Impact of Increasing Electric Mobility on a Distribution Grid at the Medium Voltage Level. Julia Vopava

Transcription

1 Impact of Increasing Electric Mobility on a Distribution Grid at the Medium Voltage Level Julia Vopava

2 Agenda Introduction Methodology Cellular Approach Determining load profiles for charging stations Results Overview Load flow calculation Self sufficiency Outlook 2

3 Introduction Increasing number of charging stations for electric vehicles decrease of supply security and grid stability Charging powers < 100 kw low voltage level (grid level 7) > 100 kw (super charges up to 350 kw) transformer station between medium and low voltage level (grid level 6) > 400 kw medium voltage level (grid level 5) Regulated in: General terms and conditions for access to distribution grids in Austria Increasing energy demand is transported at medium-voltage level FFG-Project Move2Grid focuses on the medium voltage level 3

4 Methodology Development of a distribution grid model Determining photovoltaic supply potentials Determining load profiles for charging stations Load flow calculations with time resolved load profiles Evaluation of the results Development of measures to avoid grid instability 4

5 Cellular approach Power, heat and gas grids = flexible analysis method Simplification of complex grid structures Compromises between accuracy and calculation time Distribution grid model Cell classification in consideration of grid topology Medium voltage level (30 kv and 5 kv level) Annual energy consumption (MWh) 5

6 Determining load profiles for charging stations 0. Data collection - Assumptions Li-Ion Batteries Average consumption = 16 kwh/ 100km* Battery capacity 20 kwh* Charging power depends on the desired scenario (best practice/ future trends) * can be chosen individually 6

7 Determining load profiles for charging stations 1. Data collection and preparing data Traffic analyses for the city of Leoben Including: 7 different user groups classification is made by the purpose of the trip Distance travelled Number of trips per day Purpose of the trip Home Recreational activities Work private car Work company car Education (school, university, ) Daily activities Shopping 7

8 Determining load profiles for charging stations 1. Data collection and preparing data Origin-destination matrices according to Bosserhoff Based on statistical evaluation of traffic behaviour for a specific time interval and area Processing Data distribution function: time of arrival and departure for each user group 8

9 Determining load profiles for charging stations 2. Probabilistic approaches Distribution function - driven distance distance travelled Distribution function - time of arrival / departure start / end of the charging process Effect on the shape of the load profile 9

10 Determining load profiles for charging stations 3. Modelling the charging curve P const CC constant current CV constant voltage 1 charging process s P charging power s change over point k L correction factor P const constant power SOC state of charge 10

11 Jul 07 Jul 08 Jul 09 Jul 10 Jul 11 Jul 12 Jul 13 Jul 14 Determining load profiles for charging stations 3. Modelling the charging curve cell 01 cell 11 cell power (kw) weekday Saturday Sunday aggregated load profile 11

12 Determining load profiles for charging stations 3. Modelling the charging curve UG: work + daily activities UG: daily activities cell 01 cell 11 cell power (kw) :00 06:00 12:00 18:00 00:00 Jul 08, 2014 UG user group UG: work (shift operation) 12

13 Results Overview Overview Scenarios Penetration rate of: Scenario 1 Scenario 2 Scenario 3 Scenario 4 Photovoltaic potential (PV) [%] Electric mobility (EV) [%] Purpose of the trip Charging power [kw] Home 3.70 Recreational Activities Work private car 3.70 Work company car 3.70 Education (school, university, ) 3.70 Daily activities Shopping

14 Results Load Flow Calculations Scenario 1 Scenario 2 Scenario 3 Scenario 4 Comparison of the maximum utilisation utilisation (%) cables are overloaded only EV 7 cables are overloaded with 50% PV penetration 0 LTG0216_005_1 LTG0304_005_1 LTG0513_005_1 LTG0605_005_1 LTG0610_005_2 LTG1013_005_1 LTG1124_005_1 LTG1804_005_1 LTG1819_005_1 LTG1823_005_1 LTG2122_005_ demand - 100% electric mobility 25% PV potential 50% PV potential demand - status quo Scenario PV [%] power(kw) EV [%] Demand vs. PV production cell :00 06:00 12:00 18:00 00:00 Aug 10,

15 Results Load Flow Calculations scenario 2 LTG1124 scenario 2 LTG1804 scenario 2 LTG1823 scenario 3 LTG1124 scenario 3 LTG1804 scenario 3 LTG1823 scenario 4 LTG1124 scenario 4 LTG1804 scenario 4 LTG Simulation period = 1 year utilisation (%) Duration of the utilisation of the overloaded cables hours (h) 200 scenario 2 LTG1124 scenario 2 LTG scenario 2 LTG1823 scenario 3 LTG1124 scenario 3 LTG1804 scenario 3 LTG scenario 4 LTG1124 scenario 4 LTG1804 Scenario hours scenario 4 LTG1823 PV [%] utilisation (%) hours EV [%] hours (h) 15

16 Results Load Flow Calculations transformer is overloaded ~65h a year scenario 1 scenario 1 scenario 2 scenario 2 scenario 3 scenario 3 scenario 4 scenario Duration of the load flow / utilisation of the transformer ustilisation ustilisation (%) (%) from medium to high voltage level hours hours (h) (h) scenario 1 scenario 2 scenario 3 scenario 4 power (MW) 20 0 Scenario PV [%] EV [%] hours (h) 16

17 Results Self Sufficiency ssssssff ssssssssssssssssssssss = EE PPPPPPPPPPPPPPPPPPPP + EE PPPP PPPPPPPPPPPPPPPPPP,uuuuuuuu EE DDDDDDDDDDDD + EE eeeeeeeeeeeeeeee mmmmmmmmmmmmmmmm.uuuuuuuu Overall system energy demand and production [GWh] Demand Status Quo Production Status Quo electric mobility (EV) 100% photovoltaic potential (PV) 25% photovoltaic potential (PV) 50% EE DDDDDDDDDDDD EE PPPPPPPPPPPPPPPPPPPP 85.3 EE eeeeeeeeeeeeeeee mmmmmmmmmmmmmmmm.uuuuuuuu 71.9 EE PPPP PPPPPPPPPPPPPPPPPP,uuuuuuuu 25.9 EE PPPP PPPPPPPPPPPPPPPPPP,uuuuuuuu cell cell 13 cell cell 22 1 overall system Scenario PV [%] self-sufficiency (-) EV [%] scenario 1 scenario 2 scenario 3 scenario 4 17

18 Outlook Further Scenarios Different charging powers 11/22 kw 22/50 kw 22/100 kw Controlled charging User groups with average duration of stay > 6 hours Storage integration To avoid grid instability Not comprehensive Load profiles determined + Scenarios evaluated Different penetration rates of electric mobility and Photovoltaic Potentials 18

19 Thank you for your attention Julia Vopava