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Current Ideal

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Optimized Building + Optimized Infrastructure + Optimized Policy

≠ Optimized System

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Jaccard, et al. (1997); Nordhaus (1973); Engel-Yan, et al. (2005)

Incr

easin

g Im

pact

on

Ener

gyCommuni

tyPlanning and SUS

HVAC, Motors,

Vehicles, Appliances

Transit Mode,Industrial Processes,

Building and Site DesignDensity,

Mix of Uses,Energy Infrastructure,

Transportation Network

Where we Focus

Most

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How do energy efficiency, life cycle cost, and carbon emissions of a community

development change when energy infrastructure and urban planning are balanced simultaneously early in the

development process?

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Multiple buildings

and power sources

Energy supply and

demand

Multiobjective

Optimization

Hourly

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Best, et al. (2015)

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Best, et al. (2015)

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Boundary of the Development Ju

ne 1

, 201

6

ExternalGrid

Power Station

Residential

CommercialEnergy Flow

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Create Mesh for Site Area to Describe All

Feasible Building Locations

Preprocessing

Key:

Find Minimum “Cost”

Pipe/Wire Spanning Tree

Calculate Change in Building

Performance from Temperature,

Pressure in Line

Calculate Efficiency,

Cost, Social Parameters

Choose Type of Building

that Exists at Each Node

Calculate “Cost” of Connections (Values on Arcs) Using Composite

Capital and Operating Cost

Genetic Algorithm

MILP Postprocessing

Report Best Solutions

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Initialize •Choose individuals (decision variables) in starting population

Evaluate •Analyze energy, cost, carbon performance of individuals

Select •Keep top performing 50% of individuals

Crossover •“Mate” top performers to create new population

Mutate •Randomly alter some individuals to introduce new variations

Stop •Repeat for designated number of steps

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Best, et al. (2015)

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Decision Variables: Case Studies

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Building TypesLarge Office Primary SchoolMedium Office Secondary SchoolSmall Office HospitalWarehouse Outpatient Health

CareStand-alone Retail Small HotelStrip Mall Large HotelQuick Service Restaurant

High Rise Condo

Full Service Restaurant

Midrise Apartment

Supermarket TownhouseMixed Use: Condo/Retail

Single Family Residence

Mixed Use: Office/Retail

Engine Type Fuel Source

Number Included

Gas Turbine Natural Gas

5

Microturbine Natural Gas

3

Reciprocating Engine

Natural Gas

5

Steam Turbine

Natural Gas

3

Fuel Cell Hydrogen 6Stoker Boiler/Turbine

Biomass 3

Fluidized Bed/Turbine

Biomass 3

Gasifier/Turbine

Biomass 4

Chiller Type

Energy Input Source

COP Range

Centrifugal Electricity 5.58-9.16Absorption Heat 0.71-0.83

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Fuel Efficiency for Downtown Oakland

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RunTotal Fuel

Cycle Efficiency

Hourly Standard Deviation

Maximum Efficiency from Simulation

55.67% 6.39%

Minimum Efficiency from Simulation

37.16% 6.04%

Oakland City Baseline 45.43% 9.44%Oakland CBD Baseline 43.76% 8.77%

Best, et al. (2014)

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Hunter’s Point Case Study

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Highest efficiencies do not exactly match zero carbon scenarios

Carbon and cost experience tradeoff (biomass cost)

Low cost and high efficiency is possible but tradeoff exists

Best, et al. (2015)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80

20000000400000006000000080000000

100000000120000000140000000160000000180000000

Life Cycle Cost vs. Efficiency

Efficiency

LCC

(USD

)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80

50001000015000200002500030000350004000045000

Annual Carbon Emissions vs. Efficiency

Efficiency

Carb

on E

miss

ions

(T

ons/Y

r)0 50000000 100000000 150000000 200000000

05000

1000015000200002500030000350004000045000

Annual Carbon Emissions vs. Life Cycle Cost

LCC (USD)

Carb

on E

miss

ions

(T

ons/Y

r)

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Best, et al. (2015)

CHP type is strong determinant of efficiency, but high efficiency exists across fuel and engine types

Absorption chillers have the highest efficiency due to use of excess heat

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For results with only greater than 60% efficiency.

Any amount of residential can contribute to high efficiency

Best, et al. (2015)

Lower office and commercial correlate with higher efficiency

Industrial GFA over 70% and educational GFA over 50% of the total were not found to produce high efficiency solutions

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Beyond Energy…

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Fleeter, Mena, Mori, Morrice, Sonta, Lepech, and Best (2015 White Paper)

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Calculate Number of Buildings

Calculate Maximum Useful Heat for Treatment

Calculate Treated Water Requirement

Calculate Building Heat Requirement

Calculate Available Heat for Treatment

Allocate Heat Possible in Each Hour

Calculate Water Treatment Efficiency

Calculate CHP Efficiency

Calculate Building Electricity Requirement

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Images from NREL, Twitter

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Community Social

Sustainability

SafetyAccess

(Freedom)

Community

Built Environment

Aesthetics

Recreation/ Health

Nuisances

June

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016Emergency

Response

Light Pollution

Open Space/Parks

Greenery and Views

Density and Use

Walkability

Community Centers