LF Energy Power Grid Model Meetup December 2023

Power Grid Model Meet-up
7 December 2023
Alliander N.V. | powergridmodel@lists.lfenergy.org
This session is being recorded.

Safety First
● In case of emergency
- follow signs of emergency exit
● Don't drive and call, also not hands-free
● This session will be recorded and photographed
● Online participants can post questions in the chat

Tony Xiang
● Lead scientific engineer at Alliander
● Guest lecturer at Eindhoven University of Technology
● Chair of the power-grid-model project

Agenda (UTC+1)
• 13:00 Walk-in + Coffee
• 13:30 Opening - Tony Xiang, chair PGM project, Alliander
• 13:40 Welcome Address: Enexis Digitization and Open-Source
- Alexander Verweij, manager CIO office Enexis
• 14:10 Predicting Future Network Congestion Arising from the Energy Transition Using the Power Grid Model
• - Joni Hermans & Kenneth Ruys, Enexis
• 14:40 Coffee break
• 15:10 Fairness-incorporated Online Feedback Optimization for Real-time Distribution Grid Management
- Sen Zhan, TU Eindhoven
• 15:40 Highlights Q3/Q4 2023 + Community Announcements + Brainstorm/Planning
- Peter Salemink, development lead PGM maintainers, Alliander
• 16:20 Closing - Tony Xiang
• 16:30 Drinks and Networking
• 17:30 End

Efficiënter gebruik van
het elektriciteitsnet
Platform Energietransitie 27 september 2023

Uitvoering van de energietransitie
ONZE MISSIE: Wij brengen mensen steeds meer duurzame energie. Dat doen wij door mede richting te geven
aan het energiesysteem van de toekomst en door slim te investeren in betrouwbare energie-infrastructuur. Zo
houden wij de energietransitie haalbaar en betaalbaar.
• Jaarlijks minimaal 1 GW meer netcapaciteit.
• Jaarlijkse uitvalduur: elektriciteit ≤ 17,5 minuten.
• CES klanten marktprocessen vanaf 2024 gemiddeld ≤ 15%.
• We sluiten minimaal 85% van onze klanten aan op de door hen
gewenste datum.
Wij bieden
iedereen altijd
toegang tot
energie
Klanten weten
wat ze aan ons
hebben
• Wij dragen onze visie actief uit.
• Optimale maatschappelijke keuzes in plannen (zoals RES, CES
en NAL).
• Proactief en transparant in contact met onze omgeving.
Wij sturen aan op
maatschappelijk
optimale
energiekeuzes

Uitvoering van de energietransitie: de Nieuwe Realiteit
DE NIEUWE REALITEIT: Altijd en overal toegang hebben en krijgen tot het elektriciteitsnet is niet langer vanzelfsprekend.
Wij bieden iedereen altijd
toegang tot energie
Klanten weten wat ze aan
ons hebben
Wij sturen aan op
maatschappelijk optimale
energiekeuzes
Wij vinden het belangrijk dat klanten en andere stakeholders weten waar zij aan toe zijn: op korte termijn kunnen
wij onze belofte niet overal en altijd waarmaken. Wij hebben elkaar, onze stakeholders en medewerking van onze
klanten nodig om verder te komen en nog meer te versnellen.
Zelfs als wij al onze groei-ambities realiseren, zal er voorlopig onvoldoende netcapaciteit zijn om al onze
grootzakelijke klanten te bedienen. Dat zet extra druk op ons doel om duidelijk te zijn naar onze klanten en om
hen transparant te informeren over de (on)mogelijkheden.
De (klant)vraag naar capaciteit op het elektriciteitsnet groeit explosief. Wij kunnen de ontwikkeling van de vraag
niet bijbenen en het netwerk niet snel genoeg uitbreiden. Ons doel om iedereen altijd toegang tot energie te
bieden, staat daardoor onder druk.
Als consumenten, zakelijke klanten en de industrie in de basis niets veranderen aan de manier waarop ze
gebruikmaken van het elektriciteitsnet, houdt de schaarste nog lang aan.

Transportschaarste
Afname elektriciteitsnet
Invoeding elektriciteitsnet

Groei wachtlijsten voor afname en productie
2,108
1942
0
500
1000
1500
2000
2500
0
500
1,000
1,500
2,000
2,500
Q1 2022 Q2 2022 Q3 2022 Q4 2022 Q1 2023 Q2 2023*
Ontwikkeling wachtlijst afname (excl. batterij aanvragen)
Gewenst contract vermogen Afname in MW Aantal aanvragen
*Q2 2023 bijgewerkt tot 12 juni
16,552
4917
0
1000
2000
3000
4000
5000
6000
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
Q1
2021
Q2
2021
Q3
2021
Q4
2021
Q1
2022
Q2
2022
Q3
2022
Q4
2022
Q1
2023
Q2
2023*
Ontwikkeling wachtlijst teruglevering (excl. batterij
aanvragen)
Gewenst contract vermogen TLV in MW Aantal aanvragen
*Q2 2023 bijgewerkt tot 12 juni
Het aantal aanvragen voor netaansluitingen voor afname van en teruglevering aan het net is de afgelopen jaren snel gegroeid.
Deze groei heeft geleid tot een groeiende wachtlijst met aanvragen, langere realisatietermijnen, en transportschaarste.

Proactieve investeringen Drenthe
62 65 98%
4 65 1625%
1454 2202 151%
MS-T
stations
Transfor-
matoren
MS-T
kabel
Structurele oplossing: bouwen, bouwen, bouwen.
Versneld uitbreiden
hoogspannings-
stations
Ons doel is om op onze
hoogspanningsstations zo
snel mogelijk zoveel
mogelijk netcapaciteit te
realiseren.
Dit doel bereiken wij door
vergaand te
standaardiseren,
grootschalig in te kopen en
de kavels zoveel mogelijk in
één enkel project helemaal
vol te bouwen.
Wij implementeren een pro-
actieve investerings-
strategie voor onze MS- en
LS-netten. Zo bereiden wij
deze netten voor op de
initiatieven van onze
klanten en voorkomen wij
vertraging van hun plannen.
Daarbij bieden wij
aannemers langjarige
(werk)garanties.
Pro-actief investeren
in MS- en LS-
distributienetten
Wij standaardiseren onze
netcomponenten verder om
de productie van onze
toeleveranciers te vergroten
en onze logistiek te
vereenvoudigen.
Standaardisatie
Werkzaamheden
E groeien snel!
Ons werkpakket is
verdubbeld in 5
jaar tijd!
Ons werkpakket groeit
enorm

Waar kunnen wij op de korte termijn samen aan werken?
Congestie
management
Partijen nemen op
piekmomenten tegen
vergoeding maatregelen
om hun bijdrage aan
deze piek te reduceren.
Daardoor ontstaat
ruimte voor andere
initiatieven, waardoor er
meer partijen gebruik
kunnen maken van het
net.
Counteren
Zonnepanelen worden
zo aangestuurd dat ze
op piekmomenten
(<10% van de tijd), als
het netwerk niet
voldoende capaciteit
heeft, geen elektriciteit
produceren. Als de zon
minder fel schijnt en er
wel ruimte is op het
netwerk (>90% van de
tijd) is er geen sprake
van beperkingen..
Groeps ATO
(ook wel Energyhub)
Een groep
aangeslotenen
poolt/aggregeert hun
individuele vermogens.
De dalen in het aldus
resterende patroon
kunnen worden benut
door bestaande en
nieuwe leden van de
groep zonder dat dit tot
extra druk op de
netcapaciteit leidt.
Batterijen
Gezien hun
karakteristieken zijn
batterijen technisch
uitstekend in staat om
extra aansluit- en
transportmogelijkheden
te creëren en schaarste
te bestrijden. De relatief
hoge kosten en het
verdienmodel staan
hieraan echter
momenteel in de weg.
Non-firm ATO
Een reguliere ATO
(Aansluit- en
Transportovereenkomst)
biedt altijd recht op
transport. Een Non-firm
ATO beperkt dit recht
doordat alleen in
bepaalde tijdvensters, of
als de netbeheerder
daadwerkelijk ruimte
heeft, aanspraak kan
worden gemaakt op
transportcapaciteit.

Alarmnumber shortened: 848 | Extern: 088-857 9112
Evacuation signal
Accident or First Aid
Activate fire alarm
Call 848
Leave the building
Call 848
Stay with the person
Wait for BHV
Leave the building
Go to the designated
assembly point.
Fire or explosion
13
Enexis: Predicting Future Network Congestion Arising from the Energy Transition using the
PowerGridModel

1
4
■ Kenneth Ruys
• Infiniot
• Software engineer & Technical team
lead (NeVo)
■ Joni Hermans
• Enexis
• Expert energy transition & Business
analist (NeVo)
Introduction
Enexis: Predicting Future Network Congestion Arising from the Energy Transition using the PowerGridModel

Predicting Future Network
Congestion Arising from the Energy
Transition using the PowerGridModel
Enexis Netbeheer – 7 Dec 2023

Agenda
1. Energy transition
○ Predicting the future?
○ Scenarios
2. Electricity network layout
3. Calculating the impact of the energy
transition on Enexis’ networks
○ How to model (future) network
loads?
○ Power grid model
○ Scalability
4. Network planning
○ Redundancy calculations
5. What's next?

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
17
Creating Prognosis for the energy transition

● Climate change
○ Electrification of fossil-based energy carriers
● More than 60 ‘drivers
○ Solar PV, electric vehicles, heat pumps, electrification of industry, etc…
○ Are installed behind different connection levels
● Municipalities create district plans
● National studies determine how the Dutch energy networks and energy mix
will look like in 2050 (II3050)
○ Various scenarios.
○ Enexis translates to her networks on a neighbourhood level.
Enexis: Predicting Future Network Congestion Arising from
the Energy Transition using the PowerGridModel
1
8
The energy transition

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
19
Creating Prognosis for the energy transition

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
20
Calculating the impact of the energy transition

● Four voltage levels
○ Transmission (TSO)
■ Extra high voltage (EHV)
■ High voltage (HV)
○ Distribution (DSO)
■ Medium voltage (MV)
■ Low voltage (LV)
Overview of the Dutch electricity network
PowerGridModel
21
Obtained from Phase to Phase – Netten voor distributie van elektriciteit

Schematic overview of a MV network
PowerGridModel
22

PowerGridModel
23
■
Impact of the energy transition on Enexis’ Grid
Power Grid Model network input
● Overview of all assets and their connection
● Nodes
● Cables
● Transformers & Loads (locations)
● Sources
● And more

PowerGridModel
24
● Different approaches to
determine current loads
○ Measured
○ Estimated
● Estimating loads
○ Realistic approximation of near
worst-case
○ Bottom-up
○ Monte Carlo
● Current loads are required to be
able to estimate future loads
How to model (future) network loads

PowerGridModel
25
(future) MV network loads
Define scenario
◆ Driver Prognosis
◆ Dispersion models
EV, PV en HP (connection
level)
Scenarios per driver
Base load Future load
◆ Stochastic (Monte-Carlo)
◆ Baseload profile based on
number of connections.
◆ Driver profiles based on
future adoptions
◆ New stochastic
simulation
Base load Future load
◆ Baseload based on real
customer connections
measurements
◆ Percentiles to create
‘representative’ days
◆ Aggregated driver loads
are added to the
measurements.

● 15–minute load profiles
○ Customer connections
○ Netstations
● Four scenarios
○ High demand / high generation
○ MV-Distribution network / MV-Transport network
● Driver profiles
○ Each driver has a unique profile
2
6
Enexis: Predicting Future Network Congestion
Arising from the Energy Transition using the
(future) MV network loads

PowerGridModel
27
Model impact ET on Enexis Grid
Scaling of (cloud) calculations
124 MV networks 2 seasons 2 levels 96 timestamps 28 years
 ~47.500 simulations per year.
 ~1.33m simulations for all networks during normal operation.
 ~250m simulations for a redundancy analysis.

PowerGridModel
28
● Cloud infrastructure
○ AWS
○ One cloud computer for each
network
○ Combine filtered results in
datawarehouse
● End users / applications have
views on the datawarehouse
Scaling of (cloud) calculations

PowerGridModel
29
• Power Grid Model
• Run locally
• Scalable
• Transparent / Open source
• Active development
Power Grid Model

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
30
Calculating the impact of the energy transition

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
31
Network planning

Network planning
During normal operations
● Loads per
transformer/station are
modelled.
○ ‘Current year’ up to 2050
○ 4 scenarios (high demand / high
generation)
● Resulting in:
○ Cable loading
○ Transformer loading
○ Node voltages
32

● The electricity grid must withstand
the total power during normal and
during N-1 operations
○ A cable failure / maintenance
● As the MV network is meshed a
new PF calculation is required
1. A cable is taken out of operations
2. A PF calculation is performed
3. The results are saved
4. The cable is put back into operation
● Simplifications to reduce number of
PFs
33
Network planning
During redundant operations

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
34
Network planning

● Municipalities.
● National
studies.
● Expertise.
● Industry.
Input
1
● Translate input
to development
on a
neighbourhood
level.
● Create
scenarios.
Prognosis
2
● Calculate the
impact of the
created
scenarios on
the network of
Enexis.
● Loading and
voltages.
● Normal and
redundant
operations.
Calculations
3
● Short term: can
new customers
be connected to
the network.
● Long term: are
the suggested
investments
adequate.
Network planning
4
● Automated
congestion
detection
● Network
architect create
an investment
plan.
● Operations
● Spatial
necessities
Investments
5
PowerGridModel
35
What’s next

● Investment
○ In which year does overload occur?
○ How large is the overloading?
○ Which investment is the best?
● For now, manual work; later, a
fully automated process.
● Discussion with municipalities
for the spatial necessities
○ How much kms of cables
○ How many new transformers
What happens with the results?
PowerGridModel
36
Current year
Current year

● More scenarios
● Automatic voltage regulators on HV/MV & MV/MV
transformers
● Short circuit calculations
37
What’s next?

Contact information
Kenneth Ruys / Joni Hermans
Enexis Netbeheer
Magistratenlaan 116,
5223 MB 's-Hertogenbosch
sds-enet@enexis.nl
www.enexis.nl
Questions?
You can always contact us later via e-mail.

Fairness-incorporated Online Feedback Optimization for
Real-time Distribution Grid Management
– 4th Power Grid Model Meet-up
07-DEC-2023
Sen Zhan, PhD student
Dept. of Electrical Engineering, Electrical Energy System (EES) group

Outline
4th Power Grid Model Meet-up
41
 Distribution grid issues
 Why online feedback optimization?
 Why fairness?
 Case study results
 Conclusion & discussion

Distribution grid issues
42
• Voltage limit violation
• Overloading of
transformers and cables

Moving from offline model-based to online
feedback optimization
• Precise distribution grid models not
always available
• Real-time load measurements not
available due to privacy
• Computationally challenging
• Lack robustness to inaccurate system
models and unknown disturbances
• From centralized to decentralized
43
Lukas Ortmann et al, arXiv, 2023

Optimization model
44
Original Saddle-point

45
Voltage sensitivity calculation

46
Saddle-point algorithm
5) Each bus carries out the following computation:
Emiliano Dall’Anese et al, TSG, 2018

Why fairness?
47

Case study
48
Non-controllable loads
Online feedback optimization
Measurements
Set-points of controllable DERs

Convergence static case
49

Fairness static case
50

Dynamic simulation
51

Dynamic results
52

Fairness dynamic case
53

Conclusion
• A methodology for real-time distribution grid management that is:
• Fast, decentralized and scalable
• Robust
• Fair
• Not taking load measurements
• Making full use of grid capacity
54

Discussion
• Communication infrastructure
• Fast DER actuation
• Hyperparameter tuning
• Real-time: heat pump
• Model-based sensitivity calculation
 data-driven
• First-order  second-order
55

Peter Salemink
● Development lead power-grid-model maintainers
● Scientific software engineer
● Background in Electrical Engineering

Project Governance by LF Energy
• Technical Steering Committee
- Tony Xiang (chair)
- Werner van Westering (power system consultant)
- Jonas van den Bogaard (open-source consultant)
- Peter Salemink (development lead)
• Maintainers
- Nitish Bharambe
- Martijn Govers
- Zhen Wang
- Jerry Guo
- Laurynas Jagutis
• Developers/Contributors

Community Driven Development Cycle
Half-year
Roadmap
Development
Community
Feedback
Meet-up
(today)

Highlights Q3/Q4 2023
● Short circuit calculations 1.5.x
● Serialization 1.6.x
● Disable sensors in state estimation
● SOGNO hackathon
● C++ 20
● Musllinux support (alpine based docker images)
● Improved documentation
● Feature improvements and bug fixes
● Internal refactor for automatic tap changer
● Ongoing automatic tap changer
● Ongoing Newton-Raphson state estimation

1 Million downloads reached
https://pepy.tech/project/power-grid-model
* Including automatic downloads like CI

Short circuit calculation
• Release 1.5.x
• Method equivalent to IEC60909
• Example:
- https://power-grid-model.readthedocs.io/en/stable/examples/Short%20Circuit%20Example.html

Serialization
• Release 1.6.x
• Load and dump PGM datasets from/to:
- JSON
- Msgpack
• Deprecated functions
- import_json_data
- export_json_data
• Example:
- https://power-grid-model.readthedocs.io/en/stable/examples/Serialization%20Example.html

Breaking change in C API (not in Python API)
• Introduction of dataset concept in C API
- No impact on Python API
- Breaking change for C API:
o Create
o Update
o Calculate1.6.x
• Example:
- https://github.com/PowerGridModel/power-grid-model/blob/main/power_grid_model_c_example/main.c

Disable sensors in state estimation

SOGNO hackathon
• Successful POC: PGM as service in SOGNO
platform
• RWTH Aachen University + PSI Energie EE
• PGM can be integrated in SOGNO

Workshop
• For new users!
• Webinar
• 18 Januari 2024, 14:00-17:00 (UTC +1)
• Webpage:
- https://community.linuxfoundation.org/events/details/lfhq-lf-energy-presents-power-grid-model-workshop/

Deprecation of Python versions
• Long term release strategy: 3 supported Python versions
- New Python version released in October -> drop oldest supported version in January
• Currently supported: Python >=3.8
• Accelerated deprecation in the coming 1.5 years:
deprecate 1 Python version after each meet-up
- January 2024 drop Python 3.8
- July 2024 drop Python 3.9 (extra deprecation)
- …

Features/Improvements Requests
• Mentimeter

Community Decisions
• Supported Linux Distribution
- Current: manylinux_2_24
- Proposal: manylinux_2_28
- Affected well-known Linux distros:
o Debian 9 (EOL 05-07-2020)
o Ubuntu 18.04 (EOL 30-04-2023)
o Amazon Linux 2 (EOL 30-06-2025)
(This includes AWS hosted development platform such as AppStream)
• See also:
- https://github.com/mayeut/pep600_compliance

Data science analysis toolkit
● Jaap Schouten
● Thijs Baaijen

Closing
• Our Goal: Community-driven Ecosystem
• Think Big!
- Working Groups
- Hackathons
- Brainstorms
- Tutorials/Workshops
- ConsultancyWebinar

Communications
• Mailing List (Announcement)
- https://lists.lfenergy.org/g/powergridmodel
• Road Map
- https://github.com/orgs/PowerGridModel/projects/1
• Issues and Discussion
- https://github.com/orgs/PowerGridModel/discussions
- Post issues in relevant repository

Ways of Contribution
● Good First Issues
- https://github.com/orgs/PowerGridModel/projects/1/views/5
Use the Library Give Feedback & Report Bugs
Improve C++ Core
(New Algorithms and Models)
Improve Python API
Provide Validation Test Cases

LF Energy Power Grid Model Meetup December 2023

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