importance of data driven decision making in enterprise energy management | dr. satish kumar

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Technical Session # 3B Topic : Importance of Data Driven Decision Making in Enterprise Energy Management Topic: Importance of Data Driven Decision Making in Enterprise Energy Management By: Dr. Satish Kumar

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Global HSE Conference | Sept 26 - 27 2013 | New Delhi, India

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Page 1: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Topic: Importance of Data Driven Decision Making in Enterprise Energy Management

By: Dr. Satish Kumar

Page 2: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Outline

1 Indian Context

2 Building Sector – Energy Benchmarking

4 Conclusions

3 ISO 50001

Page 3: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Sustainable Growth Conundrum - ITotal Floor Space (Billion m2) Includes Commercial and Residential

8

41

Vehicle Fleet (Millions)Includes 2 and 3 wheelers,Passenger Vehicles, Buses and Trucks

51

377

Total Power Demand (Terawatt hours) Includes both Utilities and Captive

700

3870

Cement Demand (Million tonnes)

127

860

X 5 X 7

X 5 X 7Source: McKinsey’s India Urban Awakening, 2010

Page 4: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

147; 0.5%

368; 1.3%

804; 2.7%

889; 3%

1,068; 3.6%

1,151; 3.9%

1,427; 4.9%

1,593; 5.4%

5,595; 19%

6,550; 22%

29,381

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000

UAE

France

Germany

Africa

Latin America

Japan

India

Russian …

USA

China

World

Million Tonnes of CO2

India could become the SECOND largest emitter of GHG emissions in the

world at a per capita emission of 5 tonnes of

CO2

Source: CO2 Emissions from Fuel Combustion - IEA (2010)

Sustainable Growth Conundrum - II

Page 5: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

No. of People Without Access to Power and Relying on Biomass (million)

Countries/Region# of People Lacking Access to Electricity

# of People Using Biomass for Cooking

Africa 587 657

Sub- Saharan Africa 585 653

Developing Asia 799 1,937

China 8 423

India 404 855

Other Asia 387 659

Latin America 31 85

Developing Countries* 1,438 2,679

World** 1,441 2,679

Note: *Includes Middle East Countries, ** Includes OECD and Transition Economies

Source: Energy Poverty, International Energy Agency (2010)

Page 6: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Access to Electricity: A Social Imperative

Images: www.aiche.org

Page 7: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

July 2012 Blackouts

● Largest power outage in world history

● Affected 620 million people

● Half of our population

● 9% of world population

● 22 states

● 32 GW (a sixth of nationwide generation capacity) taken offlineSources: mapsofworld.com, Wikipedia

Page 8: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Electricity Consumption (in Million kWh)

21.7% 21.4% 19.1%

100%

Others

Industrial

Agriculture

Commercial

Domestic

2020-21E

1,493,457

8.1%

35.3%

11.4%

26.1%

2010-11

648,802

9.2%

34.7%

10.0%

24.8%

2006-07

455,749

7.5%

37.6%

8.8%

24.4%

9.2 % 8.7%

x %

Electricity consumption CAGR

Note: Others include Railways, Public water pumping & lighting and bulk supply

Source: Central Statistics Organization (for 2007 fig)

18th Electric Power Survey draft report, CEA, July 2011

Page 9: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

End Use Sector Energy Use (IEA)

Source: IEA 2009

Page 10: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Planned vs. Achieved Generation

Source: Power Sector in India (KPMG 2011)

Page 11: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

The Energy Dilemma

Energy demand in India by 2030

The requirement The availability Energy is scarce, expensive,

unclean

State Electricity Tariff Increase

Rate Effective From

Punjab ~ 13 % 1 April 2013

Kerala 7% 1 May 2013

AP ~ 23% 1 April 2013

Haryana 13% 1 April 2013

Karnataka 25 Paise 1 May 2013

Peak Shortage Energy Shortage

Page 12: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Energy Efficiency is a No Brainer

Primary Fuel

100 units 33 units 24 units

1 unit saved at end user

4.2 units saved at the power plant

Power plantEfficiency = 33%

T&D loss = 27%

Source: Central Electricity Authority (2009)

T & D Losses also include electricity losses unaccounted for

Page 13: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Outline

1 Indian Context

2 Building Sector – Energy Benchmarking

4 Conclusions

3 ISO 50001

Page 14: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Commercial Buildings Growth Forecast

• Currently, ~ 659 million m2 (USAID ECO-III Internal Estimate Using MOSPI, CEA and Benchmarked Energy Use data)

• In 2030,~ 1,900 million m2 (estimated)*– 66% building stock is yet to be constructed

Year: 2010

659 M m2

Year: 2030

* Assuming 5-6% Annual Growth

Current 34%

Yet to be built 66%

SOURCE: USAID ECO- III Project

Page 15: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Commercial Electricity Use Growth

Growth of Electricity Consumption in Commercial Sector in India (2003-08)

SOURCE: Central Electricity Authority. 2009. General Review 2009

2003-04 2004-05 2005-06 2006-07 2007-080

10000

20000

30000

40000

50000

2820131381

3596540220

46685

11.314.6

11.816.1

Growth in % over the previous year

GW

h

Page 16: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Rate of Growth of Energy Use

2015 2020 2025 20300%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

New Buildings Existing Buildings

Page 17: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Scope for Massive improvement

BE LEAN - Halve the demandReview standards, reduce losses, avoid waste.

timesBE MEAN - Double the efficiency

Buy efficient equipment, use it efficiently,avoid system losses, tune it all up.

timesBE GREEN - Halve the carbon in the supplies

With on-and off-site measuresequals

You’re down to one-eighth of the CO2

BUT YOU NEED TO TAKE ALL THE STEPS!

Page 18: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Reporting and Benchmarking at Two Levels

ENERGY IMPORTED TO THE SITE (and associated emissions)• The fuel and energy commodities the building has to buy in.• Complies with national policy drivers.• Gives the headline CO2 indicator in EPCs and DECs.

BUILDING ENERGY USE (BEU), with onsite renewables added• To gauge the building’s efficiency, whatever the supply mix.• To maintain comparability with existing benchmarks.• To charge on to occupiers.• So poor buildings can’t hide under low-carbon supplies.

The two are identical where there are no onsite renewables

Page 19: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Reporting and Benchmarkingit used to be relatively simple …

1. Define the boundary of the premises.2. Collect annual energy use data by fuel.3. Identify the building type and floor area (confirm area units).4. Multiply each fuel use by the appropriate CO2 factor.5. Calculate performance indicators:

• Electricity - kWh/m2 per annum.• Fossil fuels - kWh/m2 per annum.• Carbon dioxide - kg CO2/m2 per annum.

6. Adjust if necessary, e.g. for weather and occupancy.7. Review against appropriate reference data, e.g.

• Published benchmarks, e.g. consumption guides.• Performance in previous years.• Peer review versus comparable buildings.• Savings targets.

Page 20: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Top-Down Entry Level1. DEFINE THE PREMISES AND ENERGY-RELATED BOUNDARIES• Ideally combining metering availability with management responsibility.• Confirm if for landlord’s services, tenant’s direct supplies only, or the lot?2. COLLECT BASIC DATA• Building type, e.g. office. Start with CLG classification for DECs?• Measure of extent, usually the floor area. Gross, nett and treated …• Annual electricity imported across the boundary, kWh.• Annual imports of other fuels, reported in kWh gross calorific value by fuel.3. CALCULATE PERFORMANCE INDICATORS (and not just for carbon)• kWh/m2 of electricity.• kWh/m2 of combustion fuel and heat (ideally with heat weighted).• kg/m2 of CO2 at published factors (but other factors may also be needed)

Also recommended– kWh/m2 of weighted energy (an indication of overall energy performance)

Proposed weightings 1 for fuel, 1.25 for heat, 4.2 for electricity.

Page 21: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Reporting and Benchmarking

Can we interpret the results fairly?

Page 22: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Benchmarking Data for Buildings

Mean for different commercial buildings (Source: Building Energy Benchmarking study undertaken by the USAID ECO-III Project)

Offices Area (m2)# Annual

Hours kWh kWh/m2/year kWh/m2/hr

Office (All) 17,100 4,570 3,457,000 242 0060

Public sector 12,800 2,420 1,380,000 109 0048

Private sector 18,600 5,350 4,202,000 290 0064

One shift 21,600 2,120 2,389,000 158 0075

Two shift 8,800 4,290 2,064,000 243 0058

Three shift 23,900 8,120 6,929,000 348 0044

Conditioned >=50% 14,600 4,820 3,615,000 269 0065

Conditioned <50% 28,600 3,420 2,727,000 83 0037

Hospitals Area (m2) # Beds kWh kWh/m2/year kWh/bed/year

Multi specialty hospitals 8,200 170 2,398,000 362 13,998

Hotels Area (m2) # Rooms kWh kWh/m2/year kWh/room/year

1-3 star Hotels 9,300 100 2,347,000 271 19,396

4-5 star Hotels 14,300 150 3,513,000 274 20,381

Shopping Malls Area (m2)   kWh kWh/m2/year kWh/m2/hr

Shopping Malls 10,700   2,370,000 252 0056

Source: USAID ECO III Project

Page 23: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

India Whole Building Data

Whole Building Energy Use Metrics

Whole Building Metric Units Standard Better Best

Annual Energy Use kWh/m2.a 250 150 60

Peak Energy Use W/m2 90 40 20

Annual EnergyUse/Occupant kWh/a/person 2250 1350 585

Source: LBNL Best Practices Guide for High PerformanceIndian Office Buildings 2012

Page 24: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Performance Rating Tool for Hotels

User Input

Relative Ranking Based on Database of Indian Hotels

Relative Percentage

Page 25: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Outline

1 Context

2 Present Status

4 Conclusions

3 ISO 50001

Page 26: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

ISO 50001 in Perspective

International Management Standards

QualityISO 9001

EnvironmentISO 14001

Energy Management

ISO 50001

New

Health & SafetyOHSAS 18001

Page 27: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

ISO 50001 in a Nutshell

Helps establish management systems and processes to improve energy performance, in particular energy efficiency

Applies to all types and sizes of organizations

Defines how to develop and implement an energy policyEstablish objectives, targets and action plans

Introduction 27

Page 28: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

ISO 50001 in a nutshell

Can be used for certification/registration and/or for self-declaration of an organization's Energy Management System

Doesn't determine absolute requirements for energy performance. Commitments will be specified in the organization’s energy policy

Easy integration with other ISO management systems (Quality, Environment, Occupational health and safety)

Introduction 28

Page 29: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Energy Management must

– be initiated by General Management

– have an identified person in charge

– be communicated at all levels

– comprise a detailed Energy policy

– supported by solid measurement

– include a continuous Improvement process

ISO 50001 – Framework

Page 30: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

EnMS- Management Review

Inputs to the management review shall include:Follow-up actions from previous management reviews;Review: Policy and energy performance;Status of corrective and preventive actions and recommendations for

improvementProjected energy performance for the following period

Outputs from the management review shall include:Improvements in the energy performance since the last review;Changes to the energy policy, objectives, targets, etc.;Clear allocation of resources

Introduct30

Page 31: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

• ISO 50001 is an international standard that

ISO 50001: A Business Catalyst

• Governments can promote

• Companies can adopt

• Citizens can advocate for

• Influences 60% Energy Use

Page 32: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

ISO 50001: A Business Catalyst

ISO 50001 brings multiple benefits to organizations

CO2

reduction

Energy Savings

Framework

Compliance

SustainabilityImage

Page 33: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Adoption of ISO 50001 Globally (Top 20 countries by number of sites)

• Europe leads the uptake in ISO 50001 certifications with more than 80% of the total certified sites

• Germany: the market leader for ISO 50001

• Industrial firms have been the earliest adopters of the standard

7 % of the ISO 50001 certified sites in India are Schneider Electric sites

Page 34: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

ISO 50001: Future OutlookExpected level of investment in ISO 50001 by Industry Group in 2013-2014

• Non Industrial firms starting to investigate ISO 50001

• ISO 50001 appeals to firms with existing centralized energy governance structures

• Larger firms (revenues greater than $1 billion) are more likely to invest in ISO 50001.

Page 35: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Making Energy Use and Savings Visible

Establish an Energy Baseline = energy use and energy consumption over a significant period of activity (e.g. 12 months)

Energy performance measured against the Energy Baseline

Identify Energy Performance Indicators (EnPI's) to monitor and measure Energy performance

EnPI’s refer to quantitative targets (e.g. energy use per unit of output)EnPI’s customized for each organization or company

EnPI’s tracking should demonstrate continuous improvement of energy performance across the organization

Define and Implement Energy Measurement Plan, appropriate to the size and complexity of the organization

Introduction 35

Page 36: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

The Toyota Story!● Toyota Motor Manufacturing Kentucky Inc. (TMMK), manufactures 500,000 vehicles

per year—roughly 2,000 vehicles per day in two production shifts per day, five days a week.

● Energy Conservation Measures● Condensed start-up time in Paint Dept.

from 6 hours to 1 hour● Eliminated compressed air blowoff● Used meters for command and control● Changed out process equipment● Changed out facility HVAC, lighting● Troubleshooting● Assigning energy as raw material input

From 1996 until now, the plant reduced energy significantly (in MMBTU/vehicle)

1996 11.32

2001 8.89

2008 5.81

2012 6.28

“It’s truly an enterprise system with a series of controllers and distributed servers to make that efficient, because we’re monitoring 30,000 points every few seconds, and storing 4,000 of those points in a database”, Mark Rucker, Manufacturing, Toyota.

Page 37: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

World’s First building to get ISO 50001 !

A smart building● Equipped with Schneider Electric solutions, including Remote Energy Monitoring● Electric Vehicles charging station with PV solar panel roof● Connected to the building vs. the grid

÷4Final energy consumption

vs. previous sites in thearea

80 kwh/m²/annumFinal energy consumptionROI in 5 to 7 years

Certified•ISO14001•HQE Exploitation•NF EN16001•ISO 50001

Page 38: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

ISO 50001 – Summary• The ISO 50001 international standard on Energy Management

will cover organization processes to improve Energy performance, esp. Energy Efficiency (EE)

• ISO 50001 includes quantitative items to make energy use visible and controllable.– It is based on a detailed Energy policy, including energy baseline,

performance targets & action plans, KPIs• ISO 50001 could be the business catalyst that EE needs

– a standard that governments can promote– companies can adopt– citizens can advocate for

• ISO 50001 means benefits for businesses/organizations interested in cutting energy costs, improved productivity, and better energy management

Page 39: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Outline

1 Context

2 Present Status of the Building Energy Efficiency Sector

4 Conclusions

3 ISO 50001 Framework

Page 40: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Right Steps in the Right Order

1. Start with the need/service in mind, not the amount of “stuff” required to provide it. Check your assumptions.

2. Reduce the loads that cause the need for the service first – using passive means and interactive measures.

3. Select appropriate system types and design for elegance – question rules of thumb.

4. Use efficient equipment (most people start here). Look for the most efficient technology options available.

5. Switch off when not needed (controls) (most of the rest start here).

6. Examine waste streams: for reuse – by other systems/functions. Can waste be reduced?

7. Count all benefits and costs – upstream and downstream, capital and life-cycle. Use the right metrics.

Source: Rocky Mountain Institute

Page 41: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Potential of Building Energy Efficiency?

• Business as Usual Existing Commercial Buildings:

– Energy use intensity – ~250-300 kWh/sq. m.

• Based on benchmarked data for over 1,000 commercial buildings all over India

• Best Practice (Cost-Effective) New Building:

– Energy use intensity – ~70-80 kWh/sq. m.

• Actual numbers from a best practice ITES building

Page 42: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Tragedy of a Pilot Project• Top management will pay the same attention to all projects• Integrated Building Design is a wonderful concept that will

work swimmingly well in all projects• Companies will invest (in terms of people and time) the same

level of effort in all projects• The A-team of designers, consultants, engineers, and site

people will also work on typical projects• Lessons learned are portable and replicable• No extra cost is incurred in ensuring the success of the pilot

project• Pilot projects set the benchmark for performance which can

easily be matched by typical projects

Page 43: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Importance of Plumbing and Philosophy

The society which scorns excellence in plumbing as a humble activity and tolerates shoddiness in philosophy because it is an exalted activity will have neither good plumbing nor good philosophy: neither its pipes nor its theories will hold water

- John W. Gardner

Page 44: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Impacts of Climate Change

Source: http://www.guardian.co.uk/environment/2010/oct/21/climate-change-superpowers, accessed 2012-09-06

Page 45: Importance of Data Driven Decision Making in Enterprise Energy Management | Dr. Satish Kumar

Technical Session # 3BTopic : Importance of Data Driven Decision Making in Enterprise Energy Management

Impacts of Climate Change

Source: UCL Lancet Climate Change Health Impacts Study 2009Disclaimer: Territorial boundaries are indicative, not precise