CBA met info electric sector Spain
Cost-benefit analysis of the
meteorological information for
the electric sector in Spain
Francisco Espejo Gil
Área de Relaciones Internacionales e Institucionales
Agencia Estatal de Meteorología
[email protected]
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Context
• The Spanish Ministries of Industry, Energy and Tourism
and of Finances and Public Administrations through the
National Observatory on Telecommunications and
Information Society (ONTSI) study the value of the
public information and its re-use by the infomediary
sector (driven by the EU INSPIRE directive)
• ONTSI contacted AEMET to carry out a SEB study of the
meteorological forecasts on the energy sector in Spain.
• IClaves and ACAP were awarded by ONTSI/red.es with
the contract to carry out the study in four months
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Objective
• Estimation of the economic impact of 24 h
weather forecasts on the reduction of costs of
the electricy sector in Spain in 2013
• References
• Teisberg, Weither and Khotanzad (2005) (demand,
USA)
• Leviakängas (2007, Croatia) and Leviakängas and
Hautala (2009, Finland), savings and error-prevention
• NREL-GE Energy (2010, USA, cost reduction with the
use of weather forecasts and renewable sources)
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Spanish framework
• No such study so far
• High presence of renewable energy sources (40%
in 2013)
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Conceptual framework
• Efficient (ideal) economic system
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Conceptual framework
• But in Spain the electric sector is not balanced:
The mean price of energy is below its cost
Loss of social efficiency
(resources devoted to generate
additional quantities of the good
costlier than the benefit generated
by them)
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Conceptual framework
• Weather forecasts help diminish the generating cost of
energy by better forecasting demand in next 24h,
resulting supply response (lowering the supply curve)
and thus approaching the system to its balance
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Scenarios to be evaluated
• No weather forecasts
• Current situation
• Quasi-perfect weather forecasts
SCENARIO
GROUP
Consumers
Producers
No forecast
Perfect forecast
Same benefit (the price doesn’t change)
Production costs
Government No public expense
Society
Current situation
Loss of social
efficiency
Less production
costs
Even less
production costs
AEMET budget
Additional
investments
Current loss of
social efficiency
Perfect-forecast
loss of social
efficiency
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Empirical analysis
Q=246,313 GWh (mean demand in 2013)
P=154,8 €/MWh (mean price 2013)
a=-0.24 (mean elasticity of the electric energy
price vs. demand, estimated from different authors)
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Empirical analysis
• Main unit costs by technology
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Cost of the weather information
• AEMET has an analytical accountability system
breaking down the cost of each service provided
The revenue obtained by
AEMET from the electric
sector Is 14,4% of its
commercial activity.
Therefore (?), the cost of
generating this information
is assumed to be 14,4% of
the cost of producing
commercial products =>
657,004 €
Alternative is an analysis of
joint cost
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Demand forecast (how much the demand curve
moves downwards)
• After Teisberg et al. (2005) The economic value of
temperature forecasts in electricity generation. Bull. AMS
86(12), 1765-1771
• For Spain it is assumed same %_cost reduction as in the
South US (for climate and procedural reasons), that is
0,54% reduction using weather forecasts, plus an extra
0,23% using perfect forecasts.
• With data from Spain, operational costs 33.19€/MWh
• Mean reduction in production costs using weather
forecasts: 0,0054*33.19€/MWh=0.179€/MWh
• Using perfect forecasts: 0,0023*33.19€/MWh=0.076€/MWh
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• Use of renewable energy
• After GE Energy/NREL, but estimates for USA 2017
whereas the case is real in Spain
• Cost savings using renewable sources, from no weather
forecasts to forecasts: 12.52€/MWh (in € of 2013)
• Extra cost savings using renewable sources using perfect
weather forecasts: 1.39€/MWh
• As in Spain the penetration of renewables in the energy
sector (wind+solar) in 2013 was 26%, the Spanish figures
are (using the mean between 2 calculation methods):
• 3.95€/MWh using weather forecasts
• Extra 0.41€/MWh using perfect weather forecasts, but that
would imply no extra worn out from inefficient use of fossil fuel
powerplants, that is an additional saving of 0.157€/MWh
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• In summary
Cost reduction per MWh
Case 1: No forecasts
vs. current weather
forecasts
Case 2: Current
weather forecasts vs.
perfect weather
forecasts
Mean (€)
Demand
0.179
General effect on the use of
renewables
3.951
Total
4.130
Demand
0.076
General effect on the use of
renewables
0.413
Additional worn out saving in
fossil powerplants
0.157
Total
0.570
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• All this means a benefit for the consumers
of 90,582 M€
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• But, as in Spain the price is below the costs, what we get
using weather forecasts is a reduction in the losses of the
producers
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
That is, using weather forecasts,
there is a reduction in the producer
losses of 1,017 M€.
Using perfect weather forecasts
would be an additional reduction in
these losses of 140 M€.
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
As for the reduction of the loss of
social efficiency, there is a 25,5 M€
reduction, using weather forecasts.
An additional 2,9 M€ reduction
would be achieved using perfect
forecasts
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• RESULTS
No weather
forecasts
Current situation Perfect weather
forecasts
Benefit for the
consumers (€)
90,582,220,000
90,582,220,000
90,582,220,000
Benefit for the
producers (€)
- 4,879,605,000
- 3,862,312,000
- 3,721,807,000
0
657,004
Public expense (€)
Cost reduction for
the producers (€)
Loss of social
efficiency (DWL, €)
Reduction in the
loss of social
efficency (DWL, €)
65,715,270
?
1,017,293,000
140,505,000
41,171,030
38,230,050
25,544,240
2,940,980
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
• RESULTS: CBA
Using the
Using all AEMET
analytical
2013 budget
accountability by
AEMET
Benefit (€)
Cost (€)
C-B Ratio
Using all AEMET
budget corrected
with comparison
to other
countries (x3)
1,017,293,000
1,017,293,000
1,017,293,000
657,004
91,751,893
275,255,679
1,548
11,1
AEMET, Agencia Estatal de Meteorología
3,7
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
Remarks:
• A Monte-Carlo sensitivity analysis of the results was made to check
their robustness (positive)
• Limitations of this study
• The neo-classical model of aggregated supply-demand curves is a quite strong
assumption, particularly in a heavily regulated market such as the electric one
• The demand curve is non-linear in practice (many market segments)
• A mean cost curve is used instead of a demand curve, considering the profit
against the producer’s surplus
• Some data are calculated from assumptions from other studies and markets
(elasticity, benefits, demand forecast…) These should be calculated for Spain in
further studies
• The effect of the renewables is taken from a prognosis in the USA, whereas in
Spain these are already implemented and data could be calculated
• The costs of the own electric system to obtain weather info from other sources
than AEMET has not been considered, neither the post-processing costs.
• Given the confines of the study a few other simplifying assumptions were made
• Essential is however whether the study serves the purpose despite simplifications
AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015
CBA met info electric sector Spain
¡Muchas gracias!
Thank you!
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AEMET, Agencia Estatal de Meteorología
TT-SEB2, Dublin, 23 March 2015