STORY - A vision of our future energy system

1. STORY – A vision of our future energy system
Webinar - How microgrids help optimize local energy storage
20.16.18

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Why do we talk about microgrids
Did you know it’s a trend ?
blockchain
https://www.h2020-bridge.eu/

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Microgrids
Simple illustration for today
Residential Industrial

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The main challenge in microgrids
• Technical & economical
– Flexible Devices
• Integrate user-specific preferences
– Metering elements
• Low cost
• Interoperability
– Connectivity
• Low energy consumption
– Modeling
• individual modelling is a challenge (heterogeneous appliances)
– Control Objective
• Local vs System-level services
• Regulatory
– Regulation rules may ban microgrids or lead to prohibitive costs
– Belgium : changes are being implemented (as in FR, DE,…)
A few challenges to be tackled

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Project STORY E-Cloud GAC
Residential X - X
Industrial - X -
Local Energy (RES) X X X
Battery Storage (non-EV) X - TBD
First results (20.06.18) X X -
Dynamic Pricing X TBD
Energy Allocation
Mechanism
- X TBD
Active Grid Management - X X
Story, E-cloud & GAC
Comparison of project scopes

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Agenda
• Introduction
• Story - Project overview (Actility)
• Story - Oud-Heverlee Belgium Demo (Actility)
– Results from Story Belgian Business case
– Residential street-level optimization case
• E-Cloud (ORES)
– E-cloud : Industrial microgrid
• GAC (Greenwatch)
– GAC : Residential microgrid
• Q&A
Overview of today’s discussions

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Story
• What happens if a
– Large amount of
– Small-scale storage is
– Integrated into the distribution grid
The core question of the story project

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Story - Horizon 2020 Framework
• STORY team
– 18 institutions
– 8 countries
– Use of storage, Residential & Industrial level
Overview

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Story - Horizon 2020 Framework
18 Institutions

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Story - Horizon 2020 Framework
The scope of our contribution
• Actility’s contribution
– Centralized optimization of energy use within a residential
microgrid
• Connection + equipment of a dozen houses
• Optimization of flexible appliances
• Poll 1
– What’s the key objective of Residential microgrid ?

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Story - Horizon 2020 Framework
Actility – Demand Response Aggregator : who we are

13. Stage 1
• Story – OHL Demo

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Story OHL Demo
Partners in lead for this demonstration
*The living Lab
*

15. The Story Project – OHL Demo
Geographical situation
15
*The living Lab(source : Google)
*

16. The Story Project – OHL Demo
Connecting a Microgrid
16
(source : Google)
Challenge #3 – Connect
• LoRaWan for Meas. & control
• Detailed measurements are
sent via IP due to data rate
limitation (IoT)
Challenge #1 – Flexible Devices
• Multi-vendor Heating Appliances
• Batteries (installed by Story)
• Multi-vendor EVs
Challenge #2 – Measure
• Electric Consumption
• States (Temperature, On/Off)
Challenge #4 – Control
• Model House & Heating appliances

17. The Story Project – OHL Demo
Lessons learned from installations
17
Fuses location is
unkown
Phases can be
swapped between
Main fuse box & e.g.,
Ground fuse box
Houses are living things.
The installation can
change due to other
providers intervention
Connectivity can be
limited in countryside

18. Story OHL Demo
Two Case Studies
Building scope Neighborhood scope

19. Story OHL Demo
Case Study 1 : Building level optimization
Building scope • Overall MPC* framework
• Simulation Results
• Real-Life Results
*Model Predictive Control

20. Control of Consumption - MPC
Model Predictive Control & Use cases Case 1 : Dynamic pricing
Case 2 : Minimize grid exchange

21. Control of Consumption – Simulation
Results
Appliance annual energy
cost decrease of about 10%
to 20%
Case 2 : Minimize grid exchange
Case 1 : Dynamic pricing App 1 App 2 App 3 App 4 App 1 App 2 App 3 App 4 App 1 App 2 App 3 App 4
House 1 House 1
Maximum Injection levels are
drastically reduced (even
without battery)
Dynamic pricing likely to increase
maximum offtake & injection
1
2

22. Model & connectivity example
Boiler
Temperature
Power consumption
Control
3 Temperature sensors Communication Optimisation & control
Boiler Energy State
Boiler model

23. Real life result (1/2)
Boiler
Bottom Temp
Top Temperature
Energy Content
(dotted : model)
User behaviour influences massively the boiler states
Water withdrawal have
a stochastic nature

24. Real life result (1/2)
Boiler
Energy price
State
Energy is consumed during low price period
Power
𝟓𝟎𝟎𝒌𝑾
~𝟖𝟑 €/𝑴𝑾𝒉
~𝟑𝟑 €/𝑴𝑾𝒉
Energy price

25. Real life result (2/2)
Building 1 : Direct HP power control (Gear control)
-> Thermal inertia is large due to floor heating but introduces delays
-> Interactions with domestic hot water production not easily handled

26. Real life result (2/2)
Uncontrolled Controlled
Building 2 : Indirect power control via Thermostat (Temperature set-point)
-> Much more difficult than direct control
-> Set-point follows a much more variable pattern when externally controlled
Uncontrolled case : large amount of energy at peak
Controlled case – in case energy is
required at peak, the algorithm limits it
as much as possible (short start)
Controlled case – at first, the model
underestimates thermal inertia

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Conclusions
• A house is complex
– Inter-operability is a challenge
– Home are living thing (promote self installation ?)
– Neighborhood : phase identification is needed (coordination)
• Control Results
– Positive results in Simulation
• Case 1 : 10-20 % appliance energy cost reduction in Dynamic Pricing,
leading to larger demand peaks or injection levels.
• Case 2 : Injection can be reduced to a higher extend than offtake
– Results Confirmed in real-life control
• Further assessment is undergoing
– Model Calibration (thermal inertia) is key (machine learning ?)
What we take home in this first part of the Demo

28. Stage 2
• E-cloud - ORES

29. Project E-Cloud :
20-06-18
“This research has been supported by the Public service of Wallonia within
the framework of the E-Cloud project”
29

30. Agenda
• Microgrids
• General concept
• Key characteristics
• How does it work?
• Conclusion
30

31. Vangulick – BE – S6 - 0221
Some of you may think: Microgrids are the Armageddon of the
DSO’s world
Microgrids

32. Vangulick – BE – S6 - 0221
• The central ideas are
– Generation units are made available to a community
of industrial customers
– Local generation that is consumed locally is
considered as auto-consumption
– Energy that is not produced locally enters the
classical market processes. Customers still have their
freedom of negotiation for this part.
– The storage of electrical energy could help to
increase the consumption of local generation within
the E-Cloud
E-Cloud: General concept

33. Vangulick – BE – S6 - 0221
• The E-Cloud is
– an electrical system not separated from the conventional network
– integrating consumers and local generation units aimed at
optimizing energy flows,
– optimizing for both consumers and producers and for the
Community
– this optimum, which varies in a quarter of an hour, requires to
• Combine implementation of information technology and smart grid
• Customer’s willingness to participate in this process and,
• Educate them to better understand their own consumption
E-Cloud: Key characteristics

34. Vangulick – BE – S6 - 0221
E-Cloud: How does it work ?
Total
Generation
(/1/4h)
Allocation
key
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p
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y
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35. Vangulick – BE – S6 - 0221
E-Cloud: How does it work ?
DSO ADT(*) Factory A
SME B
Producer
SME C
(*) ADT= Agence de Développement Territorial : Agency rresponsible for the
implementation, promotion and management of business park (Zone Activité
Economique (ZAE))
E-Cloud: Participation Agreement
• Factory A:
• Production part : 40%
• Rental to pay to producer:
40000€/year
• SME B:
• Production part : 35%
• Rental to pay to producer:
35000€/year
• SME C:
• Production part : 25%
• Rental to pay to producer:
25000€/year
• Producer
• Install 1 MW wind turbine & 250
kW PV

36. Vangulick – BE – S6 - 0221
All customers keep their right to negotiate for their non locally
produced energy
E-Cloud: How does it work ?
SME B
SME C
Facory A
Supplier
Zeta
Supplier
Zeta
Supplier
Omega

37. Vangulick – BE – S6 - 0221
• In each of the factories / SMEs, a (new) role is created: the Energy
Manager
– Played by the customer’ staff or by supplier or by third party
– Receives forecasts of its share of generation & its consumption for
the next day (provided by the DSO)
– can adapt his consumption planning
– During the day, can verify its share of generation meet its actual
consumption (provided by the DSO). It can try to maximize the use of
the local generation
E-Cloud: How does it work ?
Active –consumers (Consom-Acteur)
New Work
planning

38. Vangulick – BE – S6 - 0221
• Customer recruitment
– ZAE Tournai :45 Customers = 14 Recruited !
– ZAE Sart-Tilman: Info session done
• Optimization
– Design on going (result begin of June)
– Target performance: 10% decreasing of the energy
bills
• Regulation issues
– Possibility for a demonstrator to have special market
rules: ok Regulator agreed
– In line with « Winter Package » (Energy community)
Conclusion
Where are we so far ?

39. Vangulick – BE – S6 - 0221
Planning

40. Vangulick – BE – S6 - 0221
• We do believe that E-Cloud is a 4 « win »:
– Win for businesses, which increase their competitiveness.
– Win for all network users because the E-Cloud relieves
network constraints and, potentially, the investment needs
and operational costs for the DSO.
– Win for the Walloon region, which facilitates the
achievement of renewable production and
competitiveness targets.
– Win for producers, who can install generation capacities
in areas less sensitive to NIMBY.
Conclusion

41. Stage 3
• GAC Project - GreenWatch

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• PV monitoring of 6.000 residential clients
• Multi-energy monitoring
• After-sale service
• Experience since 2009
• Offer and demand flexibility
• Remote load optimization

43. Control of PV
inverters
PV predictions
GATEWAY
Control of
residential loads
ICT platform
• Evaluation, prediction,
activation and monitoring
of demand flexibility
• Market interaction• Monitoring
• Smart load control
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Offer and demand
flexibility

44. • Neighborhood with 50 houses controled
• DSO is partner of the project
• Preliminary results (+10 years)
Increase in self-consumption
✓ Neighbordhood : 53 % → 74 %
✓ Individual : 39 % → 48 %
Decrease in consumption peaks
(individual and neighborhood)
Project implementation
Without
GAC
With
GAC
39 48
14
26
48
26
0%
20%
40%
60%
80%
100%
Self-consumption (+10 years
situation)
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45. • White goods
• Electrical boiler
• Electrical heater
• Heat pumps
• Batteries?
• Electric cars
Sensors
Loads
Gateway
GAC
platform
Z-Wave 4G
Control of the loads
Market
actors
Internet
• GWio
• Control of smart
plugs, smart
relays and
specific
interfaces
• Aggregation
• Monitoring
• Optimization
• Tariff
incentives
• Flexibility
• Facilitation of
flexibility
activation
• Flexibility
demands
• Congestion checks
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kWh/kW
Regular day consumption without GAC – PV
production
Valorization of flexibility:
Individual: prosumers
• Self-consumption optimization
Collective: neighbordhood
• Self-consumption optimization
Offer and demand flexibility
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47. Valorization of flexibility:
Individual: prosumers
• Self-consumption optimization
Collective: neighbordhood
• Self-consumption optimization
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Offer and demand flexibility

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kWh
Regular day consumption – without GAC –
BelPex price
€ 0
€ 10
€ 20
€ 30
€ 40
€ 50
€ 60
€ 70
€ 80
€ 90
Valorization of flexibility:
Individual : tariff incentives
• Dynamic pricing
• Peak pricing
• Pricing periods
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Offer and demand flexibility

49. Valorization of flexibility:
Individual: tariff incentives
• Dynamic pricing
• Peak pricing
• Pricing periods
Collective: neighbordhood
• Flexibility to the DSO
• Flexibility market
lia
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ser
seri
Transfo
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Offer and demand flexibility

50. What are we looking for?
• Additional services we could include in our offer
• Centralised and decentralised batteries, blockchain
• Additional playgrounds to test our solutions & more
• ERA-NET project, H2020, …
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51. Final Stage
• Q&A

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THANK YOU!