Big Data, Small Places:

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Big Data, Small Places:

How Smart Data Collection Can Shape

EcoDistricts

Marshall Duer-Balkind

Energy Administration

District Department of the Environment Government of the District of Columbia

September 25, 2014 Washington, DC

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Agenda

Marshall Duer-‐Balkind

Program Manager, Energy Benchmarking District Department of the Environment

Helen Gurfel

Execu;ve Director

ULI Greenprint Center for Building Performance

Sean C. Luther

PiCsburgh 2030 Districts Senior Director Green Building Alliance

Constan:ne E. Kontokosta, PhD, PE

Associate Professor and Deputy Director

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District Department of

the Environment

•

Leading authority on energy and environmental issues

affecting the District of Columbia.

•

DDOE is leading implementation of the Sustainable DC

 

“In just one generation—20 years—the District of Columbia will

be the healthiest, greenest, and most livable city in the United

States.”

•

First-in-nation Energy Benchmarking program

•

DC is home to three EcoDistrict Pilot Cities projects

 

DowntownDC EcoDistirct

 

SW Ecodistrict

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Big Data, Small Places

We live in a world of increasing quan;;es of data—Big Data.

Data collec;on, analysis, and repor;ng are essen;al to

EcoDistricts from incep;on through full implementa;on.

However, poor quality data can be just as bad as no data at

all.

Yet comprehensive data collec;on can be challenging.

This panel will discuss best prac;ces in data collec;on, and

analysis and reports to date from DC, PiCsburgh, and NYC.

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Data Collection

Methods

Voluntary reporting through sharing of data, either ongoing or through surveys •  Pittsburgh •  DC

1

2

3

VOLUNTARY REPORTING

MANDATORY REPORTING

DIRECT UPLOAD

4

DIRECT METERING

Synergies with mandatory city or state benchmarking policies

•  DC

•  NYC

Direct, authorized upload of utility data

•  DC

Install of advanced meters to track data points in at short-interval or in real-time

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Data Quality

Leverage Points

Upstream

•  Community

Outreach

•  Technical

Assistance

In-‐Stream

•  U;lity

Partnerships

•  Third-‐Party

Veriﬁca;on

•  Tool

Op;miza;on

Downstream

• Sta;s;cal Cleaning

& Analysis

• Itera;ve

improvement

• Enforcement

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Data Privacy

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Purposes of Benchmarking

Help Owners and Managers understand their

energy use and compare to peers

Help policymakers with analysis, planning

program design

Drive Market Transformation

1

2

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DC Mandatory Reporting

•

Clean and Affordable Energy Act of 2008:

 

ENERGY STAR® Portfolio Manager®

benchmarking & public reporting

 

DC Government Buildings >10,000 sq. ft.

 

Private Buildings >50,000 sq. ft

•

District Government and Downtown DC

EcoDistrict are partners in the U.S. DOE

Better Buildings Challenge

•

Benchmarking Data is one of the methods

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Direct Upload

•

Problem: Owners can’t access tenant data

•

Problem: Manual data entry errors

•

Best Solution: Aggregated whole-building

consumption data, with direct automated

upload to Portfolio Manager

 

Mandated in the Sustainable DC Act of 2014

 

Pepco: Available Now

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Presenters

1

2

3

Helen Gurfel

Execu;ve Director

ULI Greenprint Center for Building Performance

Sean C. Luther

PiCsburgh 2030 Districts Senior Director

Green Building Alliance

Constan:ne E. Kontokosta, PhD, PE

Associate Professor and Deputy Director

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2030 Districts:

Goal Oriented ▪ Data Driven

Sean C. Luther, LEED AP ND ▪ @tooluther

Green Building Alliance ▪ @go_gba

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 

G

OAL

O

RIENTED

/I

NSPIRED

BY

THE

2030 C

HALLENGE

 

G

REENHOUSE

G

AS

R

EDUCTIONS

 

E

NERGY

, W

ATER

, T

RANSPORTATION

E

MISSION

G

OALS

 

P

LACE

BASED

(

DEFINED

GEOGRAPHY

)

 

G

RASS

R

OOTS

& P

RIVATE

S

ECTOR

L

EAD

 

L

OCALLY

RUN

(

NATIONALLY

COLLABORATIVE

)

 

N

OT

AN

E

CO

D

ISTRICT

?

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4

= Energy Consumption = Water Consumption & Transportation Emissions

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661 Buildings

174 Property Members

96 Professional Stakeholders 64 Community Stakeholders

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Oakland (est. 2014)

Downtown (est. 2012)

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P

ROPERTY

C

OMMITMENTS

:

Downtown

34,671,637 S.F.

60%

Oakland

24,593,609 S.F.

Total

:

59,265,246 S.F.

81%

67%

116

25%

244

63%

360

43%

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‹#›

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‹#›

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‹#›

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Energy Star Score (1-100) 2013 Score: 83 2013 Progress Report Example Building XXX Street, Pittsburgh, PA 15222 Portfolio Manager Property ID: Primarily: Office

Year Built:

Performance against baseline: -32.4%

67.3 EUI 99.4 EUI -32.4% -10% -20% -35% -50% 0 20 40 60 80 100 120 CBECS 2003 Baseline 2013 2015 2020 2025 2030 EUI ( kB tu /s q f t)

Example Building: Pittsburgh 2030 District Energy Report

2013 Site EUI 2030 District Goals CBECS 2003 Baseline

•  The above graph represents Example Building’s 2013 energy performance compared to the Pittsburgh 2030 District goals, a -10% reduction by 2015 being the first incremental step. •  A baseline of 99.4 EUI (kBtu/sq ft/yr) was established which represents a national average of

buildings similar in sq ft and function.

•  Example Building demonstrated a site EUI of 67.3, a reduction of -32.4% from the baseline. •  Example Building has reached the 2015 energy goal.

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A B C D -32.4% F G H I J K L M N O P Q R S T U V W X -60% -50% -40% -30% -20% -10% 0% 10% 20% 30%

Pittsburgh 2030 District Energy Report:

Offices Properties> 200,000 sq ft

Office Site EUI vs. 2030 District Goals 2015 Goal 2030 Goal

•  The above graph represents Example Building’s 2013 energy performance compared to Reporting Pittsburgh 2030 District office buildings greater than 200,000 sq ft.

•  24 reporting office buildings greater than 200,000 sq ft make up our largest cohort in the district. •  2013 energy performance is -32.4% below the baseline (labeled in solid orange).

Example Building

XXX Street, Pittsburgh, PA 15222 Portfolio Manager Property ID: Primarily: Office

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Example Building

XXX Street, Pittsburgh, PA 15222 Portfolio Manager Property ID: Primarily: Office A B C D E +1.2% G H I J K L M N O P Q R -‐100% -‐50% 0% 50% 100% 150% 200%

Pittsburgh 2030 District Water Report:

Office Properties > 200,000 sq ft

WUI 2015 Goal 2030 Goal

•  The above graph represents Example Buildings 2013 Water performance compared to Reporting Pittsburgh 2030 District office buildings greater than 200,000 sq ft.

•  2013 Water performance is +1.2% above the baseline (labeled in solid Blue).

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 

B

UILDING

P

ERFORMANCE

C

ONFIDENTIALITY

 

M

ANDATORY

B

ENCHMARKING

VS

. V

OLUNTARY

D

ISCLOSURE

 

C

ARROT

VS

. S

TICK

 

D

ATA

Q

UALITY

 

U

SER

INPUT

IS

A

WONDERFUL

,

DANGEROUS

THING

 

U

TILITIES

ARE

IMPORTANT

FRIENEMIES

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Sergey Semonov via h.p://theatln.tc/1i7S1Jd

Dr. Constantine E. Kontokosta, PE, AICP, LEED AP, FRICS

Head/Principal Investigator of CUSP Quantified Community Research Lab

Assistant Professor of Urban Informatics

NYU CUSP and NYU Polytechnic School of Engineering Deputy Director for Academics, NYU CUSP

The CUSP Quantified Community

MEASURING, MODELING, and UNDERSTANDING the URBAN ENVIRONMENT

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New York City

as a Living Lab

The Center for Urban Science and Progress

(CUSP) is a unique public-private research center that uses New York City as its laboratory and

classroom to help cities around the world become more productive, livable, equitable, and resilient. CUSP observes, analyzes, and models cities to optimize outcomes, prototype new solutions, formalize new tools and processes, and develop new expertise/experts. These activities will make CUSP the world’s leading authority in the emerging field of “Urban Informatics.”

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The CUSP Partnership

National Laboratories •  Brookhaven •  Lawrence Livermore •  Los Alamos •  Sandia Industrial Partners •  IBM •  Microsoft •  Xerox

•  Cisco, Con Edison, Lutron, National Grid, Siemens •  AECOM, Arup, IDEO

University Partners

•  NYU (multiple schools)

•  The City University of New York •  Carnegie Mellon University •  University of Toronto (Canada) •  The University of Warwick (UK)

•  IIT-Bombay (India) _{City & State Agency Partners} •  The City of New York

•  Metropolitan Transportation Authority •  Port Authority of NY & NJ

  Buildings

  City Planning

  Citywide Administrative Services

  Design and Construction

  Economic Development

  Environmental Protection

  Finance

  Fire Department

  Health and Mental Hygiene

  Information Technology and Telecommunications

  Parks and Recreation

  Police Department

  Sanitation

  Transportation

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- Jane Jacobs, Death and Life of

Great American Cities, 1961

CITIES ARE AN IMMENSE LABORATORY OF

TRIAL AND ERROR, FAILURE AND SUCCESS,

IN CITY BUILDING AND CITY DESIGN. THIS IS THE

LABORATORY IN WHICH CITY PLANNING SHOULD HAVE

BEEN LEARNING AND FORMING AND TESTING ITS

THEORIES. INSTEAD THE PRACTITIONERS AND TEACHERS

OF THIS DISCIPLINE (IF SUCH IT CAN BE CALLED) HAVE

IGNORED THE STUDY OF SUCCESS AND

FAILURE IN REAL LIFE….

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The CUSP “Quantified Community” (QC) will be a fully instrumented urban neighborhood that uses an integrated, expandable sensor

network and citizen engagement to support the

measurement, integration, and analysis of neighborhood conditions.

Through an informatics overlay, data on

physical and environmental conditions and use patterns will be processed in real-time to

maximize operational efficiencies, improve quality of life for residents and visitors, and drive evidence-based planning.

Kontokosta, et al.

The Quantified Community

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QC Data Sources

Combing fixed instrumentation, mobile devices, and participatory sensing

Novel

Technologies

•  Visible, infrared and

spectral imagery

•  RADAR, LIDAR

•  Gravity and magnetic

•  Seismic, acoustic •  Ionizing radiation, biological, chemical •  … Sensors •  Personal (location, activity, physiological)

•  Fixed in situ sensors

•  Crowd sourcing

(mobile phones, …)

•  Choke points (people,

vehicles) Organic Data Flows

•  Administrative records

(census, permits, …)

•  Transactions (sales,

communications, …)

•  Operational (traffic,

transit, utilities, health system, …)

•  Social media (Twitter,

Facebook, blogs, …)

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Data management, integration

Analytics,

Modeling, and

Simulation

Residents/

visitors/

workers

Operators

Evaluation and Monitoring

IMPACT

System Optimizatio n Behavior Change Economic Models

Information Flows in the QC Environment

Open Data Platform – Publicly Accessible

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TaxiVis: Interactive Visual Exploration of NYC Taxi Records

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Modified Gaussian Dispersion Plume

Graph Theory Applied to Building Emissions and Air Quality Monitoring

Source: Jain, Moura, Kontokosta 2014

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Urban Sleep Pa.erns

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A Day in the Life

of Water Street –

as Seen through

Data

_{R.
Dunks
et
al.}

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cusp.nyu.edu

NYUCUSP

@NYU_CUSP

Thank you

[email protected]

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ecoDistrict Summit

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What is the

ULI

Greenprint

Center?

2



Urban Land Institute

Greenprint

Center for Building

Performance, founded in 2009



Greenprint is a worldwide alliance of

leading real estate

owners and financial institutions

committed to

improving the environmental performance of buildings



Greenprint‘s

mission

is to lead the global real estate

community toward

value-enhancing carbon reduction

strategies



Greenprint is a member driven nonprofit , that is “

by the

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Greenprint Environmental Management Platform

Data analytics • Normalization • Carbon calculation • Online dashboards Improving performance • Benchmarking

properties, funds, & portfolios

• Project tracking

• On-demand reporting • Tracking against goals

Analysis & Benchmarking Environmental Reporting Reporting Variance checks Multi-stakeholder data entry and review process Greenhouse gas protocol calculation methodology ISO 14064 Auditability Data Quality Review Asset Data • Property characteristics • Space & tenant use • Certification/Rating Environmental Data • Energy • Emissions • Water • Waste • Refrigerants Environmental & Asset Data Capture

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By the industry, for the industry City initiatives

Environmental

Management

Platform

Greenprint Program of Work

Best Practices and Case Studies Setting Global Standards Valuation & Portfolio Management Committee Innovation Roundtable

Link financial metrics with environmental metrics

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5

Greenprint Membership

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9/24/2014 6

Greenprint Performance Report™ Volume 5: Office Properties, Cities

SAN FRANCISCO 96 properties 199 annual kWh/m2 (19 annual kWh/ft2₎ WASHINGTON D.C. 134 properties 197 annual kWh/m2 (18 annual kWh/ft2₎ NEW YORK 67 properties 271 annual kWh/m2 (25 annual kWh/ft2 PARIS 13 properties 163 annual kWh/m2 (15 annual kWh/ft2₎ LONDON 251 properties 275 annual kWh/m2 (26 annual kWh/ft2₎ FRANKFURT 11 properties 214 annual kWh/m2 (20 annual kWh/ft2₎ TOKYO 15 properties 125 annual kWh/m2 (12 annual kWh/ft2₎ SYDNEY 2 properties 299 annual kWh/m2 (28 annual kWh/ft2₎

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Metro Washington DC Building Performance Report, Volume 2

The ULI Greenprint Center and DowntownDC are pleased to present the second

Metro Washington, D.C. Building Performance Report

Metro Washington DC area is divided into 3 subcategories:

• DC BID

• Washington DC (the District) • Virginia & Maryland suburbs

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Downtown DC ecoDistrict Members

8

Downtown DC ecoDistrict’s Contributing Members

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9

energy

-1.7%

2013: 2,503 million kBtu

carbon

2013: 321,000 mtCO2e

-3.7%

occupancy

1.4%

2013: 99% electricity

-2.5%

2013: 2,416 million kBtu

-1.7%

2013: $85 million cost of energy

-8.9%

2013: 855 million gallons

water

2013 portfolio includes 171 office and multifamily properties with consistent year over year data

Report Performance Snapshot

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Greenprint Metro

Washington Range Washington Greenprint Median Greenprint U.S. Office Median Number of Properties 157 861 Size of Buildings (SF) 8,901–1,177,173 214,690 196,682 Year Built 1888 - 2012 1988 1987 2013 % Occupancy 0% - 100% 100% 100%

Site Energy Intensity

(kBtu/SF) 6.5 - 220 62 63

Energy Star Score 5 - 97 79 82

Site Carbon Intensity

(kg CO₂e/SF) 0.8 – 24.9 8.2 7.5 Metro Washington Greenprint Office Portfolio

Properties in Metro Washington Office Portfolio

Overview of office properties in the analysis:

All properties were submitted on a voluntary basis by property owners; institutional investors, investment trusts, and private real estate companies

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Metro Washington DC Building Performance

Building environmental performance is impacted by many factors, the report specifically explores space use, age, size, FTEs and occupancy

METRO

WASHINGTON VIRGINIA AND MARYLAND DC DC BID

Number of Properties 157 73 84 36

Site Energy Intensity 62 65 61 59

Site Carbon Intensity

(kg CO2e/SF)

8.2 8.7 7.6 7.5

Total Floor Area (MSF) 39.5 16.3 23.2 11.0

Average Building Age 1988 1989 1985 1991

Property Usage: % Government 20% 35% 11% 10% % General Business Services 41% 13% 58% 55% % Financial 5% 2% 7% 5% % Health Care 2% 1% 3% 3% % Technology 12% 30% 2% 4% % Retail 2% 1% 2% 2% % Other* 18% 18% 18% 21%

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12

Relationship between Energy and Weather

• Heating and cooling account for ~ 40 percent of a building’s energy consumption • Variations in weather can increase or decrease energy consumption by 7 percent

Weather across the globe in 2013 diverged from 30 year average

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Greenprint Metro

Washington Office

Normalization

Weather & FTE normalization enables performance comparisons over time

• In 2013 DC performed 1.4% better than the normalized prediction

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Correlating natural gas use with weather for multifamily properties shows a base load in summer months and heating peaks in winter months which are possibly due to tenant behavior

Greenprint Metro Washington Multifamily Weather Normalization

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Occupancy vs FTE (Energy)

• Energy usage decreased 11.3% from 2009 to 2013

• Energy use intensity by FTE decreased 9.1% from 2009 to 2013

• Absolute energy consumption, energy use per SF, energy use per FTE all

decreased demonstrating increased energy efficiency

50,000 55,000 60,000 65,000 70,000 75,000 80,000 85,000 90,000 95,000 100,000 0 10 20 30 40 50 60 70 80 90 2009 2010 2011 2012 2013 FT Es O ccu pa ncy % Occupancy FTEs 8,081

kWh/FTE kWh/FTE 8,101 kWh/FTE 8,023 kWh/FTE 7,446 kWh/FTE 7,348

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Water Utility Costs

• Cost of water has outpaced CPI by over 200 basis points • Water is now 4.5 times more expensive compared to 1983

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Metro

Washington Water Cost

• Water use for metro Washington decreased by 8.9% from 2012 to 2013 • Average cost per gallon of water increased by 32 percent from $6.74 to

$9.05 per 1,000 gallons

Over the past five years, water cost increased by 55%

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Metro Washington DC Office Building

Performance Report

The ULI Greenprint Center and DowntownDC are pleased

to present the Metro Washington, D.C. Performance Report



The report will be available for download on the

Greenprint website:

www.uli.org/greenprint

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19 Greenprint Metro Washington Range Greenprint Metro Washington Median Greenprint U.S. Multifamily Median Number of Properties 38 524 Size of Buildings (SF) 9,769–1,081,784 308,380 260,586 Year Built 1900-2013 1997 2000 Number of units 96-842 275 234 Common-are Site Energy Intensity (kBtu/SF) 1.3-19.6 6.7 9.1 Whole-building area site energy intensity (kBtu/SF) 12.3- 93.2 48 40 Metro Washington Multifamily Greenprint Portfolio

Multifamily properties capture different subsets of energy data; whole-building/common-area energy

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20

Correlating natural gas use with weather for multifamily properties shows a base load in summer months and heating peaks in winter months which are possibly due to tenant behavior

Greenprint Metro Washington Multifamily Weather Normalization

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What is the ULI Greenprint Center?

Measure, Manage, Enhance Property Value



Greenprint provides an environmental management

platform for members to measure, track and benchmark

property-level

•

Energy consumption

•

Carbon emissions

•

Water usage

•

Waste diversion



Members receive

customized reports

outlining individual

portfolio and fund performance



Greenprint Performance Report

is a consolidated view of

participating properties, detailing environmental

performance by geography and asset class

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Comparing HDD and CDD

22

By comparing 2012 and 2013 heating degree days and cooling degree days with the 30 year average shows that it is becoming warmer through out the year.

www.uli.org/greenprint

Big Data, Small Places: