Manuel Avendaño J. V. Milanović

Frankfurt (Germany), 6-9 June 2011

Manuel Avendaño J. V. Milanović

Manuel Avendaño – UK – Session 2 – Paper 0529

METHODOLOGY FOR FLEXIBLE, COST-EFFECTIVE MONITORING OF

VOLTAGE SAGS

School of Electrical & Electronic Engineering

Manchester, UK


What did we do?

Proposed methodology for determining a range of best monitoring programmes for estimating the performance of sags with different characteristics.

Incorporated user-defined voltage sag characteristics and a measure of the overall accuracy of sag estimation.



Presentation Outline

Why did we do it? (Importance and motivation) How did we do it? (Methodology) What did we get? (Results) What did we learn? (Conclusions)



Why did we do it?

Knowledge of voltage sag incidence in the network can help in tailoring solutions to mitigate the consequences of sags.

Estimation of sag characteristics is required when measurements are not available.

Fault location method utilized directly influences the number of monitors.



Why did we do it?

Sag monitoring programs (SMPs) should be focused on quantifying most critical sags− (E.g. SARFI-90%, SARFI-70%, SEMI F47, etc)

To provide a measure for assessing the sag estimation derived from a SMP− (Diff. between real and estimated events)



How did we do it?

Selection of monitor locations based on minimization of overall sag estimation error.

Utilization of existing fault location method.

Application in a generic distribution system (GDS) and comparison with an optimal placement method.



Sag estimation error (SEE)

= total number of buses

= real number of sags below i.c. SEMI F47 at bus i

= estimated number of sags below i.c. SEMI F47 at bus i

, , 47 47

1( 47)

- N

i real i estimatedSEMI F SEMI F

iSEMI F

X XSEE

N

, 47

i realSEMI FX,

47i estimatedSEMI FX

N

SEMI F47 can be substituted by any other voltage-tolerance curve (CBEMA), performance index (SARFI), etc.



1. Set target value for SEE or number of monitors (stop criteria).

2. Simulate faults to obtain sag performance.

3. Perform fault location using voltage measurements of all buses.

4. Calculate SEE incurred by all buses.

5. Monitor location = min(SEE)

6. Repeat steps 3-5 until a stop criterion is fulfilled.

Monitor placement



What did we get?

An iterative search algorithm that is:

Flexible. One or multiple monitoring programmes can be determined for any kind of user-defined voltage sag characteristics.

Cost-effective. If technical and/or economic constraints limit the number of monitors to be deployed, a series of SMPs can be provided accordingly.



Application

295-bus GDS, 278 lines, 37 transformers.

GDS equipment shut-down region below SEMI F47

5 10 15 20 25 30 35 40 45 500

20

40

60

80

100

Duration (cycles)

Pe

rce

nt

of

no

min

al v

olt

ag

e

GDSsag characteristics

Voltage level (kV)

Fault clearing time (cycles)

11 18

33 9

132 4.8

Bus faults 3.6



Sag Monitoring Programmes

Number of monitors

SEE (number of sags)

SARFI-90 SARFI-80 SARFI-70 SEMI F47

1 876 873 876 541

2 459 459 459 218

3 255 255 313 117

4 118 118 119 62

5 22 23 24 16

6 11 12 13 5

7 5 10 12 3

8 3 8 8 1

9 1 6 6 0

10 0 0 0 0



Reduction of sag estimation error

0

200

400

600

800

1000

1200

1 2 3 4

Sa

g E

sti

ma

tio

n E

rro

r

1 2 3 4


0

5

10

15

20

25

30

5 6 7 8 9 10

Number of monitors5 6 7 8 9 10


Location of monitorsSMP – SARFI-90 Optimal monitoring



Effects of robustness in fault location method on sag magnitude estimation

0 50 100 150 200 250 300

0.7

0.8

0.9

1

Buses

Vo

lta

ge

sa

g m

ag

nit

ud

e (

p.u

.)

Est. 5 monRealEst. 12 mon



Comparison with optimal monitoring

0 50 100 150 200 250 3000

5

10

15

Buses

SA

RF

I-9

0 in

de

x

RealEst. 5 monEst. 12 mon

12 monitors optimally placed vs. 5 monitors placed with proposed approach.



Comparison with optimal monitoring

0

5

10

15

20

25

30

1 2

Sa

g E

sti

ma

tio

n E

rro

r

OSMP (12 monitors)SMP (5 monitors)

Distribution of SEE for Monte Carlo simulations representing 100 years of system performance



Conclusions

A methodology for determining a range of best voltage sag monitoring programmes is proposed.

DNOs can choose a sag monitoring programme specifically designed to estimate the performance of the sags more relevant to its customers.

Due to the fault location technique employed it is more robust than previous approaches.


Documents

Manuel Avendaño J. V. Milanović