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

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]



• 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



• 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)




• Spanish framework• No such study so far• High presence of renewable energy

sources (40% in 2013)




• Conceptual framework• Efficient (ideal) economic system




• 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 goodcostlier than the benefit generatedby them)



• 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




• 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




• Empirical analysis


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)



• Empirical analysis• Main unit costs by technology




• 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 (?)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



• 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




• 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




• 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




• All this means a benefit for the consumers of 90,582 M€




• 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



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€.


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



• 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




• 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




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




¡Muchas gracias!Thank you!

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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