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.

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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