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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
Norwegian University of Science and Technology 3
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.
Norwegian University of Science and Technology 4
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
Norwegian University of Science and Technology 5
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
Norwegian University of Science and Technology 6
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
ො𝑥𝑘 = ො𝑥𝑘− + 𝐾𝑘 𝑧𝑘 − 𝐻𝑘 ො𝑥𝑘
−
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
Norwegian University of Science and Technology 7
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
ො𝑥𝑘 = ො𝑥𝑘− + 𝐾𝑘 𝑧𝑘 − 𝐻𝑘 ො𝑥𝑘
−
Estimate update equation
Rk = 0.001Rk = 1
𝐻𝑘 ො𝑥𝑘−
𝑧𝑘
𝐾𝑘 = 𝑃𝑘−𝐻𝑘
𝑇 𝐻𝑘𝑃𝑘−𝐻𝑘
𝑇 − 𝑅𝑘−1
Blending factor
Norwegian University of Science and Technology 8
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
Norwegian University of Science and Technology 9
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
Norwegian University of Science and Technology 10
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.
Norwegian University of Science and Technology 11
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
Norwegian University of Science and Technology 12
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.
Norwegian University of Science and Technology 13
Performance measures
Kalman
DFT
ZC
0.75 Hz/s1 Hz/s 0.5 Hz/s 0.25 Hz/sNon-detection zone
Norwegian University of Science and Technology 14
Performance measuresComputational resources consumption
• Number of operations measured
• Computationally efficient due to recursive nature and precalculated blending factor
Norwegian University of Science and Technology 15
Performance measures
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
Norwegian University of Science and Technology 16
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