solar resource assessment from prospecting to … · solar resource assessment from prospecting to...

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Solar Resource Assessment:

From prospecting to project finance

Presented By:

29 May 2013

Pascal Storck, Ph.D. COO of 3TIER

Rodrigo Stuart, Director Comercial of Three Energy

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3TIER Understands Weather Impacts on Renewable Energy

•  60 employees worldwide focused on reducing the risk of financing, owning and operating wind and solar projects. •  Forecast 43 GW of worldwide wind installed capacity •  Extensive international wind resource assessment •  Solar assessment & forecasting

•  Headquarters in Seattle, WA, USA •  Offices in India, Latin America, China, and

Europe (UK and Spain) •  Our approach for solar resource estimation

has been used to secure over $5 Billion in project financing worldwide.

3TIER

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3TIER’s Products and Services

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Why Perform a Solar Resource Assessment?

Answer Key Questions in Order to Mitigate the Risk Associated with a Renewable Energy Development

•  Where to build a project? •  Is the resource available when needed? •  What is the long-term variability and uncertainty?

Which helps you understand •  Optimal locations for development •  How quickly the plant will pay back the investment •  Electricity Integration Challenges and Solutions •  Energy Storage Feasibility

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When is a project bankable?

Resource assessment for financing utility scale projects solar projects

»  The most confident resource estimates depend on high-quality ground observations combined with context from long-term references (satellite and NWP).

»  Early stage assessments can be done at low cost but with relatively high uncertainty.

»  Task is to reduce uncertainty throughout the development process at minimum cost.

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How does solar resource affect bankability? Moody’s Investor Services (July 2010)

“…there has to be a high degree of confidence that solar irradiation will meet or exceed certain minimum levels. For PV solar projects, Moody’s will likely use a P90 forecast in calculating base case financial ratios…”

•  Bankability is about understanding uncertainty and managing risk.

•  So how do you get the highest P90 possible, while retaining investor confidence?

•  About that $5 Billion . . . •  Lessons learned from wind sector . . .

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It’s a big world. Where do you start?

Global Standard Error: 5% GHI, 9% DNI

Satellite Derived Estimate of Global Irradiance based on 11+ years hourly data.

3TIER

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What Are We Looking For?

GHI – Global Horizontal Irradiance

DNI – Direct Normal Irradiance

DIF – Diffuse Irradiance

Global horizontal irradiance is the total amount of shortwave radia=on received from above by a horizontal surface. This value is of par=cular interest to photovoltaic installa=ons and includes both direct radia=on and diffuse radia=on.

Direct radia=on is solar radia=on that comes from the direc=on of the solar disk in the sky. Important for Concentra=ng Solar Power installa=ons and tracking Photovoltaic installa=ons.

Diffuse radia=on is solar radia=on that has been scaGered by molecules and par=cles in the atmosphere and comes equally from all direc=ons..

On a clear day, most of the solar radia3on received by a horizontal surface will be direct radia3on, while on a cloudy day most will be diffuse

radia3on.

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Case Study: Rajasthan GHI & DNI

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There are various sources of satellite based observation data. Some are being used without comparison to observations to develop solar projects. Source Annual Avg GHI

(kWh/m2 /year) Annual Avg DNI (kWh/m2 /year)

NREL Raw 2,100 2,100 NASA Raw 1,900 N/A 3TIER Raw 1,900 1,800

Recent evidence from observations and production in Rajasthan suggest that GHI estimates from satellite are good but DNI is over-stated. At 10% uncertainty, these estimates are statistically identical. New emphasis on collecting high-quality DNI measurements in Rajasthan.

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Why Not Just Use TMY Data? “Simple “TMY” (Typical Meteorological Year) formats are not sufficient for building major projects.”

Venkataraman, S., D’Olier-Lees, T. "Key Credit Factors.” Standard and Poor’s Solar Credit Weekly 29.42 (2009)

“The TMY should not be used to predict weather for a particular period of time, nor is it an appropriate basis for evaluating real-time energy production or efficiencies for building design applications or solar conversion systems.”

NREL Technical Report 2008

TMY data are for a typical year, but every year is atypical. TMY data do not allow you to understand variability TMY data can’t be directly compared to observations. And if TMY data are derived from Satellite or other proxy data then they can have considerable error . . .

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Satellite data, by themselves, are not strictly bankable.

•  Satellite derived estimates of solar irradiance have a fairly large uncertainty (10%)

•  A bankable study can be completed but the spread between the P50 and P90 may result in unfavorable financing terms.

•  So how to go about reducing uncertainty to get the highest P90 possible?

3TIER

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3TIER Approach: Ground Observations + Context = Project

3TIER

+ =

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Methods for solar resource assessment

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Solar Resource Assessments Can Be Done Different Ways

•  Atmospheric Modeling

+

»  Ground Station Observations

»  Satellite Derived Data

Or you can combine methods…. 3TIER uses all three in its comprehensive resource assessment work.

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Atmospheric Modeling

Cons » Clouds are not always

accurately modeled

Pros » Long-term record can be

created •  Able to model any

location globally

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Satellite Derived Assessments

Cons •  Greater uncertainty than

observations (over the same time period)

•  Known issues with satellite modeling include areas of high albedo, turbidity modeling, areas of snow cover and satellite degradation

Pros •  Consistent global

approach »  Interannual variability

captured with multiple years of data •  Satellite derived data is

known to be the most accurate source of irradiance information beyond 25 km of a well-maintained ground station (Zelenka et al., 1999)

•  Modeled data based on actual observations

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Satellite Derived Assessments

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Why bother with installing ground observations if you have satellite based data?

•  Satellite data can be wrong!

USA: Desert Rock

Israel France

Africa

Satellite Observed Corrected

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Ground Station Assessments

Cons •  Few on-ground

observations available and most are short-term

•  Inaccurate to interpolate these measurements to other locations

•  Performance and prices vary

Pros » High accuracy if properly

maintained •  Critical part of solar

resource assessment, necessary to sort out local variability effects

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Why bother with satellite data if you have a year of ground-based observations? Because solar resource varies from year to year.

4% above long term mean

7% below long term mean

Lots of uncertainty, if you only have one year of observations.

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Satellite/NWP and Ground Stations Combined Cons •  Algorithm for correcting

the satellite record to the ground observations must have skill but not over fit

•  Corrections will only be as accurate as the ground station data

Pros •  Ground station

observations can be used to improve the accuracy of the satellite/NWP data

•  Puts the short-term observations into the context of over a decade of satellite data or longer NWP

+

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How Does 3TIER Combine Ground Observations and Satellite/NWP Data?

13+ years of hourly (tuned) irradiance data matched with

weather variables:

wind speed

temperature relative humidity

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Solar Record Extension Annual GHI

Ground Observations 3TIER Satellite Irradiance

Ø  1-year of observations with 10+ years of satellite based irradiance data and NWP estimates

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Solar Record Extension Annual GHI


MOSghi= ax1+ax2+ax3+…

Where, as an example, x1 = Sat Derived GHI, x2 = NWP derived GHI, x3 = MODIS AOD, X4 = NWP incoming longwave radiation, etc

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Satellite Data plus Ground Observations

Length of Observations

Training Yr Uncertainty

Blind Yr Uncertainty

0 Month 9.0 9.0 3 Months 7.01 7.86 6 Months 4.83 6.29 9 Months 2.61 4.23

12 Months 0.58 2.43

Desert Rock, USA

From 9% to 2.4% uncertainty.

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Uncertainty Value

P50 P75 P90 P95

0 Months 9 2613 2433 2270 2173 3 Months 8 2603 2441 2295 2207 6 Months 6 2712 2567 2436 2358 9 Months 4 2790 2677 2576 2516

12 Months 2 2728 2649 2577 2535

P-values for Desert Rock based on the Blind Year uncertainty values

P50 goes up as more observational data is added, and P95 steadily increases!


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Uncertainty Value

P50 P75 P90 P95

0 Months 9 2477 2320 2179 2095

3 Months 7 2509 2378 2260 2189

6 Months 6 2423 2316 2220 2162

9 Months 4 2366 2285 2212 2168

12 Months 3 2351 2289 2233 2199

P-values for Africa based on the Blind Year uncertainty values

P50 decreases by 5% by including 12 months of observations but P95 goes up by 5%


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When is a project bankable?

Resource assessment for financing utility scale projects solar projects

»  The most confident resource estimates depend on high-quality ground observations combined with context from long-term references (satellite and NWP).

»  Early stage assessments can be done at low cost but with relatively high uncertainty.

»  Task is to reduce uncertainty throughout the development process at minimum cost.

© 3TIER, Inc.

Time Series APIs

GIS Data Layers

Solar Prospecting Tools

Project Design Services

Site Climate Variability Analysis (CVA)

Time series and TMY

3TIER Solar Products

Prospecting Where is the best place to build a solar project? Is the solar resource available when it is needed?

• Typical Meteorological Year Irradiance Data

• Mean irradiance – monthly annual

Assessment What is the expected generation of my solar project? What is my 1-year P90 value?

• On-site surface irradiance observations (@1-year)

• Long term time series of irradiance values and met variable at site

Operations What will my estimated production values be in the next hour/day?

• Forecasted irradiance values

• Reconciliation

Resource Performance Reconciliation Day-Ahead Forecasting

BEFORE SITE-SPECIFIC OBSERVATIONS

AFTER SITE-SPECIFIC OBSERVATIONS

POST PROJECT CONSTRUCTION

Project Generation Estimate (PGE)

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Satellite and Ground Stations Combined

These observations include the lowest summer on record; without long-term reference data for context the statistics for this site will be artificially low.

3TIER Solar Products: CVA (IRRADIANCE)

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3TIER Solar Products: PGE “ENERGY” Energy Production Calculations Loss & Uncertainty Estimates Probability of Exceedence Histogram of Annual Energy 12x24 P50 energy production

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Questions? Please type any questions into the “Questions” field in your webinar control panel. All questions will be answered in writing after the webinar is over.

Or Contact Our Local Offices Hugo Pereira, Managing Director for Latin America at 3TIER

[email protected] Rodrigo Stuart, Diretor Comercial at Three Energy

[email protected]

solar resource assessment from prospecting to … · solar resource assessment from prospecting to...

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