DNV GL © SAFER, SMARTER, GREENER DNV GL ©

Energy Efficiency and its Transformative Power

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DNV GL - Energy, Dubai office

Riyadh, KSA – Tuesday 8th December 2015

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Energy industry drivers: the Energy Trilemma & technology

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Affordability

Reliability Sustainability

The past

Refo

rmin

g

The future

Gas

The past

Electricity

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Ongoing Climate Negotiations in Paris

The Kingdom of Saudi Arabia has submitted its Intended Nationally Determined

Contribution (INDC) to the United Nations, seeking to achieve GHG emission

reductions of up to 130 millions tCO2eq by 2030 annually through economic

diversification and adaptation.

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Japan

USA

1 2 3

UK 0.8

2

0.9

KSA

Industrial Energy Intensity

Steel

1.4

Industrial energy Intensity per GDP level

(UN, 2014)

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Buildings & Appliances

ENVELOPE HVAC LIGHTING

(SEEC, 2013)

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Energy Efficiency: energy use per capita (toe/y)

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(BP, 2014)

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Energy Efficiency: an investment- not a cost

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(Chatham House, 2012)

Models predict KSA becoming a net oil importer in 25 years

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Mandatory Energy Efficiency Program Framework

Sub-sectors of Energy

Efficiency savings goals

Initiatives to achieve

Energy Efficiency

savings goals

Enablers to

implement initiatives

Mandatory EE savings goals

Sectors

Buildings Transport Industry

New buildings

Existing buildings

New plants

Existing

plants

New

fleet

Existing

fleet

Initiatives Initiatives Initiatives Initiatives Initiatives

EE savings goals

Regulations (specific to initiatives)

ESCO’s (Energy Service Companies)

Funding

Governance

Awareness

(SEEC, 2013)

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Energy Efficiency: business as usual vs. improved efficiency

KSA domestic energy consumption

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(Chatham House, 2012)

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Machine Learning is building computer

programs that automatically improve with

experience.

Tom Mitchell

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There are multiple applications for ML – e.g. in Energy

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Detect

Forecast

Control

Optimize

Manage

Scheduling

Flexibility

Offers

Forecast

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Italian Utility benefits from savings

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USD 600 Million

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SAFER, SMARTER, GREENER

www.dnvgl.com

Thank you

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