Driving the Decision, Life-Cycles of EV Transportation

Omer Tatari, Ph.D., LEED AP

Associate Professor and Graduate Program Director

Co-Director of EVTC

Department of Civil, Environmental, and Construction Engineering

University of Central Florida

About Us

Life Cycle Assessment

Life Cycle Cost Analysis

Stochastic Optimization

System Dynamics

Agent-based modeling

Data Analytics

Integrated sustainability assessment

Triple bottom line

Quantitative models

UCF Sustainability Analytics Lab

GHG EmissionsWater footprint

Energy footprint Future projections

Selecting the best decision under uncertainty

Understand the total cost of ownership Externalities Making the most informed decisions

Acknowledgements

• U.S. Department of Transportation

• UCF Sustainability Analytics LabDr. Murat Kucukvar, Dr. Mehdi Noori, Dr. Nuri Onat, Tolga Ercan, Yang Zhao,

Mehdi Alirezaei, Burak Sen, and Carolina Kelly

• Department of Civil, Environmental, and Construction Engineering @ UCF

• UCF Florida Solar Energy Center

Can transportation be sustainable?

Constrained Growth Model Resource Maintenance Model

Improve access

Adverse environmental,

social and economic impacts

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehiclesDelivery trucks

Heavy-duty trucksPublic transportation

and school Buses

Vehicle-to-Home

Application

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehicles

Are EVs always the best choice for the climate?

Life Cycle Analysis

Well to Wheel (WTW)

Well to Tank (WTT)

Tank to Wheel (TTW)

Energy Material

Emission Waste

Process Level

Economy Level

Are EVs always good for the climate?The vehicle technologies considered are ICVs, HEVs, PHEVs, and EVs.

Toyota Corolla (ICV) Toyota Prius (HEV) plug-in Toyota Prius (PHEV-AER18) Chevrolet Volt (PHEV-AER62) Nissan Leaf (EV)

2 scenarios were considered:Scenario 1: State-based average electricity generation mix

Results:

According to Scenario 1, EVs are the least carbon-intensive vehicle option in 24 states corresponding the 38% of the number of registered LDVs in the U.S.

On the other hand, HEVs are found to be the most energy-efficient option in 45 states.

Results for Energy consumption and GWP are the same:

EVs are ranked as the best option in all of the states!!

According to Scenario 3, adoption of EVs can result up to 73% and 55% reduction of GHG emission and energy consumption respectively.

These are the highest reduction rates can be achieved compared to other scenarios.

Scenario 2:100% solar powered charging stations:

A futuristic scenario where there are solar charging stations and roof-top solar panels to charge electric vehicles are common in residential and commercial buildings.

EVs are potentially great to reduce GHG emissions.Electricity mix is critical.

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehicles

Public transportation

and school Buses

Which alternative fuel option is betterfor public transportation buses?

Rapid increase of alternative fuel adoption for public transportation buses

Figure: Alternative fuel adoption for transit buses in the U.S.

Figure: System boundary of life cycle assessment Source: Ercan, T., & Tatari, O. (2015). A hybrid life cycle assessment of public transportation buses with alternative fuel options. The International Journal of Life Cycle Assessment, 20(9), 1213-1231.

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CNG and LNG Diesel Electric and Hybrid Gasoline Biodiesel

Source: American Public Transportation Association (APTA), 2016. 2016 Public transportation Fact Book Appendix A : Historical Tables. Washington DC.

Diesel use decreased almost half in 20 years (95% in 1996 to 50% in 2015).

Electric hybrid increase from “0%” to 17% from 2004 to 2015.

Environmental Life Cycle Assessment (LCA) comparison of six alternative fuel types for transit buses, which includes manufacturing, maintenance, fuel consumption, and refueling infrastructure impacts for three driving cycles.

Emissions increase by shifting from diesel to CNG!

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Diesel Electric Hybrid B20 CNG LNG

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Figure: Fuel types of transit buses with driving cycles

Fuel Supply Manufacturing Maintenance Tailpipe Battery(Li-Ion) Infrastructure

Abbreviations:• MAN: Manhattan cycle [Ave. speed of 6.12 mph, more stop-and-go operation]• CBD: Central Business District cycle [Ave. speed of 12.6 mph, hypothetical

cycle with equally frequent stops]• OCTA: Orange County Transit Administration cycle [Ave. speed of 12.3 mph,

less stops with higher maximum speed]• PV: Photovoltaic (solar) charging station scenarios• LC: Low carbon scenario (200g CO2/kWh)

Source: Ercan, T., & Tatari, O. (2015). A hybrid life cycle assessment of public transportation buses with alternative fuel options. The International Journal of Life Cycle Assessment, 20(9), 1213-1231.

Low average operation speed (more stop-and-go) (MAN cycle) cause higher emissions for CNG&LNG buses!

BE transit bus can reduce emissions even with grid mix average.

This potential can be doubled if solar charging station is used!

Figure: Lifetime CO2 eq. (t CO2-eq) emissions of transit buses

Regional electricity generation mix matters for battery-electric bus operation!

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Figure: Lifetime CO2 eq. (t CO2-eq) emissions of BE transit bus for NERC regionsAbbreviations:* ASCC: Alaska Systems Coordinating Council * FRCC: Florida Reliability Coordinating Council * HICC: Hawaiian Islands Coordinating Council* MRO: Midwest Reliability Organization * NPCC: Northeast Power Coordinating Council * RFC: Reliability First Corporation* SERC: SERC Reliability Corporation * SPP: Southwest Power Pool * TRE: Texas Regional Entity * WECC: Western Electricity Coordinating Council

Source: Ercan, T., & Tatari, O. (2015). A hybrid life cycle assessment of public transportation buses with alternative fuel options. The International Journal of Life Cycle Assessment, 20(9), 1213-1231.

It might not be environmentally feasible for these regions to operate BE bus compared to using other alternative fuels (i.e. hybrid)!

Fleet owner’s expenses (life-cycle cost) vs. Air pollution externality (social cost of emissions)

Transit bus fleet operation: Alternative fuel options for purchases

Air pollution externalities with LCA perspective and Life Cycle Cost (LCC) analysis

Multi-objective linear programming (MOLP) for optimized economic and environmental impacts

Figure: Total Life-Cycle Cost (LCC) analysis results for each driving cycle

Figure: Conventional air pollutant impacts in terms of public health costSource: Ercan, T., Zhao, Y., Tatari, O., & Pazour, J. A. (2015). Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options. Energy, 93, 323-334.

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BE is the least cost feasible option for all driving cycles

SO2 is the most critical emission type for externality calculations.

B20 is sensitive for PM and SO2 emissions, which makes it the least favorable type.

Finding economic and environmental friendly public transportation bus fleet: What is the optimal bus fleet mix?

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Hybrid Electric CNG CO2 emissions [in 1000s t CO2] Health Damage Cost [in $ 100,000] Total Cost [$ millions]

Figure: MOLP results for three driving cycles under different objective weighting scenarios

Source: Ercan, T., Zhao, Y., Tatari, O., & Pazour, J. A. (2015). Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options. Energy, 93, 323-334.

Fleet mixtures consist of hybrid or battery-electric transit buses for equal weights scenario!

Can we generate revenue from electric bus fleets?

V2G Application to Public Transportation and School Buses

The path of making revenue from electric transit bus operation:

Aim of the study is to provide comparison between diesel and BE transit and school buses using V2G. Lifetime cash flow Lifetime air pollution externalities are calculated for five regions of the U.S.

Figure: Transit and school buses’ environmental emissions data collection and analysis pathSource: Ercan, T., Noori, M., Zhao, Y., & Tatari, O. (2016). On the Front Lines of a Sustainable Transportation Fleet: Applications of Vehicle-to-Grid Technology for Transit and School Buses. Energies, 9(4), 230.

V2G benefits for cash flow analysis results

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2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027

(a) Transit

PJM ISO-NE NYISO ERCOT CAISO Diesel-Transit Bus

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(b) School

PJM ISO-NE NYISO ERCOT CAISO Diesel-School Bus

Diesel transit bus is still slightly cost feasible compared to BE transit bus.

Figure: Cumulative cash flow of (a) Transit and (b) School diesel (average) and BE (regional) busesSource: Ercan, T., Noori, M., Zhao, Y., & Tatari, O. (2016). On the Front Lines of a Sustainable Transportation Fleet: Applications of Vehicle-to-Grid Technology for Transit and School Buses. Energies, 9(4), 230.

Diesel school bus becomes the least cost feasible option compare to other BE options.

Diesel school bus reaches higher cash flow values after 4 years of ownership in CAISO and NYISO regions.

Abbreviations:• PJM: Pennsylvania-New Jersey-Maryland interconnection• ISO-NE: Independent System Operators (ISO)-New England region• NYISO: New York Independent System Operators (ISO)• ERCOT: Electric Reliability Council of Texas • CAISO: California Independent System Operators (ISO)

Negative externality of lifetime school bus operation…

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V2G related benefits Air Emission Externalities

Figure : Total air pollution externalities of bus and fuel types

Source: Ercan, T., Noori, M., Zhao, Y., & Tatari, O. (2016). On the Front Lines of a Sustainable Transportation Fleet: Applications of Vehicle-to-Grid Technology for Transit and School Buses. Energies, 9(4), 230.

Eliminating the air pollution externalities by using V2G available BE school bus. So by using it the fleet could give back to the society by providing negative emissions!

V2G systems can neutralize all of the emission impacts of electricity consumption from BE school bus operations.

Air Pollution ExternalityQuantifying the marginal costs of air pollutants (CO, SOx, NOx,PM10, PM2.5, VOC) on human health and environmental damages, with said damages consisting of mortality, morbidity, crop loss, timber loss, etc.

Sustainable transportation fleet is possible!

Figure: Regional average life cycle cost of transit (Tr.) and school (Sch.) buses (graphical abstract)Source: Ercan, T., Noori, M., Zhao, Y., & Tatari, O. (2016). On the Front Lines of a Sustainable Transportation Fleet: Applications of Vehicle-to-Grid Technology for Transit and School Buses. Energies, 9(4), 230.

CAISO

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Regional Average Life-Cycle Cost of Transit (Tr.) and School (Sch.) Buses

With the availability of government incentives and high capacity payments, New York ISO region provides negative life-cycle cost for BE school buses compared to $310,000 cost for diesel school bus in 12 years of lifetime.

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehiclesDelivery trucks

Public transportation

and school Buses

Electric Commercial

Delivery Trucks:Green or Not?

Online retail sales are predicted to be $370 billion in 2017!

Most of these items are delivered to the customers through class 3 to class 5 delivery trucks or vans.

And these vehicles operate in peak hours, with low-speed, long-idling and frequent stop-and-go.

Sounds like a perfect situation for electric vehicles, but is it?

We performed a study to compare the environmental performance of:

Electric delivery trucks with other conventional

or alternative fuel powered trucks throughout the entire life cycle.

Diesel Hybrid CNG E-3 E-5

Infrastructure 0.00 0.00 8.90 2.21 3.31

Tailpipe 142.40 117.44 124.47 0.00 0.00

Fuel Consumption 10.70 8.82 20.98 167.17 354.55

Maintenace and Repair 3.66 3.96 2.05 1.96 2.65

Battery Manufacturing 0.00 0.21 0.00 9.36 11.71

Vehicle Manufacturing 18.53 28.35 28.84 30.67 14.28

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Vehicle Manufacturing Battery Manufacturing Maintenace and Repair Fuel Consumption Tailpipe Infrastructure

Zhao, Y., Onat, N.C., Kucukvar, M., Tatari, O., 2016. Carbon and energy footprints of electric delivery trucks: a hybrid multi-regional input-output life cycle assessment. Transportation Research Part D: Transport and Environment 47, 195-207

Although there is zero tailpipe emission, battery electric delivery trucks would not reduce GHG or energy consumption footprint as expected.

Grid independent hybrid electric trucks are the most favorable choice since the brake energy recapturing feature and relatively lower price.

Comparison with buses: Daily VMT of buses is two times the VMT of trucks. Fuel economy of buses is almost five times worse than

trucks’. Buses consumes much more fuel, and makes electric buses

more favorable.

Zhao, Y., Tatari, O., 2015. A hybrid life cycle assessment of the vehicle-to-grid application in light duty commercial fleet. Energy 93, 1277-1286

Electricity has to be generated and consumed simultaneously. If the real time demand for electric power is less than

its generation, electricity is ultimately wasted due to the lack of storage methods in the grid.

To balance the fluctuation and increase the reliability of the grid, low-efficiency combustion turbines have been used to ramp up or ramp down the output of the electricity generation.

Vehicle to Grid (V2G) technology, which utilizes the battery capacity of idling EVs as grid storage, might be able to improve the reliability of the power grid by providing ancillary services, and reduce the GHG emission.

A delivery truck fleet of 30 trucks will be sufficient to sign an ancillary service contract. (minimum capacity requirement 1MW, and this number will drop to 100 kW in some regions, which encourages more players to join)

Vehicle-to-grid applications in light duty commercial fleet

Delivery trucks are perfect carriers for such services, because: Large capacity battery Fleet operators would plug their

truck in to the grid in order to maximize the profit

No range anxiety (fixed route)

Zhao, Y., Tatari, O., 2015. A hybrid life cycle assessment of the vehicle-to-grid application in light duty commercial fleet. Energy 93, 1277-1286 GHG emission savings

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Fuel Supply Maintenance Charging Infrastructure

Tailpipe Electricity Saving

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Tailpipe Electricity Saving

Results show that both extended range electric trucks and battery electric trucks are viable regulation service providers for saving greenhouse gas emissions.

The emissions caused by electricity consumption could be offset by the emissions saved through V2G systems.

Vehicle-to-grid applications in light duty commercial fleet

Aim of study: To investigate the potential net present revenues and greenhouse gas emission mitigation of V2G regulation services provided by electric trucks in a typical parcel delivery fleet

Methods: A process based life cycle emission assessment and a life cycle ownership cost assessment are combined to form a V2G regional analysis model

Economic and Environmental Benefit Analysis of Vehicle to Grid Regulation Services

www.automotive-fleet.com

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Zhao, Y., Noori, M., Tatari, O., 2016b. Vehicle to Grid regulation services of electric delivery trucks: Economic and environmental benefit analysis. Applied Energy

By plugging an idled truck into the grid for V2G regulation services, a single truck is able to save as many as 200 to 500 tons of CO2 over its 15-year lifetime.

Regional Abbreviations: PJM Interconnection (PJM), ISO New England(ISONE), New York ISO (NYISO), Electric Reliability Council of Texas(ERCT), and California ISO (CAISO)

Can Light-duty electric vehicles improve the integrity of the electricity grid through Vehicle-to-Grid technology?

Aim of study: To predict the emissions savings and net revenue of electric vehicles providing vehicle to grid services in five different Independent System Operator/Regional Transmission Organization regions

Methods: The EV market penetration rates are

predicted using an Agent-Based Model.

The future net revenue and emissions savings of integrating vehicle to grid technology into the grid is estimated through an exploratory model with all uncertainties taken into consideration.

Can light-duty electric vehicles improve the integrity of the electricity grid through Vehicle-to-Grid technology?

Analysis of regional net revenue and emissions savings

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Noori, M., Zhao, Y., Onat, N.C., Gardner, S., Tatari, O., 2016. Light-duty electric vehicles to improve the integrity of the electricity grid through Vehicle-to-Grid technology: Analysis of regional net revenue and emissions savings. Applied Energy 168, 146-158

Worst case scenario in PJM and NYISO, the income from V2G service could still be about

$130/month, which equals to the monthly payment of a full-coverage auto insurance policy

Regional Abbreviations:PJM Interconnection (PJM), ISO New England(ISONE), New York ISO (NYISO), ElectricReliability Council of Texas (ERCT), and CaliforniaISO (CAISO)

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehiclesDelivery trucks

Heavy-duty trucksPublic transportation

and school Buses

What if our heavy-duty trucks run on electricity?

Is it worth electrifying the U.S. heavy-duty class 8 trucks?

• Objective of the study:We compared hybrid, biodiesel, CNG, and

battery electric (BE) heavy-duty trucks with respect to:

• life-cycle GHG emissions• costs (LCCs)• air pollution externalities (APE) taking into account the load-specific fuel

economy (LSFE) of trucks

• Methods Hybrid life-cycle assessment (hybrid-LCA)Monte Carlo Simulation to account for the

uncertainty in the data

Life-Cycle Cost (LCC) Comparison

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Infrastructure Battery Replacement Tailpipe Fuel Consumption

CNG-fueled trucks provide negligible improvements compared to conventional trucks in terms of overall LCCs.

Despite its incremental costs, BE trucks outperforms the other alternatives, with the potential to further decrease these costs given its incremental costs are to be decreased.

BE trucks cause 9% less costs than hybrid. Furthermore, the fuel-LCCs of hybrid trucks are almost 50% higher than that of BE trucks, on average.

Life-Cycle Greenhouse Gas Emissions (GHGs)

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CNG-fueled trucks emit the greatest amount of GHGs due to the greater upstream impacts of natural gas production and supply, the lower fuel economy, and the additional part and infrastructure needs.

The only remarkable source of GHG emissions from BE trucks is the

electricity generation.

If the electricity is to be supplied from 100% renewable source, almost

literally-zero-emission trucks are possible!

Health Impact Costs

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Since BE trucks have zero tailpipe emissions, they remarkably help

reduce the health impacts caused by heavy-duty trucks.

Electricity generation is the biggest contributor.

Health Impact Costs denote the costs incurred by the impacts of primary air pollutants (CO, NOx, Sox, PM2.5, PM10, and VOC) on human (e.g. mortality and morbidity) and environmental (e.g. crop and timber loss) health.

GHG emissions from electricity generation in different regions

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If the electricity generated in the NPCC region (the State of New York, the six New England states, and Ontario, Quebec, and the Maritime) is used to run electric heavy-duty- truck, GHG emissions from fuel consumption could be reduced by 63%.

The main reason behind this difference is the share of renewable energy employed in the electricity grid mix of the NPCC region.

TRE: Texas Regional EntityFRRC: Florida Reliability Coordinating CouncilMRO: Midwest Reliability OrganizationNPCC: Northeast Power Coordinating Council

RFC: Reliability First CorporationSERC: SERC Reliability Corporation

SPP: Southwest Power PoolWECC: Western Electricity Coordinating Council

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehiclesDelivery trucks

Heavy-duty trucksPublic transportation

and school Buses

Vehicle-to-Home

Application

Can Vehicle to Home technology be helpful in achieve a Net Zero Energy Building?

Objective: Design a Net Zero Energy Building (NZEB) by

incorporating different sources of electricity including renewable energy, EV battery and grid electricity.

An integrated solution: Solar energy, EV battery storage, and grid electricity are interacting with each other to supply the energy demand of the building.

Methodology Design an energy efficient building. Integrate renewable energy sources into building’s

energy portfolio. UseV2H technology to fulfill the requirements of NZEB. Develop an algorithm to connect different components

of the system in a real-time basis.

Figure: Developed methodology

Figure: Net Zero Energy Building

Alirezaei, Mehdi, Mehdi Noori, and Omer Tatari. "Getting to net zero energy building: Investigating the role of vehicle to home technology." Energy and Buildings 130 (2016): 465-476.

Algorithm Steps:

Check whether or not the EV is connected to the building (assuming vehicle leaves home at 8 AM and return by 5 PM).

Check the amount of generated renewable energy with energy demand of the building (is on-site generated electricity is enough to power the building?).

In each case, the system priority is to supply the energy demand of the building.

Excess amount of on-site generated electricity will be used to charge the EV (if connected).

After fully charging the EV, the main battery will be charged.

The whole system is in the interaction with grid so that it can buy the electricity form grid (if required) and transfer electricity to the grid if energy demand of the building is met and EV and main battery are fully charged.

Figure: Net Zero Energy Building

Results

We compared the hourly and cumulative rate of purchased electricity of the building with and without the integration of solar panels and the EV battery (“NZEB” and “conventional”, respectively).

The purchased electricity drops significantly in the NZEB scenario compared to the conventional scenario, with the average hourly decrease in grid reliance being roughly 61% year-round, while the most visible hourly decrease (93%) was in September.

Figure: Comparison of Hourly and cumulative Energy Consumption of the Building for Conventional and NZEB Scenarios

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Differences in monthly purchased electricity from grid for two NZEB and conventional cases

Cumulative amount of purchased electricity without applying the developed algorithm (conventional method)

Cumulative amount of purchased electricity (NZEB method)

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Figure: Monthly Amount of Electricity Transferred to the Grid

Sold electricity to the grid drops due to high energy demand of the building as the summer begins

Minimum transferred electricity to the grid because generated solar energy is lower

Summer (Apr 1st to Oct 31st) Winter (Nov 1st to Mar 31st)

Hours Price (¢/kWh) Hours Price (¢/kWh)

On-peak hours 13-18 5.936 7-10 & 18-21 4.447

Off-peak hours 20-11 3.759 10-18 2.886

Shoulder hours 11-13 & 18-20 4.527 21-7 (next day) 4.287Non-fuel base charge

N/A 6.918 N/A 6.918

Photovoltaic production incentive

N/A 5 N/A 5

Time rate pricing [2]. Time of use pricing

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Monthly Electricity Price Comparison[1]

These rates were applied to purchased electricity from grid, transferred electricity to the grid, and solar energy generation.

Electricity price for conventional case

Negative values for Electricity price for NZEB case after applying incentives.

Our electricity bill is negative!

Electricity price for NZEB case

Electricity Price

Orlando Utilities Commissions, Fuel charges rate schedule, (2016). http://www.ouc.com/docs/rates---elctric-water-meter/res_er_ouc_rate_tariff.pdf?sfvrsn=2 (accessed April 29, 2016).

Objective: Develop a Net Zero Energy Building (NZEB) through

incorporating V2H technology.

Investigate the dynamic interaction of different components of NZEB system.

Methodology Design an energy efficient building Integrating renewable energy sources into building’s

energy portfolio Using V2H technology to fulfil the requirements of

NZEB Develop an algorithm in Anylogic environment to

connect different components of the system.

Code Compliant

Baseline Energy Efficient Building

Net Zero Energy

Building

Figure: Energy consumption comparison for different types of buildings

Alirezaei, Mehdi, Mehdi Noori, and Omer Tatari. "Application of Vehicle to Home Technology to Achieve a Net Zero Energy Building: An Agent Based Modeling Approach.

Concept:

Based on DOE, Zero Energy Ready Homes have to be at least 40% to 50% more energy-efficient than a typical new home built in the same year.

This definition is more clearly visualized in Figure below, where a rough comparison is shown between the energy consumption levels of a typical code compliant building, a more energy-efficient building, and a NZEB.

Toward an efficient “Building Energy Management System”:Can agent based modeling be helpful in investigating the dynamic nature of NZEB?

Results:1. Average daily required electricity from grid

The differences between green and blue line in each day indicates the reduction of the required electricity from grid.

Figure: Comparison of required grid electricity for conventional and NZEB buildings

Average daily electricity from grid for conventional case

Average daily electricity from grid for NZEB-EV case (except on peak demand during the summer, no electricity is required from the grid)-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4Av

erag

e da

ily re

quire

d el

ectr

icity

from

grid

(kW

h)

Month

NZEB case Conventional case

The amount of electricity taken from the grid is reduced by: 76% compared to a standard code-compliant energy-efficient building 90.2% compared to an ordinary code compliant building(red line)

Electricity consumption of the building is highest during the months of June, July, and August (when the electricity price is at its lowest negative value) because less energy can be transferred to the grid.

Less saving can be made during summer.

3. Hourly electricity cost

Figure: Hourly electricity cost comparison for conventional and NZEB methods

Hourly electricity cost for conventional case

Hourly electricity cost for NZEB-EV case

-0.32

-0.27

-0.22

-0.17

-0.12

-0.07

-0.02

0.03

0.08

0.13

0.18

Aver

age

daily

ele

ctric

ity c

ost (

$)

Month

NZEB case Conventional case

This graph shows the differences between the hourly electricity prices with the conventional and NZEB methods.

With the help of the developed NZEB-EV integration algorithm, total electricity cost drops by 155% compared to conventional code compliant energy inefficient methods!

Journey to the Life Cycle of Electric Vehicles

Light-duty

vehiclesDelivery trucks

Heavy-duty trucksPublic transportation

and school Buses

Vehicle-to-Home

Application

Critical Points Environmental benefits of EVs highly depend on the electricity generation mix.

Battery-Electric transit and school buses have larger battery capacity than passenger vehicles, making them more feasible candidates for V2G service.

There is an enormous potential to neutralize operation related emissions by the use of V2G service for school buses and delivery trucks.

Battery-electric Class 8 trucks yield important improvements in terms of life-cycle costs, life-cycle emissions, and life-cycle air pollution externalities.

Buildings and EVs can be considered together in term of energy supply and consumption.

V2H technology can drastically reduce the cost of electricity through storing electricity in the battery during off-peak hours and deplete it during on-peak hours.

The role of “building energy management system” is critical. Our developed algorithm can manage the flow of electricity at each hour of the day.

For more information: http://evtc.fsec.ucf.edu/1. Onat, N., Kucukvar, M., and Tatari, O. (2015). “Electric conventional, hybrid, plug-in hybrid or

electric vehicles? State-based comparative carbon and energy footprint analysis in the United States.” Applied Energy, Elsevier, 150(2015), 36-49, IF: 5.261. DOI: 10.1016/j.apenergy.2015.04.001

2. Onat, N., Kucukvar, M., and Tatari, O. (2014). “Towards life cycle sustainability assessment of alternative passenger vehicles.” Sustainability, 6(12), 9305-9342, 2015 IF: 1.343. DOI:10.3390/su6129305

3. Onat, N., Kucukvar, M., Tatari, O., and Zheng, Q. D. (2016). “Combined application of multi-criteria optimization and life-cycle sustainability assessment for optimal allocation of alternative passenger vehicles in the United States.” Journal of Cleaner Production, Elsevier, 291-307, 2014 IF: 3.844. DOI: 10.1016/j.jclepro.2015.09.021

4. Onat, N. C., Gumus, S., Kucukvar, M., and Tatari, O. (2016). “Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies.” Sustainable Production and Consumption, Elsevier, 6(2016), 12-25. DOI: 10.1016/j.spc.2015.12.003

5. Onat, N., Kucukvar, M., Tatari, O., and Egilmez, G. (2016). “Integration of System Dynamics Approach towards Deepening and Broadening the Life Cycle Sustainability Assessment Framework: A Case for Electric Vehicles.” International Journal of Life Cycle Assessment, Springer, 21(7), 1009-1034. 2014 IF: 4.844, DOI: 10.1007/s11367-016-1070-4

6. Onat, N.C., Kucukvar, M., and Tatari, O. (2016). “Uncertainty-embedded dynamic life cycle sustainability assessment framework: An ex-ante perspective on the impacts of alternative vehicle options.” Energy, Elsevier, 715-728, DOI: 10.1016/j.energy.2016.06.129

7. Noori, M., Gardner, S., and Tatari, O. (2015). “Electric vehicle cost, emissions, and water footprint in the United States: Development of a regional optimization model.” Energy, Elsevier, 89(2015), 610-625, 2014 IF: 4.844, DOI: 10.1016/j.energy.2015.05.152

8. Noori, M., and Tatari, O. (2016). “Development of an agent-based model for regional market penetration projections of electric vehicles in the United States.” Energy, Elsevier, 96(2016), 215-230, 2014 IF: 4.844. DOI: 10.1016/j.energy.2015.12.018

9. Noori, M., Zhao, Y., Onat, N., Gardner, S., and Tatari, O. (2016). “Light-duty electric vehicles to improve the integrity of the electricity grid through vehicle-to-grid technology: Analysis of regional net revenue and emissions savings.” Applied Energy, Elsevier, 168(2016), 146-158, 2014 IF: 5.261. DOI: 10.1016/j.apenergy.2016.01.030

10. Ercan, T., and Tatari, O. (2015). “A hybrid life cycle assessment of public transportation buses with alternative fuel options.” International Journal of Life Cycle Assessment, Springer, 20(9), 1213-1231, 2014 IF: 3.988. DOI: 10.1007/s11367-015-0927-2

11. Ercan T., Onat N.C., and Tatari O. (2016). “Investigating Carbon Footprint Reduction Potential of Public Transportation in U.S.: A system Dynamic Approach.” Journal of Cleaner Production, Elsevier, 133(2016), 1260-1276, 2014 IF: 3.844. DOI: 10.1016/j.jclepro.2016.06.051

12. Ercan, T., Yang, Z., Tatari, O., and Pazour, J. (2015). “Optimization of transit bus fleet’s life cycle assessment impacts with alternative fuel options." Energy, Elsevier, 2015, 323-334, 2014 IF: 4.844. DOI: 10.1016/j.energy.2015.09.018

13. Ercan, T., Noori, M., Zhao, Y., and Tatari, O. (2016). “On the front lines of a sustainable transportation fleet: Applications of vehicle-to-grid technology for transit and school buses.” Energies, 9(4), 230, 1-22, 2014 IF: 2.077. DOI: 10.3390/en9040230

1. Zhao, Y., Onat, N., and Tatari, O. (2016). “Comprehensive Life Cycle Assessment of Electric Delivery Truck.” Transportation Research Part D: Transport and Environment, Elsevier, 47(2016), 195-207, 2014 IF: 1.937. DOI: 10.1016/j.trd.2016.05.014

2. Zhao, Y., Ercan, T., and Tatari, O. (2016). “Life Cycle Based Multi-Criteria Optimization for Optimal Allocation of Commercial Delivery Truck Fleet in the United States.” Sustainable Production and Consumption, Elsevier. DOI: 10.1016/j.spc.2016.04.003

3. Zhao, Y., and Tatari, O. (2015). “A hybrid life cycle assessment of the vehicle-to-grid application in light duty commercial fleet.” Energy, Elsevier, 1277-1286, 2014 IF: 4.844. DOI:10.1016/j.energy.2015.10.019

4. Zhao, Y., Noori, M., and Tatari, O. (2016). “Vehicle to Grid regulation services of electric delivery trucks: Economic and environmental benefit analysis.” Applied Energy, Elsevier,170(2016), 161-175, 2014 IF: 5.261. DOI: 10.1016/j.apenergy.2016.02.097

5. Sen, B., Ercan, T., and Tatari, O. (2016). “Does a battery-electric truck make a difference? –Life cycle emissions, costs, and externality analysis of alternative fuel-powered Class 8 heavy-duty trucks in the United States.” Journal of Cleaner Production, Elsevier, 141(2017), 110-121, 2015 IF: 4.959. DOI: 10.1016/j.jclepro.2016.09.046

6. Alirezaei, M., Noori, M., and Tatari, O. (2016). “Getting to net zero energy building: investigating the role of vehicle to home technology.” Energy and Buildings, Elsevier. 2014 IF: 2.884. DOI: 10.1016/j.enbuild.2016.08.044

Thank you!Omer Tatari, Ph.D., LEED AP

Associate Professor and Graduate Program Director

Co-Director of EVTC

Department of Civil, Environmental, and Construction Engineering

University of Central Florida

tatari@ucf.edu