Red Eléctrica de España is the Spanish transmission system operator. It operates and maintains the transmission grid to ensure security of electricity supply. Renewable energy sources now account for 39% of Spain's installed capacity, including 22.6% from wind and 4.4% from solar PV. Integrating high levels of renewable energy presents challenges like variability in generation, lack of observability and controllability, and impacts on grid constraints and voltage control. The CECRE control center helps address these issues by providing centralized monitoring and control of renewable facilities.

1. The CECRE: Making renewable energy
technologies compatible with the securitytechnologies compatible with the security
of the system
June 2013

2. Who is Red Eléctrica?
Red Eléctrica de España (REE) is the Spanish transmission system operator (TSO)
System Operation:
❑ Operate the grid & coordinates its uses with the generation facilities in order to ensure the security
and continuity of the electricity supply.
Transmission (Since 2007 as exclusive transmission company):
❑ The development and the maintenance of the transmission facilities
❑ Provide maximum service reliability
2
❑ ~ 41,000 km of lines and 78,000 MW of transforming capacity
Transmission Grid End 2012
Main magnitudes (SPPS) REE
Lines
400 kV [km ct] 20104
≤≤≤≤ 220 kV [km ct] 21124
Substations
≤≤≤≤ 220 & 400 kV [nº bays] 5053
Transformers [MVA] 78050

3. System Overview
Installed capacity in Spain today
Issues and solutions integrating RE nowadays
Demand coverage
Outline
3
Distributed Generation (Observability/Controllability)
Grid constrains (RdT/RdD)
Behavior facing disturbances (Voltage dips)
Power balance feasibility and RES courtailments
Voltage control
Impact of forecast errors(SIPREOLICO/SIPRESOLAR)
CECRE: Control Centre for Renewable Energies
Conclusions

4. System Overview
Installed capacity in Spain today
Issues and solutions integrating RE nowadays
Demand coverage
Outline
4
Distributed Generation (Observability/Controllability)
Grid constrains (RdT/RdD)
Behavior facing disturbances (Voltage dips)
Power balance feasibility and RES courtailments
Voltage control
Impact of forecast errors(SIPREOLICO/SIPRESOLAR)
CECRE: Control Centre for Renewable Energies
Conclusions

5. Spanish Electrical System
GeneratorsInternational Exchanges · REESpecial Regime
Transmission network· REE System Operator· REE TSO (foreign)
Ancilliary services bids
5
Daily and Intradaily
Market
Daily and Intradaily
Market
Demand bids
Energy flows
Communication
Market Operator· OMEL
Distribution companies
Red de distribución
< 132 kV
Subestación
de distribución
Qualified consumers
Outages
Ancillary ServicesAncillary Services
Consumers with/without
last resort tariff
Suppliers Last resort suppliers Demand bids

6. Daily load demand
Maximum demand:
41 318 MW 13:26 h 19/07/2010
Maximum demand:
45 450 MW 18:53 h 17/12/2007
Winter load demand record Summer load demand record
6
Big gap between peak hours
demand
and off- peak hours demand
• Spanish maximun peak demand: 45 GW
• Spanish minimum off-peak demand : 18 GW.

7. Influential factors in load demand
Temperatura Mínima
1.9 ºC
24000
28000
32000
Temperatura Máxima
34.1 ºC 31.2 ºC
29.3 ºC
28.7 ºC24000
28000
32000
❑ Temperature
38.000
30.000
34.000
36.000
28.000
32.000
Temperature Mínimum Temperature maximum
7
8.3 ºC
20000 20000
Nubosidad
21000
25000
29000
❑ Cloudiness
Puente Fiesta Postfestivo
10000
13000
16000
19000
22000
25000
28000
L M X
❑ Holidays
26.000 24.000
38.000
26.000
30.000
34.000
38.000
26.000
30.000
34.000
36.000
32.000
28.000
Long weekend: work day -bank holiday-work day

8. World Cup 2010 final in South Africa (11th July 2010)
Influential factors: special events.
32000
33000
34000
20:30 h home
matchs
23:00 h final
matchs
8
27000
28000
29000
30000
31000
32000
MW
HORA 21:15 h first half
22:15 h
secon
d half

9. 800-1.400
600-1.100
1.500-2.400
Transmission capabilities of interconnections(I)
9
1.500-2.400
1.500-2.400
600 900
http://www.ree.es/operacion/capacidades.asp
•In specific situations, usually linked to
unavailability of network elements of the
transport capacity values can occur below
the ranges presented.
Not considered these values by its low
frequency and representativeness.

10. System Overview
Installed capacity in Spain today
Issues and solutions integrating RE nowadays
Demand coverage
Outline
10
Distributed Generation (Observability/Controllability)
Grid constrains (RdT/RdD)
Behavior facing disturbances (Voltage dips)
Power balance feasibility and RES courtailments
Voltage control
Impact of forecast errors(SIPREOLICO/SIPRESOLAR)
CECRE: Control Centre for Renewable Energies
Conclusions

11. Installed capacity june 2013
Hydro-power
17,31% Thermical Renewable
0,64% CHP &Other RE
7,26%
Solar PV
Solar CSP
2,05%
Special regime hydro
2,04%
Technology MW %
Combined cycles 24947 24.9
Hydro-power 17303 17.3
Coal 10740 10.7
11
Combined cycles
24,96%
Coal
10,75%
Fuel-Gas
0,51%
Nuclear
7,58%
Wind
22,59%
Solar PV
4,32%
Coal 10740 10.7
Nuclear 7572 7.6
Fuel-Gas 506 0.5
Total (ordinary regime) 61068 61.0
Wind 22668 22.6
CHP &Other RE 7252 7.2
Solar PV 4429 4.4
Special regime hydro 2039 2.0
Solar CSP 2050 2.0
Thermical Renewable 639 0.6
Total (special regime) 39077 39.0
Total 100145

12. 251.901 GWh = 174.144 Net Ordinary Regime
+ 102.428 Net Special Regime
-11.206 International exchanges
-3.215 Hydro-pump storage
- 570 Baleares Interconnection
Demand supply 2012
12
Special Regulation Regime
Renewable:
Minihydro
Biomass
Wind
Industrial waste
Urban waste
Solar
Non Renewable:
Cogeneration
Coal
Fuel - Gas oil
Refinery gas
Natural gas
Coal; 12,6% Coal national (RD
134/2010); 7,7%
Combined cycle; 14,8%
Fuel-
Gas;
0,0%
Nuclear; 23,2%
Small Hydro; 1,8%
Hydro-power; 7,6%
Solar CSP; 1,4%
Solar PV; 3,2%
Wind; 19,1%
CHP Renewable; 1,9% CHP non RES; 13,3%
∑Energy without emissionsCO2 ≈ 58,2% ∑Renewable Energy ≈ 35%

13. Installed capacity evolution
13

14. System Overview
Installed capacity in Spain today
Issues and solutions integrating RE nowadays
1.- Demand coverage
Outline
14
2.- Distributed Generation (Observability/Controllability)
3.- Grid constrains (RdT/RdD)
4.- Behavior facing disturbances (Voltage dips)
5.- Power balance feasibility and RES courtailments
6.- Voltage control
7.- Impact of forecast errors(SIPREOLICO/SIPRESOLAR)
CECRE: Control Centre for Renewable Energies
Conclusions

15. 1.- Demand coverage
Big difference between peak hours demand and off- peak hours
demand during the day
No possibility to storage big quantity of electrical energy means
Generation must adapt to demand in each moment
Flexibility of each plant to adapt their production to the demand
necessities is mainly determined by technology facilities
15
Continuous manageable generation actions are needed in order to maintain
system equilibrium
necessities is mainly determined by technology facilities
RES has priority of dispatch
RES production depends on their primary energy availability
It is required plants that can adapt their production to the demand necessities:
manageable generation

16. Demand coverage: Wind Generation in year 2012 (I)
Maximum coverage 2012 (24/09/2012): 64% wind production = 13285 MW
16
Minimum coverage 2012(11/09/2012): <1% wind production = 81 MW
Very variable production output
Historical maximum wind production (06/02/13 at 15:49 h): 17056 MW

17. Winter
PV power plants:
Wind
RES
CC Hydro
Demand coverage: Solar photovoltaic
0
5
10
15
20
25
30
35
40
45
50
7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00
MW
Hour of the day November 21st 2010
Plant1 30 MW Plant2 13 MW Plant3 7 MW
17
Winter
Sumer
PV power plants:
CC Hydro
Wind RES
CC Hydro
Plant1 30 MW Plant2 13 MW Plant3 7 MW
Plant4 22 MW Plant5 48 MW Sum 120 MW
0
10
20
30
40
50
60
70
80
90
100
6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00
MW
Hour of the day October 20th 2010
Plant1 30 MW Plant 2 13 MW Plant 3 7 MW
Plant4 22 MW Plant 5 48 MW Sum 120 MW

18. CSP power plants:
Wind
RES
Demand coverage: Solar thermoelectric (I)
18
Winter
Sumer
CSP power plants:
CC Hydro
Wind RES
CC Hydro

19. Example of the needed flexibility Maximum demand
36 319 MW
Generation mix
during off-peak
Downward tertiary reserve
exhausted in hours 3:00-9:30 and
15:00-18:00 h
19
5 combined cycle
units during off-
peak hours
Minimum demand
20 638 MW
30 combined cycle
units during peak
hours

20. 2.- Distributed generation:
Lack of observability and controllability
Connection points are far from consumption.
More than 2000 RE facilities, each belonging to different companies with
different policies on operation and maintenance.
Slow contact in case of emergency reductions, outages or transmission
assets maintenance.
20
assets maintenance.
If required actions take too much time, risks are higher. Then stricter
limitations must be applied and have to be planned further in advance, so
higher reductions to RES production have to be established by the TSO.
Solved by grouping facilities in control centers with real-time contact
with the System Operator through the CECRE.

21. Observability, why?
OBSERVABILITY
Real time
measurements
Production
forecast
Hot reserve
evaluationAvoiding
demand
forecast errors
21
Observability is required to have real time information of the
production of the renewable energy facilities.
This information is used to make reliable production forecasts
for this type of installations.
Renewable forecasts are a basic tool for hot reserve evaluation.
Its accuracy affects the required levels of reserve and helps
dispatching manageable generation to counteract renewable and
non manageable variability.
Receiving the real time measurements of all the generation
facilities allow the TSO to distinguish between generation and
demand, avoiding demand forecast errors as well.
Dispatching
manageable
generation
COUNTERACT
RENEWABLE
VARIABILITY

22. Observability: And if not, what?
Without a reliable
forecast
Demand forecast
errors
22
Increasing
Uncertainties
Reducing the
Security of the
system
Increasing the
required level
of reserves
Reducing RE
production

23. 3.- Grid constrains
Depending on the generation scenario and the grid situation there are
significant changes in the use of lines.
Transmission grid/Distribution grid maintenance works
23
Transmission grid/Distribution grid maintenance works
Grid elements unavailability due to breakdowns
It is necessary to reduce renewable non manageable generation to maintain
security system or grid elements

24. Influence of renewable energy integration in power flows
November 3rd 2011 November 6th 2011 November 7th 2011
Grid constrains
24
Heavy flows from the North-
West to the center and East.
Low hydro and CC.
Heavy flows from the East
to the center and North.
Low hydro and CC.
Heavy flows from the East
and South-West to the
center and South. High
hydro and CC.

25. 4.- Behavior facing disturbances
Technological characteristics (power electronics) of some RES facilities
can cause:
Wind and solar photovoltaic generation tripping due to voltage dips
Wind generation tripping due to their over-speed protection
25
Increase of installed RES power with fault-ride-through capabilities and
system security

26. Demand coverage:
Demand is given at a certain moment, until relevant demand side management
takes place, generation must adapt to demand to maintain system equilibrium.
Adequacy to system demand profiles.
Variability and predictability
5.- Power balance feasibility and RES curtailments
26
The combination of these two factors along with the behavior and uncertainty of the
demand contribute to situations with balance feasibility difficulties due to lack of
downward reserve.
Variability and predictability
Variability influences the rest of the electric system that must compensate such
variations to keep the system balanced.
Predicting this variability and awareness of uncertainties crucial for efficient
operation.

27. Generation mix during off-peak hours
Balance feasibility during off-peak hours (I)
Maximum demand:
39 183 MW
Downward tertiary reserve
exhausted in hours 2:00-6:00
27
Minimum demand:
23 653 MW

28. 27 combined cycle units
during peak hours
Balance feasibility during off-peak hours (II)
Lower production
on peak hours
Wind Combined cycle
28
1 combined cycle unit
during off-peak hours
High production during
off-peak hours

29. 6.- Voltage control
Parameter that determines system quality.
Conventional generation, through reactive power injection/absorption, play
an essential roll in continuous system voltage control at the substation level.
Nowadays, RES generators only maintain power factor.
29
Continuous voltage control through the CECRE also for RES
generation with P>10 MW.

30. 7.- Impact of forecast errors (SIPREOLICO/SIPRESOLAR)
Forecast can mitigate the effects of renewable energies variability in
System Operation, but errors must be taken into account and additional
reserves must be provided to overcome them.
Larger forecast errors imply more provision of reserves increasing system
30
Larger forecast errors imply more provision of reserves increasing system
costs
REE has developed its own prediction for wind generation (SIPREOLICO)
and for solar generation (SIPRESOLAR)

31. 7800
8200
8600
Impact of forecast errors on system operation
Wind Solar
Increase of 586 MW in 30 min. Gradient: 1172 MW/h
Decrease of 1110 MW in 1 h 25 min. Gradient: -785 MW/h
Decrease of 400 MW in 1 h
Solar gradients are smaller than wind gradients due to the
fact that wind total installed capacity is quiet higher than
solar one. But also relevant.
31
5800
6200
6600
7000
7400
7800
At present wind downward/upward ramps may reach
±1500 MWh.
Renewable production depends on weather conditions, so less wind or more clouds mean great
production gradients. So it is necessary to check the instantaneous need for manageable generation
in order to size reserves . Generation RES forecast becomes crucial for system balancing.

32. RES forecasts available to the CECRE
Wind: SIPREOLICO Solar: SIPRESOLAR
Aggregated national hourly forecast up to 10 days
in advance
Detailed hourly forecasts up to 48 hours in advance
Developed in MATLAB environment
Statistical method: based on self-adaptive time series
Two different forecast for CSP and PV.
Aggregated national hourly forecast up to 10 days in
advance
Detailed hourly forecasts up to 48 hours in advance
Based on artificial neural network..
32
Statistical method: based on self-adaptive time series
Probabilistic wind power forecast: confidence intervals
Based on artificial neural network..
Probabilistic wind power forecast: confidence intervals

33. On the morning of Sunday November 2nd at 8:00 h with one of the lowest demands of
the year (~20 000 MW), wind prediction error hit 3 200 MW.
Increase in error from 5:00 to 7:00 h too fast to have time to shut down thermal plants.
Spanish system ran out of downward reserves very rapidly and the only solution to
Exhaustion of downward reserve due to wind forecast errors
Wind reduction instructions, November 2nd 2008
33
Spanish system ran out of downward reserves very rapidly and the only solution to
balance the system was to decrease wind production from 7:22 to 9:30 h.

34. January 23rd and 24th 2009: Storm Klaus. Winds up to 220 km/h hit the Iberian
peninsula.
Most turbines in the north of Spain shut down due to their over-speed protection.
Difference between real and forecasted wind production was greater than 6 000 MW on
Exhaustion of upward reserve due to wind generation tripping
Wind reduction instructions, January 23rd and 24th 2009
34
Difference between real and forecasted wind production was greater than 6 000 MW on
some hours, but since demands were low and thermal plants were connected in real
time due to alert situation there was enough upward reserve to deal with these errors.

35. System Overview
Installed capacity in Spain today
Issues and solutions integrating RE nowadays
Demand coverage
Outline
35
Distributed Generation (Observability/Controllability)
Grid constrains (RdT/RdD)
Behavior facing disturbances (Voltage dips)
Power balance feasibility and RES courtailments
Voltage control
Impact of forecast errors(SIPREOLICO/SIPRESOLAR)
CECRE: Control Centre for Renewable Energies
Conclusions

36. Target: achieve a greater level of integration for renewable energy sources without
compromising system security
Main function: Organise special regime electric production according to the needs of the
electric system.
Control Centre for Renewable Energies (CECRE)
36

37. System Overview
Installed capacity in Spain today
Issues and solutions integrating RE nowadays
Demand coverage
Outline
37
Distributed Generation (Observability/Controllability)
Grid constrains (RdT/RdD)
Behavior facing disturbances (Voltage dips)
Power balance feasibility and RES courtailments
Voltage control
Impact of forecast errors(SIPREOLICO/SIPRESOLAR)
CECRE: Control Centre for Renewable Energies
Conclusions

38. Conclusions
Integrating non manageable generation is a challenging task: Low availability, production not
correlated with consumption, lack of firmness of generation programs and power balance difficulties.
Although these, CECRE and the RESCC have helped to reach a high penetration of special regime
generation in the System making these technologies compatible with security of supply.
Wind forecast has been improving in the last years, being now a basic tool for hot reserve
evaluation. Its accuracy for time scopes from 5 hours to 24 hours in advance affect required levels of
38
evaluation. Its accuracy for time scopes from 5 hours to 24 hours in advance affect required levels of
reserve and helps dispatching manageable generation to counteract wind fluctuations.
CSP plants can adapt their production to the demand necessities, even more if they can storage
heat into salts. But it is necessary to pass the power controllability tests carry out by the SO.
Complying with the new RD 1565/2010 will let the TSO to receive the real time measurements
achieving visibility and controllability of the solar PV generation.
In addition, if facilities are grouped in control centers with real-time contact with the System
Operator through the CECRE, implies that curtailments take less time to be done so less strict
limitations could be planned and placed, increasing RES production and installation.

39. Thanks for your attention!
39
María Sánchez Llorente
masanchez@ree.es