑐 − 𝑡𝑧𝑐𝑙𝑎𝑠𝑡

𝑡𝑧𝑐 =𝑡𝑛−1 ∙ 𝑉𝑛 − 𝑡𝑛 ∙ 𝑉𝑛−1

𝑉𝑛 − 𝑉𝑛−1


Kalman

𝑥𝑘+1 = Φ𝑘𝑥𝑘 + 𝑤𝑘

𝑧𝑘 = 𝐻𝑘𝑥𝑘 + 𝑣𝑘

Process equation

Measurement equation

ො𝑥𝑘 = ො𝑥𝑘− + 𝐾𝑘 𝑧𝑘 − 𝐻𝑘 ො𝑥𝑘

−

Estimate update equation Simplification in phasor estimation

𝐸 𝑤𝑘𝑤𝑖𝑇 = ቊ

𝑄𝑘 , 𝑘 = 𝑖0, 𝑘 ≠ 𝑖

𝐸 𝑣𝑘𝑣𝑖𝑇 = ቊ

𝑅𝑘 , 𝑘 = 𝑖0, 𝑘 ≠ 𝑖

𝑅𝑘 and 𝑄𝑘 determine sensitivity of the algorithm

[2] Brown, R. G., „Introduction to random signal analysis and kalman filtering”, John Wiley & Son, 1985, New York


Kalman with power system signals𝑥 𝑡 = 𝐴 𝑡 𝑐𝑜𝑠 𝜔𝑡 + 𝜃 = 𝐴 𝑡 𝑐𝑜𝑠𝜃𝑐𝑜𝑠 𝜔𝑡 − 𝐴 𝑡 𝑠𝑖𝑛𝜃𝑠𝑖𝑛 𝜔𝑡

𝑥𝑘+1 = Φ𝑘𝑥𝑘 + 𝑤𝑘 𝑧𝑘 = 𝐻𝑘𝑥𝑘 + 𝑣𝑘

Process equation Measurement equation


−

Estimate update equation

𝑥1𝑥2 𝑘+1

=1 00 1

𝑥1𝑥2 𝑘

+𝑤1𝑤2 𝑘

𝑧𝑘 = cos 𝜔𝑡𝑘 −𝑠𝑖𝑛 𝜔𝑡𝑘𝑥1𝑥2 𝑘

+ 𝑣𝑘

Stationary phasor

𝑥2𝑥1

[3] Girgis, A. A., Bin Chang, W. and Makram, E.B., „A digital recursive measurement scheme for on-line tracking of power system harmonics”, IEEE Transactions on Power Delivery, vol. 6, no. 3, pp. 1153 – 1160, 1991.

𝐾𝑘 = 𝑃𝑘−𝐻𝑘

𝑇 𝐻𝑘𝑃𝑘−𝐻𝑘

𝑇 − 𝑅𝑘−1

Blending factor


0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

Rk = 0.001

Rk = 1

Phasor – real part

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

t1

t1t1

Measurement

Estimate

Measurement

Estimate

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

t1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

t1

Blending factor Blending factor

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

t1

Kalman with power system signals


−

Estimate update equation

Rk = 0.001Rk = 1

𝐻𝑘 ො𝑥𝑘−

𝑧𝑘

𝐾𝑘 = 𝑃𝑘−𝐻𝑘

𝑇 𝐻𝑘𝑃𝑘−𝐻𝑘

𝑇 − 𝑅𝑘−1

Blending factor


Kalman based adaptive algorithm

iph(t)

rLS filter Kalman filter

vph-g(t)

Frequency

ROCOF

If ROCOF > β TRIPY

1

2

3

4

5

6

if I < I

elseBlending factor Kk

Blending factor αKk

phDC phDC_thresh

phDC, IphI

• Fault detection criterion – DC offset in phase currents due to fault

• Fast DC offset estimation

• Use different blending factor to change frequency esitmation sensitivity


Lab setup

MATLAB/SIMULINKMV network model

IEC 61850 Sampled Values 4kHz

uabc(t), iabc(t)

IEC 61850 GOOSE Tripping signal

OPAL RT 5600 STM32F746G-DISCO STM32F746NG Cortex-M7

Discovery

Access to microprocessor memory by PC through

USB

• μC w/ protection logic and IEC 61850 (GOOSE and SVs)

• OP5600 w/ CIGRE distribution network


MV network

1

2

3

4

5

8

79

10

11

6

2.8

km

4.4

km

0.6

km

0.6

km

0.5

km

0.3 km

0.8

km

0.3

km

0.2

km

1.7

km

1.5 km

1.3

km

S2

S3

12

13

14

CB1b

CB1a CB2a

4.9

km

3.0

km

2.0 kmS1

CB2b

HV/MVHV/MV

110kV

20kV 20kV

SGCBDG

FEEDER 1 FEEDER 2

110kV Grid

F1

F2

F3

Vph

Iph

Isl. relay

CIGRE benchmark distribution network:

• Representative European MV network

• 2 feeders‒ OHL dominated (feeder 2)‒ cable dominated (feeder 1)

• Synch. Generator at bus 7

[4] Strunz, K., Abassi E., Fletcher, R., Hatziargyriou, N. D., Iravani, R., and Joos, G., „Benchmark systems for network integration of renewable and distributed energy resources”, CIGRE WG C6.04, 2014.


Demonstration

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7-1.5

-1

-0.5

0

0.5

[Hz/s

]

Rate-of-change-of-frequency

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.749

49.5

50

[Hz]

Frequency

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7

Time [s]

0

100

200

300

[A]

DC offset in phase current

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7-2

0

2

[Hz/s

]

Rate-of-change-of-frequency

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7

49.8

50

50.2

[Hz]

Frequency

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.70

100

200

300

[A]

DC offset in phase current

ROCOFth = 1 Hz/s

ROCOFth = -1 Hz/s

DCoffth = 50 A

ZC

DFT

Kalman

ROCOFth = -1 Hz/s

DCoffth = 50 A

Time [s]

Two phase fault at the adjacent feeder Islanding


Performance measures

• Generator output power – 0..1 pu• HV system short circuit power – 1000..5000 MVA• Fault location – three different locations • Fault type – 3ph, 2ph, 2ph-g

𝑆 =𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑜𝑟𝑟𝑒𝑐𝑡 𝑟𝑒𝑠𝑡𝑟𝑎𝑖𝑛𝑡𝑠

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑒𝑥𝑝𝑜𝑠𝑢𝑟𝑒𝑠∙ 100%

Security as [5]

Security

[5] Udren, E., Zipp, J., Michel, G., et al., „ Proposed statistical performance measures for microprocessor-based transmission-line protective relays;part i - explanation of the statistics, preceding companion paper”, IEEE Transactions on Power Delivery, vol. 12, no. 1, pp. 134 – 143, 1997.



Kalman

DFT

ZC

0.75 Hz/s1 Hz/s 0.5 Hz/s 0.25 Hz/sNon-detection zone


Performance measuresComputational resources consumption

• Number of operations measured

• Computationally efficient due to recursive nature and precalculated blending factor



2ph 3ph

Faults

Use three phase

other criterion

or

Fault detection criterion

1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7

Time [s]

-1000

-800

-600

-400

-200

0

200

400

600

800

[A]

DC offset

Ph A

Ph B

Ph C


Conclusion

• Application of Kalman method with variable blending factor performs better in case of security

• Increased security allows for setting the relay to be more sensitive and decrease non-detection zone

Adaptive frequency estimation method for ROCOF islanding ...

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