L’Atlas Mondial des Energies Renouvelables Application a la Mauritanie

Dr. Nicolas Fichaux, IRENA

Bridge the gap between nations having access to the necessary funding, technologies, and expertise to evaluate their national potentials, and those deprived of those elements.

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Bridge the gap between nations having access to the necessary funding, technologies, and expertise to evaluate their national potentials, and those deprived of those elements.

Access to data and methods Building capacities on strategic planning Mobilizing technical assistance

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Albania, Australia, Austria, Belgium, Colombia, Denmark, Egypt, Ethiopia, Fiji island, France, Gambia, Germany, Greece, Grenada, Honduras, India, Iraq, Iran, Israel, Italy, Kazakhstan, Kenya, Kiribati, Kuwait, Lithuania, Luxembourg, Maldives, Mali, Mauritania, Mauritius, Mexico, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Peru, Philippines, Poland, Portugal, Qatar, Saudi Arabia, Senegal, Seychelles, South Africa, Spain, Sudan, Swaziland, Switzerland, Tonga, Tunisia, Turkey, UAE, Uganda, UK, United Republic of Tanzania, Uruguay, USA, Vanuatu, Yemen, Zimbabwe.

Global Atlas

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What share of my energy mix can be supplied by renewable energy?

Where are the resources located?

What is the most cost-effective combination of technologies?

What amount of investments does it represent? How many jobs ?

Is there a large enough market for sustaining a supply chain?

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Conceptual diagram of Renewable Energy Potentials (from NREL, 2012)

How competitive is it?

How much can it cost?

Where can it be harvested? How much power?

Where is the resource?

Complexity StandardsPrivate sector

interest Risks

• COUNTRY-DRIVEN• LONG TERM PLANNING PROCESS • COMMITMENT REQUIRED

Winds in Africa. Mesoscale 5km basemap from 3TIER. Average annual wind speeds at 80 m high.

The values can not be used without validation, but the wind patterns appear clearly, and are consistent with other mesoscale sources. The boxes attempt to highlight areas with possibly strong annual average wind speeds.

This rough approximation does not exclude the possibility of good wind sites outside the red squares, due to local effects not captured by the mesoscale model.

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Data bankability

Investor’sinterest

PUBLICSECTOR EFFORT

Local measurementsPRIVATE

SECTOR EFFORT

Existing local measurements

Data quality

Zoning

NOT ‘BANKABLE’

‘BANKABLE’

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Global Atlas in numbers • 1 interface to access 1,100 datasets on 11 Geoservers • 67 countries, of which 47 contributed to the project

• 100,000 sessions since Jan. 2013• 1,000 registered users created 1,600 maps stored in the

system

• 150 daily visitors with peaks of 1,000+ visitors • 2-days training module for 35 policy makers in 25 countries

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Some datasets of the Global Atlas

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Global Atlas 2.0

Global Atlas is an Integrated Global Spatial Data Infrastructure

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Global Atlas analysis

ApplicationCarte de Mauritanie:

http://irena.masdar.ac.ae/?map=1693

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Solar

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Solar time series - Nouakchott

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PV installation simulation - Nouakchott

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Wind

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Winds > 7 m/s, population, grids, roads

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Wind rose and frequency

Oct 2015 – Global Wind Atlas - DTU

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Oct 2015 – Global Wind Atlas - DTU

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Blackberry World, Windows Mobile, Google Play, soon on iOS

www.irena.org/GlobalAtlas

Potentials@irena.org

Calculation scheme for wind energy yield using wind speed distributions and power curves

Ei = Annual energy yield of wind class [Wh,

watthours], i = 1, 2, 3 …n ti = duration of wind speeds at wind class [h/a,

hours/year] Pi(vi) = Power of wind class vi of wind turbine

power curve [Watt] vi = wind class [m/s] PN = Nominal power of WEC [kW] at nominal

wind class vi [m/s]

hi = relative wind class frequency in %

Source: J.liersch; KeyWindEnergy, 200925

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Calculation scheme for annual energy production

Ei = Pi(vi) * ti

E = E1 + E2 +…+ En

E = Energy yield over one year

J.lie

rsch

; Key

Win

dEne

rgy,

200

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Shape of different wind speed distributions• Weibull distribution:

shape factor k=1,25 and A= 8 m/s

• Weibull distribution: shape factor k=3 and A= 8 m/s

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Sample power curves of wind turbines(82 m rotor diameter, 2 and 3 MW)

Sou

rce:

Ene

rcon

pro

duct

info

rmat

ion

2014

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