1. Koen Vanthournout, VITO (Flemish Institute for Technological Research)
Jan Van Ooteghem, Ghent University / iMinds

2. LINEAR
“Local Intelligent Networks and Energy Active Regions”
1. Flemish Government decision
„dd. 8 mei 2009 VR 2009 0805 DOC.0671‟
2. Official start: May 2009. Project runs until December 2014.
3. Total budget of 40M€:
– Flemish government: 10M€
– Industry: 30M€ (personnel, hardware, ...)
www.linear-smartgrid.be
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3. Linear situated
• Increased share of intermittent renewables
• Electrification of transport and heating
• Stabilization/decrease classical production portfolio
⇒ Energy excesses and shortages
⇒ Grid capacity issues
Classical control paradigm
“production follows consumption”
no longer holds
⇒ storage
⇒ “consumption follows production” (i.e., demand response)
Linear focuses on
Residential Demand Response
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4. Partners
Research Partners
Flemish Government
Industrial Partners
Additional Members
Steering Committee
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5. Core: large scale residential DR pilot
Residential demand response with as little
impact on the user comfort as possible
1. Focus on automated ‘smart’ devices.
2. Keep technical targets and BCs hidden
for the user.
3. Keep interaction simple and stimulate
good behavior financially.
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6. Linear Smart Devices
• Washing machines
• Dishwashers
• Tumble dryers
• Electric hot water buffers
• (Electrical vehicles)
• (Heat pumps)
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7. Linear Control architecture
Transformer Linear Historic
measurements Server BC data
• One business case at the time
• # aggregators with # control
technology
• Generic interfaces for smart devices
Server
… • P1 smart meter interface definition
Fifthplay • Interface definition between
aggregator and user flexibility
INTERNET GW GW GW GW GW Integration tests in lab ongoing,
HOME
tests started at friendly users
Smart Touch Energy Plugs Miele VITO DHW VITO Smart
Meter Display meas. Network GW buffer controller plug
Miele Miele Miele BSH BSH
wash. tumble dish wash dish EV
machine dryer washer mach washer
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8. 250 participating families
3 groups Friendly users Geographically Geographically
dispersed concentrated
Focus Technical testing BRP cases DSO cases, link with smart
meter projects
Target 30 100 120
Contract signed 33 81 13
Smart devices 25 203 25
installed
Status Integration tests • Installed Recruitment and
started • Reference installation ongoing in
measurements ongoing Hombeek& Leest (Eandis)
• 15 HP owners in
and Genk (Infrax)
recruitment pipeline
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9. Linear Business Cases
Use DEMAND RESPONSE for:
1. Portfolio Management BRP/Retailer
 Shift consumption in function of the day ahead market (corrected for 2020
production mix)
2. (Wind) Intraday balancing BRP/Retailer
 Shift consumption in function of the quarter hour unbalance of a BRP portfolio
3. Transformer aging DSO
 Shift consumption to avoid accelerated aging due to high transformer
temperatures
4. Voltage control for LV distribution feeders DSO
 Shift consumption based on local voltage measurements to ameliorate voltage line
deviation
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10. Linear - business cases
LV transformer load
Peakload
Future distribution grid:
• More residential consumption
=> higher offtake peaks on LV transformers
P
•
1
More intermittent (renewable) generation Peakloadre
duction due
=> injection peaks on LV transformers to DR
P
Aging of transformer will be accelerated during 2
these peak periods (increase of temperature) t1 Deferrel of t2
Investment
If DSOs succeed in controlling temperature of LV transformer, Lifetime
they are able to allow a higher share of local generation and
extra demand without the need for new network investments
Objective: control the temperature on a transformer by the application of
automated active demand to defer/decrease network (transformer) investments
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11. Linear - business cases
LV feeder voltage profile
Future distribution grid:
• More residential consumption
=> voltage drops in feeders
• More intermittent (renewable) generation
=> voltage increases in feeders
Predictability of the voltage profile of a feeder
decreases
Situations can occur where the voltage levels
Voltage profile with and without DG
either become too high or too low (Source: EELAB)
Objective: keep the voltage profile of the different LV lines within permitted limits
by the application of automated AD (no coordinated local control at household
level) to defer/decrease network (new lines / transformers) investments
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12. Linear - business cases
Dynamic Energy component
Portfolio management Distribution fee
Fixed Transmission fee
Dynamic tariffs can be used to Charges
incentivize consumers to reschedule
their consumption
Tariffs used:
• 6 time blocks a day
• Based on Belpex DAM +
prediction sun/wind (scenario
2020)
• Communicated DA for the
next day
Objective: coincide as much as possible periods with low generation costs (based
on high availability of renewable generation by wind and/or sun) with
consumption by applying dynamic tariffs to residential consumers
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13. Linear - business cases
Wind balancing
• BRP = responsible for the balance of
injection + offtake in their perimeter on a
quarter-hourly basis
• TSO manages the instantaneous imbalances
(that the BRPs are not able to control), by
making use of power reserves
Costs involved for making use of power
reserves are transferred to the BRPs Balancing mechanism
(Source: Elia)
BRP with wind production in its portfolio:
higher imbalance risk + higher imbalance
cost
Objective: decrease the imbalance cost of the BRP by decreasing the unpredicted
imbalance caused by wind production (intraday) in its portfolio by aggregating
flexibility available at residential consumers’ premises (flexible cluster)
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14. Linear - business cases
Control mechanism
DSO BRP/retailer
LV Dynamic tariffs
Portfolio
Automated transformer
management
active demand load
LV feeder
Wind
voltage
balancing
profile
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15. Questions?
Koen Vanthournout, VITO (Flemish Institute for Technological Research)
Jan Van Ooteghem, Ghent University / iMinds