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© OECD/IEA 2014
Grid Integration of Renewables
Energy Training Week 111 April 2014, Paris
Simon Mueller Analyst – System Integration of Renewables Renewable Energy Division
© OECD/IEA 2014
Context
The integration challenge
Flexibility and system transformation
System friendly VRE deployment
System operation
System planning and investment
Conclusions
Outline
© OECD/IEA 2014 2
© OECD/IEA 2014
Context
The integration challenge
Flexibility and system transformation
System friendly VRE deployment
System operation
System planning and investment
Conclusions
Outline
© OECD/IEA 2014 3
© OECD/IEA 2014
The Grid Integration of Variable Renewables Project - GIVAR
Third project phase at a glance
7 case studies covering 15 countries, >50 in-depth interviews
Technical flexibility assessment with revised IEA FAST tool
Detailed economic modelling at hourly resolution
© OECD/IEA 2014 4
© OECD/IEA 2014
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Japan
Brazil
India
France
Sweden
ERCOT
NW Europe
Italy
Great Britain
Germany
Iberia
Ireland
Denmark
Wind 2012 PV 2012 Additional Wind 2012-18 Additional PV 2012-18
VRE share of total annual electricity output
Note: ERCOT = Electricity Reliability Council of Texas, United States Source: IEA estimates derived in part from IEA Medium-Term Renewable Energy Market Report 2013.
Large-scale integration accomplished today, but more to come
Instantaneous shares reaching 60% and above
Case studies
© OECD/IEA 2014 5
© OECD/IEA 2014
Context
The integration challenge
Flexibility and system transformation
System friendly VRE deployment
System operation
System planning and investment
Conclusions
Outline
© OECD/IEA 2014 6
© OECD/IEA 2014
What shapes the challenge?
Interaction of VRE and the system shape challenge
Integration challenge is system specific
But: limited number of factors on each side
Learning from other system contexts is possible!
Properties of variable renewable energy (VRE)
Flexibility of other power system components
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The GIVAR III case study regions
Power area size (peak demand)
Grid strength
Inter-connection (actual & potential)
No. of power
markets
Geographic spread of
VRE
Flexibility of dispatchable generation
Investment opportunity
India
Italy
Iberia (ES & PT)
Brazil
NW Europe
ERCOT (Texas, US)
Japan (East)
? © OECD/IEA
2014 8
© OECD/IEA 2014
Location Seconds Years
Properties of variable renewables and impact groups
Systems are different – impacts will vary too
But common groups of effects
Low short run cost
Non synchro-
nous
Stability
Uncertainty
Reserves
Variability
Short term
changes
Abun- dance
Scarcity Asset
utilisation
Location constrained
Trans-mission
grid
Modularity
Distribution grid
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© OECD/IEA 2014
Power systems already deal with a vast demand variability Can use existing flexibility for VRE integration
No problem at low shares, if …
© OECD/IEA 2014 10
Exceptionally high variability in Brazil, 28 June 2010
No technical or economic challenges at low shares, if basic rules are followed: Avoid uncontrolled, local ‘hot spots’ of deployment
Adapt basic system operation strategies, such as forecasts
Ensure that VRE power plants are state-of-the art and can stabilise the grid
© OECD/IEA 2014
FAST2 assessment: All power systems can take 25% in annual generation already today.
There is no technical limit on how much variable generation a power system can absorb
But system transformation increased flexibility required for higher shares
Much higher shares technically feasible
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0 10 20 30 40 50 60
Brazil
ERCOT
Iberia
Italy
Japan (East)
NW EUR
Uncurtailed share of VRE in power generation [%]
Curtailment
none
low
medium
high
VRE share 2012
Source: FAST2 assessment.
© OECD/IEA 2014
When VRE are added to a system with adequate capacity:
Situations of low load and high VRE generation VRE curtailment if flexibility insufficient
Negative market prices due to inflexible generation and VRE support mechanisms
Grid bottlenecks in regions with high VRE density Limitations feeding production from the distribution to the
transmission grid
Insufficient evacuation capacity in regions with rapid build out of new VRE capacity
Voltage and frequency stability can be an issue in specific situations
Main short-term challenges
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© OECD/IEA 2014
Higher uncertainty
Larger and more pronounced changes
Main persistent challenge: Balancing
0
10 000
20 000
30 000
40 000
50 000
60 000
70 000
80 000
1 8
15
22
29
36
43
50
57
64
71
78
85
92
99
10
6
11
3
12
0
12
7
13
4
14
1
14
8
Load
leve
l [M
W]
Hours
20% 10% 5% 2.50% 0%
Largerrampsat high shares
More frequent up and down at high
shares
Smoothing effect at low shares
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability; combined effect of wind and solar may be lower, illustration only.
Net-load at different annual VRE shares
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-10 000
0
10 000
20 000
30 000
40 000
50 000
60 000
70 000
80 000
90 000
1 877 1753 2629 3505 4381 5257 6133 7009 7885
Load
leve
l [M
W]
Hours
0% 2.5% 5.0% 10.0% 20%
Lower minimumAbundance
Maximum remains
highScarcity
Changed utilisationpattern
Netload implies different utilisation for non-VRE system
Main persistent challenge: Utilisation
-10 000
0
10 000
20 000
30 000
40 000
50 000
60 000
70 000
80 000
90 000
1 877 1753 2629 3505 4381 5257 6133 7009 7885
Load
leve
l [M
W]
Hours
0% 2.5% 5.0% 10.0% 20%
Base-load
Mid-merit
Peak
Base-load
Mid-merit
Peak
Lower minimumAbundance
Maximum remains
highScarcity
Changed utilisationpattern
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability; combined effect of wind and solar may be lower, illustration only.
© OECD/IEA 2014 14
© OECD/IEA 2014
Context
The integration challenge
Flexibility and system transformation
System friendly VRE deployment
System operation
System planning and investment
Conclusions
Outline
© OECD/IEA 2014 15
© OECD/IEA 2014
Integration vs. transformation
Classical view: VRE are integrated into the rest
Integration costs: balancing, adequacy, grid
More accurate view: entire system is re-optimised
Total system costs
Integration is actually about transformation
Remaining system
VRE
Power system
• Generation • Grids • Storage • Demand Side Integration
© OECD/IEA 2014 16
© OECD/IEA 2014
2. Make better use of
what you have
Op
eratio
ns
1. Let wind and solar play their
part
3. Take a system wide-strategic
approach to investments!
System friendly
VRE
Technology spread
Geographic spread
Design of power
plants
Three pillars of system transformation
© OECD/IEA 2014 17
Investm
ents
© OECD/IEA 2014
Main idea: minimise total system costs, not VRE generation costs alone!
5 aspects:
Deployment volumes
Location and technology mix
Technical capabilities
System friendly power plant design
Curtailment
Cost-effectiveness does not mean cheapest technology where resources are best
System friendly (V)RE deployment
© OECD/IEA 2014 18 Source: adapted from Agora, 2013
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
Share of a
nnua
l gen
eration
[‰]
Conventional turbine configuration
System-oriented turbine configuration
Example: System friendly design of wind turbines reduces variability
© OECD/IEA 2014
2. Make better use of
what you have
Op
eratio
ns
1. Let wind and solar play their
part
3. Take a system wide-strategic
approach to investments!
System friendly
VRE
Technology spread
Geographic spread
Design of power
plants
Three pillars of system transformation
© OECD/IEA 2014 19
Investm
ents
© OECD/IEA 2014
Forecasting of VRE production key strategy for cost-effective operation
Forecasts improve dramatically with shorter horizon
Real-time generation data key for short-term accuracy
More mature for wind than for PV
VRE production forecasts
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0%
5%
10%
15%
20%
25%
1 5 9 13 17 21 25 29 33 37 41 45
Mea
n a
bso
lute
err
or
/ av
erag
e p
rod
uct
ion
Forecast horizon (Hours before real-time)
2008 2009
2010 2011
2012
Accuracy of wind forecasts in Spain
Source: REE
© OECD/IEA 2014
Short scheduling intervals (5min best practice)
Adjust schedules up to real time (5min best practice)
Generation and transmission schedules
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6 7 8 9
Cap
acit
y (M
W)
Time (hours)
Actual load curve
Load schedule -15 minutes
Load schedule -60 minutes
Balancing need 15 min schedule
Balancing need60 min schedule
Impact of scheduling interval on reserve requirements, illustration
© OECD/IEA 2014
Germany has four balancing areas (historic reasons)
Reserve sharing mechanism across four areas
Reduced requirements despite rapid increase of VRE
Co-operation with neighbours
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0
10
20
30
40
50
60
0
1
2
3
4
5
6
7
8
2008 2009 2010 2011 2012
Inst
alle
d V
RE
cap
acit
y (G
W)
Res
erve
req
uir
emen
t (G
W) VRE
capacity
Upward reserves
Downward reserves
+100%
+0%
-40%
Required frequency restoration reserves in Germany
© OECD/IEA 2014
Are your operating reserve and system service definitions VRE ready?
Example Ireland DS3 programme
System service definitions
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• Synchronous Inertial Response• Fast Frequency Response• Fast Post-Fault Active Power
Recovery
• Ramping Margin
0 – 5s 5 – 90s 90s – 20min 20min – 12hr
Inertial
Response
Reserve
Ramping
POR
SOR
TOR1
TOR2
RR
Ramping
SIR
FFR
time
Source: EirGrid • Dynamic Reactive Power
ms – s
Transient Voltage Response
Voltage Regulation
Network
Dynamic
Reactive
Power
Network
Adequacy
Grid 25
s – min min – hr
Steady-state
Reactive
Power
• Steady-state Reactive Power
© OECD/IEA 2014
2. Make better use of
what you have
Op
eratio
ns
1. Let wind and solar play their
part
3. Take a system wide-strategic
approach to investments!
System friendly
VRE
Technology spread
Geographic spread
Design of power
plants
Three pillars of system transformation
© OECD/IEA 2014 24
Investm
ents
© OECD/IEA 2014
* Compound annual average growth rate 2012-20 , slow <2%, dynamic ≥2%; region average used where country data unavailable This map is without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.
Transformation depends on context
© OECD/IEA 2014 25
Stable Power Systems
• Little general investment need short term
Dynamic Power Systems
• Large general investment need short term
Slow demand growth*
Dynamic demand growth*
Maximise the contribution from existing flexible assets
Decommission or mothball inflexible polluting surplus capacity to foster system transformation
Implement holistic, long-term transformation from onset
Use proper long-term planning instruments to capture VRE’s contribution at system level
© OECD/IEA 2014
Large shares of VRE can be integrated without significantly increasing power system costs in the long run.
Achieving this successfully requires a system-wide transformation.
System cost and transformation Test System
© OECD/IEA 2014 26
86-94
104 -119 100 - 112 97-109
0
20
40
60
80
100
120
140
Legacy Transformed
generation
Transformed
generation and 8% DSI
0% VRE 45% VRE penetration
Total system
cost (USD
/MWh)
Grid–high
Grid–low
DSI
Fixed VRE
Emissions
Fuel
Startup
Fixed
non–VRE
© OECD/IEA 2014
Transformation of the generation mix
Significant shift in the dispatchable plant mix due to balancing and flexibility effect
Dispatchable plants need to: Ramp quickly, at short notice and in a wide range
Remain cost-effective at mid-merit and peaking capacity factors
Reservoir hydro can be ideal match
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© OECD/IEA 2014
Importance of coordinated development of grid and generation well understood
Chicken and egg problem for first-off, distant VRE projects Competitive
Renewable Energy Zones (CREZ), Texas
Irish gate system
Appropriate cost recovery is key!
Planning the grid - transmission
© OECD/IEA 2014 28
345 kV double-circuit upgrades identified in
CREZ transmission plan
CREZ, Texas
Source: NREL
© OECD/IEA 2014
Role of distribution grid bound to change fundamentally with rise of distributed generation
Target levels for in-feed, not just consumption?
Planning the grid - distribution
© OECD/IEA 2014 29
Power flows across HV-MV transformer example form Bavaria, Germany
Source: Bayernwerk, Fraunhofer IWES
© OECD/IEA 2014
Existing planning tools struggle to represent VRE contribution to generation adequacy
Match between power demand and VRE profile has a critical impact on capacity credit of VRE Consider firm capacity from VRE over maximum possible geographic footprint
Seek to include structural shifts in power demand when assessing the capacity credit of VRE (may require new tools!)
Capacity credit of VRE – Interconnection and DSI
© OECD/IEA 2014 30
Contribution of Demand Side Integration (DSI) to shape of electricity demand, Great Britain
© OECD/IEA 2014
Context
The integration challenge
Flexibility and system transformation
System friendly VRE deployment
System operation
System planning and investment
Conclusions
Outline
© OECD/IEA 2014 31
© OECD/IEA 2014
Integration challenged result from interaction
On VRE side: 6 relevant properties
Already at low shares:
Avoid uncontrolled local concentrations of VRE power plants (“hot spots”)
Ensure that VRE power plants can contribute to stabilising the grid when needed
Use state of the art VRE forecast techniques
When VRE impact becomes noticeable:
Optimise system and market operations
Deploy VRE in a system-friendly way to maximise their value to the overall system
Conclusions 1/2
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© OECD/IEA 2014
Countries with dynamic power systems should
Approach VRE integration as a question of holistic, long-term system transformation from the onset
Consistent approach to entire generation mix
Chicken-and-egg problem with first, distant VRE sites
Shifted role of distribution grid
Use energy planning tools and strategies that appropriately represent VRE’s contribution at system level
Ensure that accurate techniques are capacity credit assessment techniques
Conclusions 2/2
© OECD/IEA 2014 33
© OECD/IEA 2014
Additional backup
© OECD/IEA 2014 35
© OECD/IEA 2014
-20
0
20
40
60
80
321 322 323 324 325 326 327
GW
Day of the year Wind Solar Demand Net load
Investments in system flexibility – Need for a suite of solutions
© OECD/IEA 2014 36
Solar and wind can be abundant …
… or scarce.
No single resource does it all!
: very suitable, :suitable, o : neutral, : unsuitable Data: Germany 2011, 3x actual wind and solar PV capacity
Example:
Abundance Flexible generation
DSI
Storage
Curtailment
Scarcity Flexible generation
DSI o
Storage
Curtailment
-20
0
20
40
60
80
33 34 35 36 37 38 39
GW
Day of the year Wind Solar Demand Net load
© OECD/IEA 2014
Investment Model for Renewable Energy Systems (IMRES) Test system: Similar size to Germany but isolated system
Dispatchable power plant mix optimised by model
Different levels of VRE penetration – up to 45% in annual generation – were investigated.
Different scenarios: Extreme and purely hypothetical case: a share of 45% VRE in annual
generation was added to the system overnight and only the operation of the remaining system was allowed to change (Legacy case)
Different scenario of the test system considers a more transformative approach. The installed power plant mix is re-optimised in the presence of 45% VRE and additional flexibility options are deployed (Transformed case).
Modelling 45% of wind and solar PV
© OECD/IEA 2014 37
© OECD/IEA 2014
Benefit/cost of flexibility options North West Europe - DSI
Overall system savings of 2.0 bln $/year
DSI costs of 0.9 bln $/year
Note: graph represents the differences between DSI scenario (DSI 8% of overall demand) and baseline scenario
Benefit/cost ratio: 2.2
© OECD/IEA 2014 38
-29 -140-437
-1 539
899128
-2 500
-2 000
-1 500
-1 000
- 500
0
500
1 000
1 500
System benefit DSI costs
Mill
ion
USD
per
yea
r
DSI
Capex CCGT
Fixed Opex
Start up costs
Variable cost incl. fuel
CO2 costs
DSI assumed to be 8% of annual power demand:
• 71% made of heat and other schedulable demand (110 TWh)
• 29% EV demand (44 TWh)
CO2 price USD 30 per tonne Coal price USD 2.7/Mmbtu Gas price USD 8/Mmbtu
© OECD/IEA 2014
Benefit/cost of flexibility options North West Europe
DSI has large benefits at comparably low costs
Interconnection allows a more efficient use of distributed flexibility options and generates synergies with storage and DSI
Cost effectiveness of hydro plant retrofit depend on project specific measures and associated investment needs
Notes: 1) CAPEX assumed for selected flexibility options: interconnection 1,300$/MW/km onshore and 2,600$/MW/km offshore, pumped hydro storage 1,170$/kW, reservoir
hydro 750 $/kW -1,300$/kW (repowering of existing reservoir hydro increasing available capacity). Cost of DSI is assumed equal to 4.7 $/MWh of overall power demand (adjustment of NEWSIS results)
2) Fuel prices and CAPEX ($/kW) for VRE and flexibility options are assumed constant across all scenarios Source: IEA/PÖYRY
2.3 2.2
1.2 1.1 1.1
0.6 - 1.5
DSI + IC DSI IC Storage + IC Storage Hydro capacity boost
Benefit/cost ratio
1
© OECD/IEA 2014 39
© OECD/IEA 2014
2) Better system & market operation
VRE forecasting
Better market operations:
Fast trading Best practice: ERCOT (Texas) – 5 minutes
Price depending on location Best practice: ERCOT – Locational Marginal Prices
Better flexibility markets Example: Reserve provision not always remunerated
Make better use of what you have already!
Example: ERCOT market design
© OECD/IEA 2014 40
