flex-offers: unified handling of flexibility in...
TRANSCRIPT
Aalborg University, Denmark
Nov 4, 2016
Flex-Offers: Unified handling ofFlexibility in Electricity Consumption
and Production
Laurynas Šikš[email protected]
THE FLEX-OFFER CONCEPT
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Flexible Offer (flex-offer) allows unified modelling of a flexibleconsumer/producer in ALL these cases
Flexible Electricity Consumers and Producers
•No flexibility •Time-shift flexibility •Time-shift flexibility•Amount flexibility• [Total Amount requirement]
•Amount flexibility withintra-time unitdependencies
Earliest starttime
Latest endtime
totalMinEnergy ≤ ≤ totalMaxEnergy
Time
kW
Hour 1 2 3 4
No or simple flexibility patterns Complex flexibility patterns
Previously usedenergy is high
Previously usedenergy is low
Slide 3
TBP1 all the examples are from households, perhaps you could add a few for the industrial/commercial cases we have eg in ArrowheadTorben Bach Pedersen; 1.11.2016
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Flex-Offer Aggregation and Disaggregation
DisaggregationAggregation Scheduling
Aggregation
Prosumer flex-offers
Disaggregation
Scheduled prosumer flex-offers
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(Simple or Aggregated) Flex-Offer Lifecycle
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(Simple or Aggregated) Flex-Offer Lifecycle
Time
kW
09:00 09:15 09:30 09:45 10:00 10:15 10:30 10:45 11:00
10
20
30
Start time
v1
v2
v3
v4
(One feasible)Flex-Offer Schedule
Generate ON/OFF signals tofulfil the schedule
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(Simple or Aggregated) Flex-Offer Lifecycle
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Summary
ØFLEX-OFFERS: A POWERFUL CONCEPT APPLICABLE IN MANYSMART-GRID APPLICATIONS:
• Demand supply balancing• Electricity trading• Congestion management• …
USING FLEX-OFFERS BOTH FORELECTRICITY AND DISTRICT HEATING
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Flex-Offers for electricity and heating
ØOBSERVATION 1: kW and kWh can be used for both electrical andthermal energy, and so can Flex-OffersØOBSERVATION 2: Flex-Offers for different types of energy should be
treated separatelyØOBSERVATION 3: For interplay, energy conversion needs to be
modelled as a flex-offer
E.g., A house heated with a heat-pump and comfort constraints
Temperature x(t),
Heater power u(t),
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Example of modelling energy conversion
Constraints on input and state
R – thermal resistance (oC/kW);C – thermal capacitance (kWh/ oC);h – coefficient of performanceqa – ambient temperature (oC)qr – required temperature (oC)d – user temperature band (oC)
1. Linear Time Invariant State Space Model
Earliest start Latest end
kW
1 2 3
6.5
0
3. FO with EnergyFlexibility
2. Exact polyhedrons 4. FO with Energy Flexibilityand Dependencies
kW
1 2 3
8
0Earliest start Latest end
= 1. .
FLEX-OFFER RELATED PROJECTS ANDMAJOR ACHIEVEMENTS
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Related Projects/Initiatives
www.mirabel-project.euwww.totalflex.dk
www.arrowhead.eu
2010-2013
• Scalable ICT system for:• Higher RES integration• Demand-supply balancing• Flex-offer management
• Develops and demonstratesa market-based system for
flexibility trading andcongestion
management
2012-2016 2013-2017
• Largest European auto-mation project of all time
• Collaborative automationand interoperability ofnetworked devices in (1)production, (2) end-userservices, (3) smart buildingsand infrastructure, (4)
electro-mobility, and (5)markets of energy.
2016-
• Will integrate,and demonstrate a group of
smart-grid technologies for thecost effective use of demandresponse in distribution grids
2015-2021
• Research on how to utilizesoftware and data for smartersolutions in heath, traffic,energy, and communityservice domains
Flex-Offers
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Major results: Hierarchical ICT infrastructure
ØFlexible demand and supply can lead to 7-13% cost reduction for BRPs.ØFlexible demand and supply improves RES integration significantly: 70% of the
negative impact of fluctuating renewables can be neutralized if 15% of the energyconsumption is flexible and intelligently controlled by the BRP.ØHouseholds can reduce energy bills by 10-20%
(BRPs)
measurementsflex-offers
prices
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Major results: Flex-Offer Aggregation
f1
f2
f3
f4
f5
Omitted as it does not satisfies the
G1
G2Grouping
f1
f3
f2
f4
f5
Groupingparameter
s
Bin-packing
G1
G21
f1
f3
f2
f4
f5
G22
bin-packing constraints
Bin-packingparameters
N-to-1aggregation
F1
F2
Aggregationparameters
For all forms of flex-offers, a number of flex-offer (dis-)aggregation techniques were developed: simple,incremental, with bin-packing, with balancing.
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Major results: Flex-Offer Aggregation
ØMillions of flex-offers can be aggregated anddisaggregated in seconds
ØAggregation+Scheduling+Disaggregation is BETTERAND FASTER than just Scheduling
ØAggregated flex-offers of the desired form can begenerated:
• “More flexibility NOW”• “More flexibility LATER”• “Keep balance conditions”
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Major results: Flex-Offer Market
ØPERFORMED AN ANALYTICAL AND EXPERIMENTAL VALIDATION OFFLEXIBILITY IN THE DANISH REGULATION AND SPOT MARKETS:• On average, 50% of the energy demand from a
household is flexible.• BRPs/Aggregators can achieve 49% reduction in the
regulation cost with just 3.5% of energy demandbeing flexible
ØCONSIDERED FLEXIBILITY PRICING AND DEVELOPED AMARKET FOR FLEXIBILITY (FLEX-OFFERS)
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Major results: Flex-Offer Market
ØDEFAULT SCHEDULE AND PRICES FOR DKWH:
Time interval 11:00-11:15
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Major results: Flex-Offer Market
ØFLEXIBILITY TRADING: 11:00-11:15
DSO
Existing electricity markets
Market Place forflexibility
flex-offer
TVPP
Electricitycompany Aggregator
CVPP
BRP
Buying flex-offer
Selling flex-offer
Flexible Resources
Buying flex-offer
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Summary
ØFLEX-OFFERS• Powerful concept for unified modelling of flexibility• Suitable for negotiation, planning/trading, control, and billing• Validated in a number of Danish and EU projects
ØKEY REFERENCES• Matthias Böhm, Lars Dannecker, Andreas Doms, Erik Dovgan, Bogdan Filipic, Ulrike Fischer,
Wolfgang Lehner, Torben Bach Pedersen, Yoann Pitarch, Laurynas Siksnys, Tea Tusar: Datamanagement in the MIRABEL smart grid system. EDBT/ICDT Workshops 2012: 95-102
• Luis Lino Ferreira, Laurynas Siksnys, Per Pedersen, Petr Stluka, Christos Chrysoulas, Thibaut Le Guilly,Michele Albano, Arne Skou, César Teixeira, Torben Bach Pedersen: Arrowhead compliant virtualmarket of energy. ETFA 2014: 1-8
• Laurynas Siksnys, Emmanouil Valsomatzis, Katja Hose, Torben Bach Pedersen: Aggregating andDisaggregating Flexibility Objects. IEEE Trans. Knowl. Data Eng. 27(11): 2893-2906 (2015)
• Laurynas Siksnys, Torben Bach Pedersen: Dependency-based FlexOffers: scalable management offlexible loads with dependencies. e-Energy 2016: 11:1-11:13
THANK YOU!
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Background
ØRENEWABLE ENERGY IS CHALLENGING:
ØSOLUTION: MAKE DEMAND AND SUPPLY FLEXIBLE
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Use-case Example1. A consumer arrives home at 10pm and wants to rechange
the electric vehicle‘s battery at the lowest possible price bythe next morning
2. The consumer‘s LEDBMS generates a FO:
3. A negotiation with the BRP/aggregator is started:
4. The consumer is rewarded for its offered flexibility
kW
t
10 pmEarliest Start Time
6 amLatest Start
Time
8 amLatest End
Time
2h
Profile
Time Flexibility Interval
3 amStart Time
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Major results: Flex-Offer Aggregation
Time
Amount/Dt
f1
Time
Amount/Dt
f2
Time
Amount/Dt
Sf1
Sf2
Sf3
f3
Time
Amount/Dt
fA
tes =min (sf1,sf1,sf1)
tf(fA)=1
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Prosumers(millions)
Aggregators(thousands)
TSOs(few)
FlexOffer Management Platform
FlexOffers
Schedules
Marketbids
Markets(few)
DSOs(hundreds)
Techniques for flexibility extraction from the smart-metermeasurements
Techniques for flexibility detection and extraction at theappliance levels
• Scalable techniques for aggregating FlexOffers anddisaggregating FlexOffer schedules
• Techniques for balancing energy and avoiding gridcongestions during FlexOffer aggregation
AggregatedFlexOffers
AggregatedFlexOffers
DisaggregatedSchedules
DisaggregatedSchedules
• Cost-effective FlexOffer scheduling techniques for energybalancing
• Integrated system for FlexOffer data prescriptive analyticsand management
• Algorithms for predicting grid congestions
• Flexibility market approach• Evaluation of flexibility value in energy regulation
markets
• Service-oriented pilotdemonstration
www.arrowhead.eu