Dead Battery?

The Decision to Scrap a Wind Turbine
Opportunity Cost, Timing and Policy
Johannes Mauritzen, [email protected]
NHH Norwegian School of Economics, Bergen
And
Institute for Industrial Economics (IFN), Stockholm
October 10th, 2011
www.nhh.no
Data and Methodology
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Main
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Duration Models
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Data set from Danish Transimission Operator, Energinett
Date of Installation and ”Decomission”
Coordinates
Principality
Capacity, Tower Height, Rotor Diameter, Manufacturer
Kaplan Meier non-parametric estimation
Cox semi-parametric regression model
Identification
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Semi-Instrumental Variables
Semi- (regression) discontinuity
Proportional Hazards Assumption
Total Wind Power Capacity in Denmark
Total Wind Power Capacity in Denmark
16.05.11
Fornavn Etternavn, [email protected]
Tariff for Wind Power
16.05.11 Fornavn Etternavn, [email protected]
5
Scrapped Turbines per Month
Scrappage Policies
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April
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December 15th, 2004
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1st, 2001 – January 1st, 2004
Retroactive to 1999
Max capacity of 150 kW
Subsidy of .17 DKK/kWh
• 3x scrapped value <100kW
• 2x scrapped value >100, <150
Max capacity of 450 kW
Subsidy of .12 DKK/kWh
• 2x scrapped capacity
• limited to 12,000 FLH, max of .48 DKK total tariff
• February 21, 2008 – extra .08 DKK/kWh hour added
16.05.11
Fornavn Etternavn, [email protected]
Kaplan Meier Survivor Function Estimate
Kaplan Meier Survivor Function Estimate
16.05.11
Fornavn Etternavn, [email protected]
Kaplan-Meier Survival Estimates (100-200 kW)
Kaplan-Meier Survival Estimates (400-500 kW)
Turbine Scrappage Hazard: Cox Regression
16.05.11
Fornavn Etternavn, [email protected]
16.05.11
Fornavn Etternavn, [email protected]
Turbine Scrappage Hazard: Cox Regression
Turbine Efficiency Indicator
16.05.11
Fornavn Etternavn, [email protected]
16.05.11
Fornavn Etternavn, [email protected]
16.05.11
Fornavn Etternavn, [email protected]
Conclusion and Discussion