Transcript Economic Regulation - The United States Association for

Imperial College
London
Supporting wind: European
examples and problems
David Newbery
USAEE/IAEE North American Conference Plenary:
Developments in Electricity Generation and Distribution
Anchorage, Alaska, 31st July 2013
http://www.eprg.group.cam.ac.uk
1
Imperial College
London
•
•
•
•
•
Outline
Why support wind?
How is wind supported and financed?
Efficient market design vs reality
Lessons from the UK
Towards a better support system
D Newbery 2013
2
Imperial College
London
Logic of 20-20-20 Directive
• Supports RES deployment to drive down costs
– induces investment => learning-by-doing
• Solution to equitable EU burden sharing
=> all countries contribute to public good of learning
• Learning comes from:
– design (cost, reliability, controllability, etc)
– production, installation, siting/planning, grid
integration
but not from operation (provided reliable)
D Newbery 2013
3
Learning justifies Renewables Directive
Costs after doubling relative to
initial value
Source: IEA
D Newbery
Learning curves for generation technologies
2010 price
$2,000/kWp
=$(1990)1,220
Start of ETS
39GW 2010
1
Right measure
of LbD driver
5
Source: N. Nakicenovic, A. Grübler, and A. McDonald, eds., Global Energy Perspectives (CUP, 1998).
Renewables support replaces R&D
UK Electricity R&D intensity
3.0%
2.5%
ROCs
hydrogen and fuel cell
2.0%
nuclear fission and fusion
Renewables
1.5%
fossil fuels
Total ESI R&D (estimate)
1.0%
0.5%
D Newbery 2013
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
0.0%
1974
percent electricity revenue
other power
6
Imperial College
London
Characteristics of wind
• Low capacity factor, very site specific
= 25% on-shore, 36% off-shore in GB
=> potentially considerable site rent
• High variability
– requires considerable flexible dispatchable reserves
– creates new demands for System Operator
• Low predictability day-ahead
– hard to contract ahead, risk of imbalance
Support design needs to address these
D Newbery 2013
7
Considerable locational variation
D Newbery Cranfield 2012
Source Renewable Energy Foundation
8
Seasonal capacity factors
Average monthly capacity factor GB on-shore wind, 1994-2005 wind data
60%
50%
1994
1999
2004
1998
2000
1997
av 1994-2005
2003
1996
2001
2005
2002
1995
percentage
40%
30%
20%
10%
0%
Jan
Feb
Mar
April
May
Source: Green and Vasilakos (2010)
June
July
Aug
Sep
Oct
Nov
Dec
Hourly average wind and total demand
50%
70,000
45%
60,000
50,000
35%
30%
40,000
25%
30,000
20%
Jan wind CF LHS
May wind CF LHS
Aug wind CF
Jan demand
May demand
15%
10%
5%
0%
20,000
10,000
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hours ending
Source: Green and Vasilakos (2010)
Demand, MW
capacity factor %
40%
Imperial College
London
Supporting wind
• Market failures:
– CO2 under-priced
– learning benefits not valued
– risks higher than for conventional generation
• Pricing CO2 problematic - raises energy prices
=> Britain has adopted Carbon Price Floor, others might prefer
CO2 intensity target or RE target
• Identify benefits from building and operation
=> availability subsidy + average (?) value of energy?
• Reduce risks through contract design
Object is to deliver benefits at least system cost
D Newbery 2013
11
Carbon prices have crashed
EUA price October 2004-March 2013
35
30
OTC Index First Period
Second period Dec 2008
25
Euro/t CO2
Second period next Dec
20
15
Second
period
10
5
start of
ETS
0
Oct- Apr- Oct- Apr- Oct- Apr- Oct- Apr- Oct- Apr- Oct- Apr- Oct- Apr- Oct- Apr- Oct04 05 05 06 06 07 07 08 08 09 09 10 10 11 11 12 12
Source: EEX
UK’s Carbon Price Floor - in Budget of 3/11
EUA price second period and CPF £(2012)/tonne
to £70/t by 2030
£30
£(2012)/tonne CO2
£25
second period price
Carbon Price Floor
£20
Corrective tax
£15
Corrective tax
£10
As at 1 Jun 2011
£5
Forward prices
£0
Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19 Jan-20
D Newbery 2013
Source: EEX and DECC Consultation
13
UK price movements: 2007 to 2009 in €
120
Fossil plant naturally hedged
100
60
40
20
1Ja
n09
1Oc
t-0
8
1Ju
l-0
8
8
1Ap
r-0
1Ja
n08
1Oc
t-0
7
1Ju
l-0
7
1Ap
r-0
7
0
1Ja
n07
€/MWhe
80
Electricity forward 2010 (€/MWh)
Gas cost forward (2010) + EUA
Coal cost forward (2010) + EUA
EUA price in €/tCO2
Gas and coal-fired generation costs move in line with electricity prices
Imperial College
London
Contracts for wind
• Variety of Feed-in-tariff (FiT)s:
– FiT, Premium FiT (pFiT), Contract-for-difference
– need to address risk, location, support
• Germany, Spain, Denmark adopted FiT
– transfers all risk to TSO, poor locational signals
– rapid roll-out, Germany extracts wind rent
• UK 3 models: auctions, ROC  pFiT, CfD
– locational transmission charges, single GB price
How do they compare?
D Newbery 2013
15
MW
CCC’09 UK 2020 target is 27,000 MW
Installed wind capacity in MW
30,000
25,000
20,000
15,000
UK’s target looks
feasible at DE
roll-out rate
10,000
5,000
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Denmark
Germany
D Newbery 2013
Spain
UK
17
Imperial College
London
UK experience
• RE auctions drove down prices
– but no penalty for non-delivery => overoptimism
=> decreasing proportion actually delivered
• Renewable obligation certificates (ROCs)
– pay premium on wholesale price & sell to retailers
• no rent extraction, investment concentrated in Scotland
=> risky , benefits incumbent vertical gentailers
=> low roll-out despite excellent wind
• Electricity Market Reform proposes CfDs
– but requires windfarms to sell in illiquid wholesale market
– removes wholesale price risk but not balancing risk
D Newbery 2013
18
Imperial College
London
Towards a better system
• System Operator to contract for wind
– ideally through tender auction
• offer different support profiles, tenors, indexed or not
– select least total cost (transmission, balancing, CO2)
– or secure sites first and then auction
=> extracts unnecessary rent => least consumer cost
• Agree with EU on where learning benefits lie
– Reliable capacity? => pay for availability not MWh
• avoids negative prices, avoids distorting location
D Newbery 2013
20
Location choices under LMP and spot pricing for wind
N: 2,500 hrs/yr
T cost
£15/
MWh
With ROCs wind farm
inefficiently locates at N
P1 £35/MWh
(after new T)
ROC = £50/MWh
=>£87.5k/MW/yr
=>£212.5k + ROC
Pay wind for availability
+ average spot price => efficient E
E: 2,000 hrs/yr
C: £50/MWh
£49/MWh
=>£98k/MW/yr
=>£198k + ROC
Imperial College
London
Conclusions
• Wind suffers market failures - CO2, risk and learning
• These can be separately addressed with good contracts
• learning - club good that needs collective agreement
– on what it delivers and how to induce that efficiently
• Most RE support is poorly designed as hard to
agree on club goods and prone to lobbying
– fails to recognise system costs: location, balancing
– fails to extract rent to reduce support cost
All of these concerns are amplified off-shore
D Newbery 2013
22
Imperial College
London
Supporting wind: European
examples and problems
David Newbery
USAEE/IAEE North American Conference Plenary:
Developments in Electricity Generation and Distribution
Anchorage, Alaska, 31st July 2013
http://www.eprg.group.cam.ac.uk
23