power and cost predictions for an offshore wind … · power and cost predictions for an offshore...
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POWER AND COST PREDICTIONS FOR AN OFFSHORE WIND-WAVE-STORAGE SYSTEM
Jocelyn Kluger PhD Candidate Massachusetts Institute of Technology Thesis advisors: Professors Alex Slocum and Themis Sapsis
NAWEA 2015 Symposium June 8, 2015
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Introduction 2
Introduction OWC Optimization Supply Smoothing Conclusions
Figure by M. Haji
Goals 1) Minimize cost, stress of
OWC 2) Minimize CEEP of nearby
gas plant Ocean Renewable Energy Storage Figure from: S. Okuhara et al., J. Fluid
Dynamics 2013
Wells turbine rotates in one direction independent of water flow
Oscillating Water Column array 500 MW offshore wind farm
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Why combine 3 systems? 3
¨ Smooth out rapid fluctuations in available power
¨ Collocation reduces Cost ¤ Shared transmission and mooring lines ¤ ORES can double as the anchor point
Introduction OWC Optimization Supply Smoothing Conclusions
Based on 2007 wind and wave data
500 MW wind farm + 47 MW wave farm + 2000 MWh ORES
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Goals 4
1. Optimize OWC array Levelized Cost of Energy ($/kWh)
Ø Vary geometry
Introduction OWC Optimization Supply Smoothing Conclusions
2. Smooth out the offshore system power supply
Ø Vary energy storage and wave farm capacity
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Power Model
¨ Frequency domain: For each column
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What are coefficients? What is Fe? How calculate annual power? Which variables are from source, and which from simulation
For each water column in tube:
Adjustable turbine linear damping
Introduction OWC Optimization Supply Smoothing Conclusions
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Optimization Procedure
1) Vary D and T 2) Constrain water plane area: NAw < 20ATower
¤ Limit wind turbine stress and motion 3) Use annual wave data 4) Constrain response
¤ displacement, Y<T ¤ Maximum power, PMax< Mean(Punrestricted)
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ATower AW
N Columns
Introduction OWC Optimization Supply Smoothing Conclusions
Sample Sea State
Sea State Probability Distribution
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Power Results ¨ ff
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Cost estimate
¨ Cost from turbine capacity, structural mass, hinge components ¤ Let O & M =, Lifetime= 20 years
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0
100
200
300
400
500
600
700
$/kW
Annual expenses per kW
Operations & Maintenance Installation
Steel mass
Wells turbine
0
1000
2000
3000
4000
$/kW
Installed Capital Cost per kW
Installation
Steel mass
Wells turbine
$0.83 Kg
x 0.115 Portion of capital cost
paid each year
Based on: Sandia Labs Report 2014-18311 and Tegan Cost of Wind Energy Introduction OWC Optimization Supply Smoothing Conclusions
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Cost Results ¨ ff
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Power Capacity Then, capacity factor on top of capacity Capital Cost Capacity factor, LCOE
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Optimal System ¨ ff
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Parameter Value
Average annual power 0.25MW
Capacity 0.36 MW
Capacity factor 0.7
Capital Cost $1.3 million
Levelized Cost of Energy $67/MWh
Introduction OWC Optimization Supply Smoothing Conclusions
6 Columns
D=12 m
2T=14 m
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Supply Smoothing 11
Surplus Renewable Power Supply Insufficient Renewable Power Supply Goals:
1) Keep each hour’s power within +10% previous hour’s power
2) Minimize cost n Vary storage and wave farm capacity
500 MW wind farm + 47 MW wave farm + 2000 MWh ORES
Introduction OWC Optimization Supply Smoothing Conclusions
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Control strategy to smooth output power 12
Performance measure: • Minimize mean (S2-S1) • Minimize LCOE
¨ Effect of 1. energy storage capacity 2. Wave power
¤ Use ORES to supply/absorb power as required, if it can ¤ Try to maintain ORES stored energy at 50% capacity
ORES absorbs difference
Power
Acceptable net S2net values
S2
S2
S2net
S2net
0.9S1net
Wind + Wave Supply Wind + Wave + ORES Net Supply
time t2= t1+1 hour Introduction OWC Optimization Supply Smoothing Conclusions
S1net
Power (MW)
0.9S1net
Acceptable net S2net values
S2
S2
S2net
S2net
1.1S1net
Time (hr) t1 t2
S2
S2net
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Supply-Demand Matching 13
Average hourly gas plant fluctuation for varied wave and ORES capacity and total system cost
Introduction OWC Optimization Supply Smoothing Conclusions
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Conclusions 14
Introduction OWC Optimization Supply Smoothing Conclusions
0
2
4
6
8
10
$ Billion
Installed Capital Cost
Storage
Wave farm
Wind farm
Levelized Cost of Energy
Capital Cost
Parameter Value
Levelized Cost of Energy $287/MW
Capacity 780 MW
Capacity factor 0.51
Maximum hourly power fluctuation
413 MW (12 times per year)
Best “smoothed-power output” wind-wave-storage system (room for improvement)
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Future Work 15
¨ Optimize wave device power ¤ Floating device, backward-bent duct
¨ Predict stress and motion induced on wind turbine ¨ Experimentally verify theory ¨ Energy storage optimization
Introduction OWC Optimization Supply Smoothing Conclusions
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Acknowledgements 16
Much thanks to... ¨ Maha Haji ¨ My PERG labmates ¨ My advisors, Prof.s Themis Sapsis and Alex Slocum
Introduction OWC Optimization Supply Smoothing Conclusions
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Conclusions 17
Introduction OWC Optimization Supply Smoothing Conclusions
0
2
4
6
8
10
$ Billion
Installed Capital Cost
6.4 GWh Storage
275 MW Wave farm
500 MW Wind farm
Levelized Cost of Energy
Capital Cost
Parameter Value
Levelized Cost of Energy $287/MW
Capacity 780 MW
Capacity factor 0.51
Maximum hourly power fluctuation
413 MW (12 times per year)
Best “smoothed-power output” wind-wave-storage system (room for improvement)
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Thank you! 18