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Dead Battery?

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The Decision to Scrap a Wind Turbine Opportunity Cost, Timing and Policy Johannes Mauritzen, johannes.mauritzen_at_nhh.no NHH Norwegian School of Economics, Bergen – PowerPoint PPT presentation

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Title: Dead Battery?


1
The Decision to Scrap a Wind Turbine
Opportunity Cost, Timing and Policy
Johannes Mauritzen, johannes.mauritzen_at_nhh.noNHH
Norwegian School of Economics, Bergen And
Institute for Industrial Economics (IFN),
Stockholm
October 10th, 2011
2
Data and Methodology
  • Main Data set from Danish Transimission Operator,
    Energinett
  • Date of Installation and Decomission
  • Coordinates
  • Principality
  • Capacity, Tower Height, Rotor Diameter,
    Manufacturer
  • Duration Models
  • Kaplan Meier non-parametric estimation
  • Cox semi-parametric regression model
  • Identification
  • Semi-Instrumental Variables
  • Semi- (regression) discontinuity
  • Proportional Hazards Assumption

3
Total Wind Power Capacity in Denmark
4
Total Wind Power Capacity in Denmark
5
Tariff for Wind Power
16.05.11
Fornavn Etternavn, navn_at_nhh.no
5
6
Scrapped Turbines per Month
7
Scrappage Policies
  • April 1st, 2001 January 1st, 2004
  • Retroactive to 1999
  • Max capacity of 150 kW
  • Subsidy of .17 DKK/kWh
  • 3x scrapped value lt100kW
  • 2x scrapped value gt100, lt150
  • December 15th, 2004
  • 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

8
Kaplan Meier Survivor Function Estimate
9
Kaplan Meier Survivor Function Estimate
10
Kaplan-Meier Survival Estimates (100-200 kW)
11
Kaplan-Meier Survival Estimates (400-500 kW)
12
Turbine Scrappage Hazard Cox Regression
13
(No Transcript)
14
Turbine Scrappage Hazard Cox Regression
15
Turbine Efficiency Indicator
16
(No Transcript)
17
(No Transcript)
18
(No Transcript)
19
(No Transcript)
20
Conclusion and Discussion
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