maximizing available wind and hydro resourcesweb.mit.edu/mppgreenislands/gip/workshop... · part ii...
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Maximizing Available Wind and Hydro Resources
Pamela DeAmicis MIT, Technology and Policy Program Advisor: Stephen Connors MIT-Portugal Program May 25, 2011
Agenda
• Thesis Focus • Hydro and Wind Characterization Across Azores • Difficulties Associated with Maximizing Wind
and Hydro Resources • Case Study: Flores • Model Overview
Thesis Focus
• Part 1: Characterize Wind and Hydro Resources ▫ Are hydro and wind patterns complimentary or
compounding?
• Part 2: Maximizing Available Wind and Hydro Resources ▫ How much wind energy can be implemented on small
islands without destabilizing the grid? ▫ How does energy storage change this? ▫ What price should islands be willing to pay for energy
storage?
Part I - Wind and Hydro: Complimentary, or Compounding?
• Wind and Hydro: ▫ Can they be used in tandem to balance one another?
OR ▫ Do these resources display similar patterns and
compound one another?
• How well do renewable resources match demand?
• Three islands utilize wind and hydro • Faial (run-of-river hydro) • Flores (small hydro dam) • Terceira (run-of-river hydro)
Faial: 2008 Wind and Hydro
Total Generation Hydro Generation
Wind Speed Wind & Hydro
Faial: 2008 Wind and Hydro
Total Generation Hydro Generation
Wind Speed Wind & Hydro
Highest Demand
Lowest Renewable Potential
Highest Renewable Potential
Flores: 2008 Wind and Hydro
Total Generation Hydro Generation
Wind Speed Wind & Hydro
Flores: 2008 Wind and Hydro
Total Generation Hydro Generation
Wind Speed Wind & Hydro
Highest Demand
Lowest Renewable Potential
Highest Renewable Potential
Terceira: 2009* Wind and Hydro
Total Generation Hydro Generation
Wind Speed Wind & Hydro
*Wind installed in 2008; 2009 is first complete year
Terceira: 2009* Wind and Hydro
Total Generation Hydro Generation
Wind Speed Wind & Hydro
*Wind installed in 2008; 2009 is first complete year
Highest Demand
Lowest Renewable Potential
No Data
Highest Renewable Potential
Wind and Hydro: Results
• Flores has hydro generation throughout the year • Terceira and Faial have limited generation in summer and fall
Demand Renewable Resources Diurnal Patterns Highest after sunset in winter No significant matching pattern
Diurnal Patterns Lowest in early morning, year-round
No significant matching pattern
Seasonal patterns: Winter
2nd Lowest demand - all islands Highest renewable resources – all islands
Seasonal patterns: Spring
Lowest demand - all islands 2nd highest renewable resources – all islands
Seasonal patterns: Summer
Highest demand - all islands Lowest renewable resources – all islands
Seasonal patterns: Fall
2nd highest demand - all islands 2nd lowest renewable resources – all islands
Part II – Maximizing Resources for Electricity Generation • Complexities of Small Island Energy Systems • Renewable sources often fluctuate quickly • Especially true of wind • Mostly unpredictable
• Ramping wears thermal generators • Thermal generators need to back up renewable sources
• Storage potentially reduces both of these needs
Case Study: Flores
• Population: 4,000 (2%) • Highest utilization of
renewable energy (48%) • Installed Capacity: • 2.2 MW thermal • 1.5 MW hydro • 0.6 MW wind
• Small hydro dam • ~ 6 MWh
2008 Monthly Generation
2008 Seasonal Variation in Generation
Renewable Generation Patterns - Wind Total Monthly Generation – Wind, 6 Year Average
Renewable Generation Patterns - Hydro Total Monthly Generation - Hydro, 18 Year Average
Model Overview
• 7-day hourly unit commitment • Stochastic wind, hydro; ▫ 9 Possibilities
• Model outputs generation in all scenarios • Expected Value Solution ▫ Cost of Running System ▫ Deterministic optimization solution using
weighted average of randomized wind, hydro ▫ Wind, hydro result in lower value
Scenarios
• Seasons: ▫ Winter (Dec.-Feb.) ▫ Spring (March-May) ▫ Summer (June-Aug.) ▫ Fall (Sept.-Nov.)
• Years: ▫ 2008 - Base ▫ 2012 - Planned generation increase completed ▫ 2018 - 75% renewable goal
1) No additional generation 2) Various wind amounts 3) Adding in storage
Sample Model Output – No Battery
Input: January 1 – 7 2008
Demand, Wind, Hydro Wind: 2.3 generated levels Hydro: 1.25 generated levels
0
0.5
1
1.5
2
2.5
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
StorageIn
StorageGen
Hydro
Wind
D4
D3
D2
D1
Results: Total Cost € 26,052 Total Diesel 22.81 MWh Storage Gen 0 MWh
Sample Model Output – Battery
0
0.5
1
1.5
2
2.5
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
StorageIn
StorageGen
Hydro
Wind
D4
D3
D2
D1
Input: January 1 – 7 2008
Demand, Wind, Hydro Wind: 2.3 generated levels Hydro: 1.25 generated levels
Results: Total Cost € 25,698 Total Diesel 20.12 MWh Storage Gen 3.68 MWh
Questions?
Back-Up Slides
Wind and Hydro: Results Continued
Demand Wind Hydro Combined Demand Wind Hydro CombinedWinter 0.56 0.30 0.41 0.36 Winter 0.69 0.21 0.46 0.33Spring 0.48 0.18 0.31 0.25 Spring 0.25 0.14 0.13 0.13Summer 0.58 0.21 0.18 0.19 Summer 0.00 0.00 0.00 0.00Fall 0.58 0.25 0.17 0.21 Fall 0.22 0.01 0.01 0.01
Demand Wind Hydro Combined Demand Wind Hydro CombinedWinter 0.58 0.24 0.35 0.30 Winter 0.68 0.20 0.08 0.14Spring 0.56 0.20 0.19 0.20 Spring 0.63 0.16 0.00 0.08Summer 0.62 0.14 0.05 0.10 Summer 0.68 0.11 0.00 0.06Fall 0.60 0.19 0.01 0.10 Fall 0.67 0.17 0.04 0.10
Demand Wind Hydro Combined Demand Wind Hydro CombinedWinter 0.50 0.08 0.32 0.20 Winter 0.53 0.22 0.06 0.14Spring 0.47 0.00 0.24 0.12 Spring 0.50 0.18 0.07 0.13Summer 0.52 0.07 0.00 0.04 Summer 0.52 0.13 0.00 0.07Fall 0.51 0.21 0.00 0.11 Fall 0.53 0.19 0.00 0.10
Terceira Terceira
Faial Faial
2008 2009
2009
Flores
2008 2009
2008
Flores
Renewable Generation Patterns - Wind Total Monthly Generation – Wind, 6 Year Average
Average Monthly Wind Speed – 2008 Only
0.000
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Capacity Factor
Month
Montly CF
Seasonal CF
Monthly WS
Seasonal WS
Wind Speed vs. Generation - Winter
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78EOBV01 Jan
78EOBV01 Jan
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78EOBV01 Feb
78EOBV01 Feb
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78EOBV02 Jan
78EOBV02 Jan
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78EOBV02 Feb
78EOBV02 Feb
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78EOBV01 December
78EOBV01 Dec.
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78EOBV02 December
78EOBV02 Dec.
Wind Speed vs. Generation - Spring
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78EOBV01 March
78EOBV01 March
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78EOBV01 April
78EOBV01 April
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78EOBV01 May
78EOBV01 May
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78EOBV02 March
78EOBV02 March
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78EOBV02 April
78EOBV02 April
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78EOBV02 May
78EOBV02 May
Wind Speed vs. Generation - Summer
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78EOBV01 June
78EOBV01 June
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78EOBV02 June
78EOBV02 June
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78EOBV01 July
78EOBV01 July
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78EOBV01 August
78EOBV01 August
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78EOBV02 July
78EOBV02 July
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78EOBV02 August
78EOBV02 August
Wind Speed vs. Generation - Fall
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78EOBV01 September
78EOBV01 Sept.
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78EOBV01 October
78EOBV01 Oct.
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78EOBV01 November
78EOBV01 Nov.
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78EOBV02 September
78EOBV02 Sept.
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78EOBV02 October
78EOBV02 Oct.
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78EOBV02 November
78EOBV02 Nov.
Wind Turbine Efficiency Curve
0.00
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-‐
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Outpu
t (KW
)
Wind Speed (m/S)
300 kW Wind Turbine
Power (kW)
P Effieincy
Winter 2008 Power Curve
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Actual
Potential
With Effiency
Sample Model Output – No Battery
Input: January 1 – 7 2008
Demand, Wind, Hydro Wind: 1.8 MW (3 X current) Hydro: 1.2 MW (1 X current)
Results: Total Cost € 25,583 Total Diesel 18.06 MWh Storage Gen 0 MWh
0
0.5
1
1.5
2
2.5
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
StorageIn
StorageGen
Hydro
Wind
D4
D3
D2
D1
Sample Model Output –Battery
Input: January 1 – 7 2008
Demand, Wind, Hydro Wind: 1.8 MW (3 X current) Hydro: 1.2 MW (1 X current)
Results: Total Cost € 26,125 Total Diesel 15.36 MWh Storage Gen 4.05 MWh
0
0.5
1
1.5
2
2.5
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
StorageIn
StorageGen
Hydro
Wind
D4
D3
D2
D1