Upload
jory
View
37
Download
4
Embed Size (px)
DESCRIPTION
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control. Funded by and in collaboration with EPRI Tony Rogers, DNV Co- authors : Alex Byrne, Tim McCoy, Katy Briggs. Introduction. - PowerPoint PPT Presentation
Citation preview
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine ControlFunded by and in collaboration with EPRI
Tony Rogers, DNVCo-authors: Alex Byrne, Tim McCoy, Katy Briggs
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
2
Introduction
Goal of project: Leverage existing technical research into estimates of cost of energy of nacelle-based light detection and ranging (lidar) turbine control
This presentation- Lidar applications to control- Cost model- Results and sensitivity- Conclusions and recommendations
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
3
Controls Application of Lidar Applications considered:
- Nacelle-mounted, forward-looking lidar- Options: load reduction, increased energy
Advantages- Less biased than nacelle anemometry- Advanced knowledge of wind
Challenges- Wind evolves after measurement point- High lidar costs- Technical complexity- Lidar reliability- Turbulence
DTU Tjæreborg experimentwww.vindenergi.dtu.dk
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
4
Controls Application of Lidar
F. Dunne, E. Simley, and L.Y. Pao NREL/SR-5000-52098
Typical example:
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
5
Cost Model Approach
Benefits based on:- Reported model and test results
Benefits- Increased energy capture - Reduced operations and maintenance (O&M)
costs
Costs- Lidar costs- Increased capital or O&M costs
Cost model: equivalent net present value (NPV) method to calculate change in cost of energy
Performed uncertainty and sensitivity analyses using Monte Carlo simulation
Wind Iris Prototype at the Alpha Ventus Offshore Project, Germany.
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
6
Benefits Considered and Strategy for Capturing Benefits
Yaw control or gust tracking- Increased power capture
Reduced loads- Reduced O&M and downtime costs- Extended life - Turbine redesign
2. Larger Rotor
3. Taller Tower
Year 1
Year 20
Year 26
1. Extended Life
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
7
Magnitude of Lidar Benefits
Overview- Limited test results- Modelling has many assumptions
- Interdependencies often not considered
Load reduction and energy capture estimates transformed into estimates of O&M cost and turbine availability improvements- DNV KEMA’s estimates of lidar benefits from
optimized controls for increased energy capture and load reduction:
CTW’s Vindicator atop a Nacelle
Increased energy due to optimized controls 0.6%
Reduced turbine O&M costs (life-time average) 6%
Increased turbine availability, reduced O&M downtime 0.4%
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
8
Costs Considered
Capital cost of lidar- Sources: lidar vendors- Considered volume pricing—fairly uncertain
Lidar O&M cost- Sources: lidar vendors—very uncertain
Increased component O&M costs- Yaw motors, pitch motors, etc.- Source: internal DNV KEMA database
Added cost for larger rotor or taller tower - Source: theoretical scaling
Added O&M costs with life extension- Source: internal DNV KEMA database
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
9
Scenarios and Benefits
Scenario
Benefit
Scenario 1 Scenario 2 Scenario 3
2.5 MW Turbines, Retrofitted Lidar,
Extended Life
5 MW Turbines, Integrated Lidar,
Larger Rotor
5 MW Turbines, Integrated Lidar,
Taller Tower
Increased energy/revenue due to extended project life
6-year extension; 30% energy increase
N/A N/A
Increased energy due to larger rotor N/A 6% increase in rotor
area; 4% energy increase
N/A
Increased energy due to taller tower
(assumed wind shear exp: 0.2) N/A N/A
8% increase in tower height; 3% energy
increase
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
10
Cost Benefit Monte Carlo Results
-16%
-14%
-12%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
Pe
rce
nt
Ch
an
ge
in
CO
E Scenario 3: Taller tower
Scenario 2: Larger ro-tor
Scenario 1: Life exten-sion
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
11
Conclusions and Recommendations for Future Work
Conclusions:- Extended life and taller tower scenarios: Noticeable impact on cost of energy (COE)- Larger rotor scenario: increased capital cost of larger rotor outweighs benefits- Biggest factor in COE impact: strategy of capturing loads benefits- Large uncertainty still exists on the loads benefits and some costs
Recommendations for future work: - Offshore considerations- Required to reduce uncertainty:
- Prototype tests that include lidar-based pitch control- Firmer volume capital and O&M costs of lidar- Better understanding of loads reduction effects on O&M costs
- Fatigue- Extreme limited designs
- Address wind evolution problem- Potential improvements in lidar capabilities (more beams, accuracy, reliability)
Expected Impacts on Cost of Energy through Lidar Based Wind Turbine Control
April 17, 2012
www.dnvkema.com