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Mathias Müller 01.11.2019

E-Mobility Integration Symposium

Methodology for simulation of large distribution grids with dynamic generation of load profiles

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Agenda

1. Introduction and motivation (C/sells)

2. Simulation model GridSim and charging strategies

3. Methodology for dynamic load profile generation

4. Evaluation of methodology

5. Summary

C/sells – showcases for smart network solutions

• Part of SINTEG funding programme (BMWi-supported)

• Duration 01.01.2017 - 31.12.2020 • C/sells is largest SINTEG showcase • Demonstration area covering Baden-Württemberg,

Bavaria and Hesse • 56 partners from science, business & industry

• 34 technical demonstrators • 9 participation cells

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Altdorf Flexibility Market as part of C/sells

Flexbilitiy market on distribution grid level

Altdorf Flexibility Market (ALF)

Region: Altdorf area, Bavaria Leading project partner: Targets of the demo cell: • Determination of flexibility requirements in

the distribution grid • Development and implementation of a

flexibility market mechanism • Demonstration including citizen participation

Number of participating citizens: 30 – 60

In collaboration with:

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The project region in Altdorf

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MV networkOther areas consideredAltdorf municipality

Key facts: • 2 HV/MV transformers

• 8 MV feeders

• 173 low-voltage grids

• 4,200 buildings with 8,000 households

• 2,429 PV plants

• 493 heat pumps

• 778 electric storage heaters

• …

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Available data for modeling grid load

Detailed low-voltage grids • 10 grids (1 medium-voltage feeder)

• Modeling each grid connection point (building)

with synthetic load profiles • Housholds • Trade and commerce (standard load

profiles) • Electric heating • PV plants

Detailed simulation of the whole low voltage grid

Aggregated low-voltage grids • 163 grids were models as medium-voltage

loads

• Modeling via standard load profiles and scaling by annual energy consumption / installed power

• Housholds • Trade and commerce • Electric heating • PV plants

Aggregation of the whole grid to the MV connection point

Differentiation between aggregated and detailed low-voltage grids

Overview of the combined simulation

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HV MV

MV LV

Detailed grid connection point

Detailed low-voltage grid Medium-voltage grid

aggregated detailed

How to simulate EVs other flexibility options with new operation modes in aggregated grids?

To many influences to calculate load profiles in advance for EVs with different charging strategies 8

9 profiles type of day (3)

season (3)

Heat pump (uncontrolled) 35 profiles temperature (35)

Household

?? profiles

type of day (3)

temperature (35)

EV charging power

PV surplus*

electricity price* *depending on charging strategy

• General: • Charging power 50 %: 3,7 kW | 50 %: 11 kW • 274 EVs simulated in detail

• Uncontrolled charging:

• EV is charged directly after plug-in • EV is charged with maximum power

• Self-consumption optimized: • EV is charged directly up to 40 % SoC • Charging with PV surplus • Charging before departure up to

70 % SoC

Charging strategies for EVs

Charging strategy has big impact on the resulting load curve! 9

Dynamic generation of load profiles and usage in simulation

Methodology for dynamic load profile generation 10

Calculating charging power per EV and

timestep depending on charging strategy

Calculating average profil per EV and

timestep

Scaling the average profil per aggregated

grid

Statistical evaluation of the methodology

The standard deviation is decreasing with the number of EVs 11

Questions:

• When ist the proposed methodology valid?

• How many EVs must be simulated in detail?

• What is the expected error?

Statistical Evaluation of 1,900 charging profiles

Calculating standard deviation for different numbers of EVs for 100 samples each

Statistical evaluation of the methodology (II)

Methodoly is valid for more than 50 EVs modelled in detail 12

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Average standard deviation is decreasing rapidly with number of EVs (cut by half from 10 – 50 EVs)

Maximum standard deviation is around twice as high as the average standard deviation

Relevance for grid simulation

e.g. transformer (400 kVA) with 50 EV

Average standard deviation: ± 10 kW

Maximum standard deviation: ± 22,8 kW

This is only around 2,5/5 % of the installed capacity

Critical Review

The developed method can be adjusted for other cases. 13

Methodology is only valid for a high numbers of EV (simulated in detail and also per aggregated grid)

Small number simulated in detail: Small number in aggregated grids: Case

Weak point Average load profile can have high gradients (is not really smooth)

Taking more than the current power to calculate the profile. Including previous power

into the calculation by using some weithing factors (need to be determined…)

Improvements

Resulting total power is very low

Picking individual load profiles instead of scaling the average profile (risk of to high

simultaneity factors)

Summary

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Methodology to simulate EVs with different charging strategies in low- and medium-voltage grids was developed

Methodolgy works good for high numbers of EV (adjustments for lower numbers are possible)

Methodology also works for heat pumps or storages

Aim of the presented work is the perform load flow calculations in medium-voltage grids

?!„…“

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Question? Thank you

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Forschungsstelle für Energiewirtschaft e. V. Am Blütenanger 71 80995 München Tel.: +49 89 158 121 – 0 Email: info@ffe.de Internet: www.ffe.de Twitter: @FfE_Muenchen

Mathias Müller, M. Sc.

mmueller@ffe.de

+49 89 158 121 - 32

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