CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
Cost-benefit analysis of the meteorological information for
the electric sector in Spain
Francisco Espejo GilÁrea de Relaciones Internacionales e InstitucionalesAgencia Estatal de Meteorologí[email protected]
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• 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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• 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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Spanish framework• No such study so far• High presence of renewable energy
sources (40% in 2013)
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Conceptual framework• Efficient (ideal) economic system
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Conceptual framework• But in Spain the electric sector is not
balanced: The mean price of energy is below its cost
AEMET, Agencia Estatal de Meteorología
Loss of social efficiency(resources devoted to generate additional quantities of the goodcostlier than the benefit generatedby them)
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• 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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Scenarios to be evaluated• No weather forecasts• Current situation• Quasi-perfect weather forecasts
SCENARIO
GROUP No forecast Current situation
Perfect forecast
Consumers
Same benefit (the price doesn’t change)
Producers Production costs
Less production costs
Even less production
costs
Government
No public expense
AEMET budget Additional investments
Society Loss of social efficiency
Current loss of social efficiency
Perfect-forecast loss of
social efficiency
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Empirical analysis
AEMET, Agencia Estatal de Meteorología
Q=246,313 GWh (mean demand in 2013)P=154,8 €/MWh (mean price 2013)-0.24 (mean elasticity of the electric energyprice vs. demand, estimated from different authors)
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Empirical analysis• Main unit costs by technology
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• Cost of the weather information• AEMET has an analytical accountability
system breaking down the cost of each service provided
AEMET, Agencia Estatal de Meteorología
The revenue obtained by AEMET from the electric sector Is 14,4% of its commercial activity. Therefore (?)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 Alternative is an analysis of joint costjoint cost
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• 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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• 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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• In summary
Cost reduction per MWh Mean (€)
Case 1: No No forecasts forecasts vs. current weather forecasts
Demand 0.179
General effect on the use of renewables
3.951
Total 4.130
Case 2: Current weather forecasts vs. perfect weather forecasts
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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• All this means a benefit for the consumers of 90,582 M€
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• 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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015AEMET, Agencia Estatal de Meteorología
That is, using weather forecasts,there is a reduction in the producerlosses of 1,017 M€.Using perfect weather forecastswould be an additional reduction inthese losses of 140 M€.
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015AEMET, Agencia Estatal de Meteorología
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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• RESULTSNo 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
Public expense (€)
0 657,004 ?
Cost reduction for the producers (€)
1,017,293,000
140,505,000
Loss of social efficiency (DWL, €)
65,715,270 41,171,030 38,230,050
Reduction in the loss of social efficency (DWL, €)
25,544,240 2,940,980
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
• RESULTS: CBA
Using the analytical accountability by AEMET
Using all AEMET 2013 budget
Using all AEMET budget corrected with comparison to other countries (x3)
Benefit (€) 1,017,293,000 1,017,293,000 1,017,293,000
Cost (€) 657,004 91,751,893 275,255,679
C-B Ratio 1,548 11,1 3,7
AEMET, Agencia Estatal de Meteorología
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
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
CBA met info electric sector Spain
TT-SEB2, Dublin, 23 March 2015
¡Muchas gracias!Thank you!
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AEMET, Agencia Estatal de Meteorología
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