simulación en tiempo real smart grids phil hil

1. Supervisors:
MERCIER Aurélien, BENOIT Clémentine, BESANGER Yvon

2. Contents
1
2
3
4
5
Introduction
GreenLys
Modeling the Electrical Network
Methodology
Conclusions & future work
2

3. 1. Introduction
• Liberalized markets,
• DGs
• The reduction in operating margins
• New Services
Most effective strategy
3

4. Smart Grid
• A smart grid is an electricity network that can
intelligently integrate the actions of all users
connected to it – generators, consumers and
those that do both- in order to efficiently
deliver sustainable, economic and secure
electricity supply.*
4
*http://www.smartgrids.eu/ETPSmartGrids

5. 2. GreenLys
• GreenLys => R&D project for implementing Smart Grid is
supported by ADEME, launched in 2012 in the cities of
Grenoble and Lyon
1. Help to end users to consume better.
2. Better integration of local production of renewable
energy and electric vehicles.
3. Handle the peaks of production and consumption in
order to reduce CO2 emissions.
4. Improve safety, reliability and performance of the grid.
5

6. 11 WORK
PACKAGES
*WP 6
6
Analyze and Provide intelligent
management solutions
The WP 7 focuses its work in the
implementation of an Aggregator
*WP 7

7. SOFTWARE
• GAMS
7
• MATLAB -
SIMULINK • RT-LAB
General Algebraic
Modeling System
Modeling system for mathematical
programming and optimization

8. 3. MODELING
THE ELECTRICAL NETWORK
• Transformers
8
• Lines
• Loads

9. 9
STUDIED NETWORK
Substation
MV/LV
Transformer Power KvA Number of clients Number of nodes
odP125
Tr1 1000 257 26
Tr2 1000 171 31
P555
Tr3 1000 243 43
Tr4 1000 237 25
Tr5 1000 15 20
P775 Tr6 630 248 25
P1020 Tr7 400 205 21
P1346 Tr8 250 99 14
The low voltage network is fed with 400V phase to phase, the configuration is 3P4W
(Three phases with neutral).

10. REAL TIME SIMULATOR
RT-LAB, fully integrated with MATLAB/Simulink, is the
real-time simulation software chosen in the Greenlys
Project
• Possibility to include real devices in the simulation
• Gaining Time
• Lowering cost
• Increasing test functionalities
• Automatic test script in order to run
tests 24 hours a day, 7 days a week
10

11. 11
DC
AC
TURBINE
GENERATOR
ARENE URT
DFIG
ANALOGICAL WIND TURBINE
DC
AC
AC
DCM
Control
strategies
(MPPT, P ct.)
Control
strategies
(wind profile)
Digital Analog
Real-time simulation
Power-Hardware-in-the-loop (PHIL)
Example : Hybrid wind turbine test bench

12. 12
REAL-TIME HYBRID SIMULATOR
DC
AC
Current measure
TURBINE
GENERATOR
ARENE URT
DAC
ADC
Controlled current source
Voltage measure
DFIG
Power
amplifier
ANALOGICAL WIND TURBINE
DC
AC
AC
DCM
Control
strategies
(MPPT, P ct.)
Control
strategies
(wind profile)
Current
sensor
•
Real-time
closed-loop
Example : Hybrid wind turbine test bench
Voltage
reference
Real-time simulation
Power-Hardware-in-the-loop (PHIL)

13. 3. METHODOLOGY
13

14. 14
P555

15. 15
GOOGLE EARTH
DIFFICULT
A LOT OF TIME NEEDED
ARCMAP
GEODATABASE , EASY
TREATMENT
TOPOLOGY

16. 16
Trafo 1
l2
l3
l4
I1
l1 l5
l6
l39 l40 l19
l46
l49
I14
l38
l50
l45
l44
l8
l9
l7
l11
l12
l10
l27
l28
l25
l26
0 1
2
3
4
5 6
7 8 9 10 11
12
13
16
15
17
19
18
20
22
21
23 24
25
26
27
l20
14

17. 17
Information given by GEG
Typical values for Distribution Networks

18. 18

19. Distribution GRID
on RT-LAB
19

20. 20
MV
*Sifuentes Jose (2013) Modélisation de réseaux de distribution dans un simulateur temps-réel
pour des applications « Smart Grids »,

21. LV
21
5 LV networks
modeled in detail
during the
internship

22. Feeder
22

23. Load
23
Into Simulink , we must add
the capacitance

24. Measurements
at Loads
24

25. 25
Node Phase
Random
Consumers
Aggregated Curves (
randomly)
14
A 4 4,29,42,50
B 2 8,31
C 2 25,2
Random Distribution
of Loads and Consumers

26. 26

27. LOAD FLOW
• Loads have constant power, hence the equations are
nonlinear (Knitro solver).
• Loads are considered with constant impedances, the
equations are linear (Cplex solver).
27

28. SCENARIOS TO
EVALUATE THE MODELS
S1 (to) S2 (t1) S3 (t2) S4 (t3) S5 (t4) S6 (t5) S7 (t6)
Load % 50 50 50 16 32 100 50
Phase C A B Only A Only A A, B , C A, B , C with reactive power
28

29. KNITRO VS PQ
CONSTANT
S1 (to) S2 (t1) S3 (t2) S4 (t3) S5 (t4) S6 (t5) S7 (t6)
G S G S G S G S G S G S G S
P (KW) 492.85 494.4 492.86 494.4 492.86 494.4 168 169.5 351.86 353.6 1028.18 1030 492.755 494.4
Q (KVAr) 15.75 16.5 15.75 16.5 15.75 16.5 6.34 6.58 28.445 29.59 67.14 70.37 113.35 114.4
S (KVA) 493.10 494.68 493.11 494.68 493.11 494.68 168.12 169.63 353.01 354.84 1030.37 1032.40 505.62 507.46
Voltage* % 0.07 0.07 0.07 0.05 0.07 0.11 0.10
Current* % 0.07 0.08 0.08 0.07 0.13 0.11 0.10
Max
voltage **
%
0.08 0.08 0.08 0.08 0.17 0.12 0.10
Max
current** %
0.10 0.13 0.13 0.08 0.16 0.11 0.10
29
G= GAMS AND S=SIMULINK
*=Difference average between the 2 models at each node
**=Maximum error between the 2 models

30. TOTAL ACTIVE
POWER AT Tr8
30

31. Imbalance in the
3 Phases
31

32. 5. CONCLUSIONS
• The real time simulations allow analyzing several scenarios
with lowering costs
• PHIL hybrid simulator => possibility to include real devices
with high power in the simulations
• In this thesis have been implemented a methodology for
modeling the LV network
• Simulink-Matlab, GAMS and RT-Lab => real distribution grid
with its medium and low voltage network.
32

33. 6. FUTURE WORK
• The next phase >> SCADA with a communication network
based on the 61850 standard for smart grids.
• Send information between RT-Lab, GAMS, analog devices
(PV source, programmable load, smart meters, etc.) in
real time >> OPC
33

34. REFERENCES 1/2
[1] Energinet.dk (2011) Smart Grid in Denmark, at
http://www.danishenergyassociation.com/Theme/SmartGrid2.aspx
[2] European smart grids technology Platform (2014) What is a Smart Grid, at
http://www.smartgrids.eu/ETPSmartGrids
[3] US department of energy (2014) What is the Smart Grid, at
https://www.smartgrid.gov/the_smart_grid#smart_grid
[4] GREENLYS (2014) Le project Greenlys, at http://www.greenlys.fr
[5] Mercier Aurélien (2013) Etude de l’insertion massive de production décentralisée
et des charges non conventionnelles dans les réseaux urbains dans le contexte Smart
Grid, Etude bibliographique, Institut Polytechnique de Grenoble, France
[6] L’ADEME (2012) Convention de Financement, France
[7] Caire Raphael (2004) Gestion de la production décentralisée dans les réseaux de
distribution, Thèse de l’Institut Polytechnique de Grenoble, France
[8] Martino (2001) Réseau de distribution commun au GIE IDEA, Institut
polytechnique de Grenoble, France
[9] Sifuentes Jose (2013) Modélisation de réseaux de distribution dans un simulateur
temps-réel pour des applications « Smart Grids », STAGE PFE, Institut Polytechnique
de Grenoble, France
34

35. REFERENCES 2/2
[10] OPAL RT (2014) Real Time Digital Simulation Software, at http://www.opal-rt.com/product/rt-lab-
professional-real-time-digital-simulation-software
[11] OPAL RT (2013) Module 1: Real-Time system Fundamentals
[12] GEG (2012) Maps in format KML, information given at the beginning of the internship
[13] Benoit Clementine (2013) Ecriture_LF_Cplex , Institut Polytechnique de Grenoble, France
[14] Sekkai Selmane. MathWorks . Application Engineer (2014) Electrical Distribution in System
Modeling and Analysis in MATLAB® and Simulink ®”. Webinar at
http://www.mathworks.com/videos/electrical-distribution-system-modeling-and-analysis-in-matlab-
and-simulink-81978.html
[15] GAMS (2014) An introduction to GAMS, at http://www.gams.com/
[16] Math Works (2014) Documentation Center, at
http://www.mathworks.com/help/matlab/math/random-numbers-with-specific-mean-and-
variance.html
[17] Ditutor (2014) Gauss Campane , at
http://www.ditutor.com/distribucion_normal/campana_gauss.html
[18] Entrepeneur (2014) Bussines Plan, at http://www.entrepreneur.com/encyclopedia/business-plan
[19] Lanfrey Jean-Baptiste (2010), Real-Time Simulation of Simscape Models
[20] Feito J. Sanz (2002), Maquinas Electricas, Prentice Hall, Madrid
[21] Single-Phase Line Models, at
http://www.openelectrical.org/wiki/index.php?title=Single-Phase_Line_Models
35

36. 36
Merci pour votre attention

37. Appendix 3
GAMS Simulink
TR2 n26 0.83 0.83
TR3 n27 1.56 1.50
TR4 n12 0.96 0.92
TR5 n11 0.62 0.62
TR6 n22 1.48 1.45
TR7 n14 1.05 1.03
TR8 n13 1.06 1.03
37

38. Appendix 4
38

39. Aerien Cuivre 4X50 3*48+48
Aerien Cuivre 4X35 3*38+38
Aerien Cuivre 4X25 3*22+22
Aerien Cuivre 4X16 3x14+14
39
The next cables were assumed like equals.
Aerien Cuivre 4X240
Aerien Cuivre 4X120
The information for the next cables was obtained through potential extrapolation
y = 24.264x-1.051
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
0.00 20.00 40.00 60.00

40. Appendix 6
40
0.5 1 1.5 2 2.5 3 3.5 4 4.5
100
150
200
250
X: 2.648
Y: 227.3
Ts = 200us
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
50
100
150
200
250
X: 2.611
Y: 227.2
Ts = 0.5s
Ode14
Ode3
Ode14

41. Appendix 7
The mean and variance are not b and a exactly
because they are calculated from a sampling of
the distribution.
 a
 b
 y = a.*randn(1000,1) + b;
41