fleets of electric vehicles as adjustable loads ...use of fleet of evs as controllable loads (i.e....

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Fleets of electric vehicles as adjustable loads –Facilitating the integration of electricity generation

by renewable energy sources

Katrin Seddig1,2; Patrick Jochem2; Wolf Fichtner2

1 Energy Solution Center (EnSoC) 2 Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP), Chair of Energy Economics

New York, 17.06.2014 – 37th IAEE International Conference

Katrin Seddig, Patrick Jochem, Wolf Fichtner 17.06.20142

Introduction

Methods and data

Results

Conclusion and outlook

Agenda


Introduction

Situation

“Energy Transition” in Germany aims to reduce greenhouse gas emissions, e. g. by

Energy efficiency increase in industry

Build-up of wind energy and photovoltaic systems

Growing share of electric vehicles (EV) and alternative fuels in the transportation sector

Complication

An Increasing number of EV cause

Increase of energy consumption of a representative household

Influence of the grid load (i.e. peak power)

Objections of the actual research project (‚Integrated fleet and charge management‘)

Use of fleet of EVs as controllable loads (i.e. controllable electricity consumption in time and power)

Quantification of their load shifting potential

Integration of renewable energy sources (RES)

Impacts of different charging strategies

3

Introduction Methods and data Results Conclusion and outlook


Increased share of renewable energy sources in Germany

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Shar

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%]

Years

Geothermal energyPhotovoltaicsBiomassWind energyHydropower

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05

101520253035

Inst

alle

d C

apac

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in G

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Wh

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Years

Electricitysupply

Installedcapacitiy


Development of electricity consumption from RES in German from 2000 - 2012

Development of electricity supply of installed capacity and from PV plants in Germany

Data source: BMWi (2013)

Data source: BMWi (2013), Fraunhofer ISE (2014)


Corresponding load shifting potentials might equalize the supply side fluctuations and could therefore help to increase the share of electricity generation by RES

Possibilities to integrate EVs for load shifting

Might lead to a stabilization of the grid and it could be used as a balancing capacity

Load shiftingAvoid peak-loads

(peak shaving)

Avoid low loads(valley filling)

Demand Response

5

Source: Based on Jochem et al. (2013)



Multi-agent based simulation - Overview of main agents

6

Agents

Electric Vehicles

Specifications:

- Battery capacity : 24 kWh- Average electricity

consumption: 0.2 kWh/km

Fleets of EV

Specifications:- Short term parker- Long term parker- Commercial fleet

Charging points

Charging power:

- 3.7 kW - 22 kW

Assumptions, e. g.: For each electric vehicle is a charging point available and for the duration of the parking

time, it is connected Each EV is assigned to a mode of charging power, however within this, it is possible to

charge with varying charging power



Model structure

Calculations are performed in a 1-minute resolution (𝑡 ∈ {1, … , 𝑇})

Limitation of the power input for the parking garage is foreseen

It depends on the maximum power of the building connection (PBC)

As long as there is enough charging power available for the EV (PEVSE) at the charging points 𝑖 ∈{1,… , 𝐼}, the EV charges at the residual load

PBC ≥ 𝑖 𝑃𝐸𝑉𝑆𝐸𝑖,𝑡 ∀ 𝑡; with PBC Maximum power of building connection

PEVSE Charging power of EV at charging point i

EVSE Electric vehicle supply equipment

If maximum power is reached no new customer request for charging will be accepted, until charging power is available (due to a finished charging process from another EV)

If a charging request of an EV is denied the success rate drops

If parking time is longer than charging time, then load shifting is possible

7



Input data for each fleet of the electric vehicles

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Rel

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Length of stay [h]

Short term parker

Commuter

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5 15 25 35 45 55 65 75 85 95 105R

elat

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Distance [km]

Short term parker(Leisure, Shopping,others)Commuter

Parking duration of EV fleets during a weekday in aparking garage

Distance of trip (national wide data)


Data source: PBW (2013) Data source: BMVBS (2012)

For commercial fleets data was statistically analyzed to derive synthetical driving profiles Short and long term parker were analyzed using data from a parking garage


Overview of chosen scenarios

9

Uncoordinated charging

(Mode 2 or Mode 3)Summer PV Winter PV Without PV

Strategy SoC 100 x x

Strategy SoC next trip


For all scenarios 75 commercial EVs, 150 long term and 150 short term EVs are considered

PV specifications: On the roof of the parking garage maximum usable potential of 200 kWp

Summer PV: total feed-in of 8420 kWh (Mo - Fr) Winter PV: electricity supply of 333 kWh (Mo - Fr)


Impacts of the charging strategiesUncontrolled charging without PV

10


Without PV the success rate for the requests of EVs drops As maximum power limit of the building connection is reached

Maximum Power of BC (PBC) Accumulated charging power of all fleets

Commercial fleet Short term parker Long term parker


Impacts of the charging strategiesUncontrolled charging with summer feed-in data for PV

Charging curve changes

Higher flexibility for load shifting is available

Nearly no charging over night is necessary, however, possible (especially for the commercial fleets)

11

Available charging power Accumulated charging power of all fleets

Commercial fleet Short term parker Long term parker



Impacts of the charging strategiesUsing preferable PV

With adapted charging scheduling algorithm:

82 % of the electricity could be supplied by the PV plants

Up to 100% of generated PV electricity can be used

12

Available charging power Accumulated charging power of all fleets

Used PV energy for charging Other electricity used for charging



Impacts of the charging strategiesCO2 emission reduction by each fleet

Long term parker could reduce the most CO2 emissions

1.23 t CO2 reduction (if German average CO2 emission factor for the energy mix of 477 g CO2/kWhel

is used)

Have the highest load shifting potential during a day due to their long parking time

13

Available PV charging power Commercial fleetShort term parker Long term parker



Conclusion

An integration of (local) electricity generation by RES is promising

Leads to a release of the local electricity grid

Generated PV electricity of the parking garage can be used nearly up to 100 %

Charging behavior of commuters can be adapted towards PV integration

Results of the simulation show:

Load shift potential towards different parts of the day is significant and might substitute local storages or grid extensions

Commercial fleets might provide high load shift potentials during nights e. g. for ‘wind integration’

14



Outlook

Implementation of monetary values

Adaption of charging strategies

Priorization of fleets depending on the willingness to pay (different scheduling algorithms)

Developing different business models for the involved parties (e. g. energy supplier, parking garage operator)

Integration of wind energy as one part of the charging power

Could improve the flexibility for load shifting

Improvement of the profitability of public charging stations through a charging scheduling algorithm

15



Thank you for your attention!

Katrin Seddig

Energy Solution Center (EnSoC) e. V.

Research Assistant

Phone: +49 721 754033-14

Email: [email protected]


Flath, C.; Ilg, J.; Gottwalt, S.; Schmeck, H.; Weinhardt, C. (2013): Improving Electric Vehicle Charging Coordination Through Area Pricing, Transportation Science.

Waraich, R.A., M.D. Galus, C. Dobler, M. Balmer, G. Andersson und K.W. Axhausen (2013): Plug-in Hybrid Electric Vehicles and Smart Grid: Investigations Based on a Micro-Simulation, Transportation Research Part C, 28, S. 74-86.

Kaschub, T.; Jochem, P. und Fichtner, W. (2013): Steigerung des Elektrizitätseigenverbrauchs von Heim-Fotovoltaikanlagen durch Elektrofahrzeuge, in uwf UmweltWirtschaftsForum, Vol. 21, Heft 3 (2013), S. 243-250.

BMVBS [German Federal Ministry of Transport, Construction and City Development] (2012): Kraftfahrzeugverkehr in Deutschland 2010, Braunschweig, Germany.

Jochem, P.; Kaschub, T. und Fichtner, W. (2013): How to integrate electric vehicles in the future energy system? in: Hülsmann, M and Fornahl, D. (Eds.): Evolutionary Paths Towards the Mobility Patterns of the Future, Springer, Heidelberg.

ADACautotest (2012): Nissan Leaf, <http://www.adac.de/_ext/itr/tests/Autotest/AT4719_Nissan_Leaf/Nissan_Leaf.pdf>, abgerufen am 22.01.2014.

Pfriem, M. und Gauterin, F. (2013): Less range as a possible solution for the market success of electric vehicles in commercial fleets, Proceedings of EVS27-Conference, Barcelona.

Uhrig, M.; Leibfried, T. (2013): Ausbaubedarf von Parkhäusern zum Laden von Elektrofahrzeugen, in proceedings of ETG Kongress 2013, Berlin, Germany.

Fraunhofer ISE (2014): Aktuelle Fakten zur Photovoltaik in Deutschland, Freiburg, Germany.

BMWi [German Federal Ministry for Economic Affairs and Technology] (2013): Erneuerbare Energien, Accessed February 2014, http://www.bmwi.de/DE/Themen/Energie/Energiedaten-und-analysen/Energiedaten/ energietraeger.html.

Meteotest. Accessed March 2014, http://www.meteotest.ch/.

Jochem, P.; Babrowski, S.; Kaltenbach, N.; Fichtner, W. (2013): Electric Vehicle Market Penetration and Corresponding CO2 Emissions: A German Case Study For 2030, Proceedings of IAEE Conference, Düsseldorf, Germany.

References


Global radiation for some weekdays of Stuttgart (Germany) area in 2013

Global radiation was about 1090 kWh/m2/a in Stuttgart in 2013

generated energy by PV for the considered parking garage about 218 MWh

Back up

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Monday Tuesday Wednesday Thursday Friday

4.-8. February 8.-12. April 15.-19. July 25.-29. November

Data source: Meteotest (2014)


CountryAverage CO2 Emission in

g CO2/kWhel g CO2/km*

Austria 215 43

Brazil 68 14

Canada 167 33

People’s Rep. of China 764 153

Denmark 315 63

France 61 12

Germany 477 95

India 856 171

Japan 497 99

South Africa 869 174

Sweden 17 3

Thailand 522 104

Turkey 472 94

United Kingdom 441 88

United States 503 101

World 536 107

Back up

* Calculated with an assumed EV electricity consumption of 0.2 kWh/km.

CO2 emissions of EV in different countries in 2011

Data source: Jochem et al. (2013)

fleets of electric vehicles as adjustable loads ...use of fleet of evs as controllable loads (i.e....

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