energy storage and demand side management
DESCRIPTION
David MacLeman – SSEPD Nathan Coote – SSEPD Mark Stannard – SSEPD Matthieu Michel – UKPN Alistair Steele - SSEPD. Energy Storage and Demand Side Management. What are we really trying to do with Energy Storage?. Energy storage continuum. Enhanced Demand side Management. - PowerPoint PPT PresentationTRANSCRIPT
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David MacLeman – SSEPD
Nathan Coote – SSEPD
Mark Stannard – SSEPD
Matthieu Michel – UKPN
Alistair Steele - SSEPD
Energy Storage and Demand Side Management
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What are we really trying to do with Energy Storage?
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Energy storage continuum
Demand Side Response
Fuel Manufacture
Sabatier process (Methane)Electrolysis (Hydrogen)Haber Process (Ammonia)Inter sector energy exchange...
Bi-directional storage
BatteriesFlow BatteriesThermal conversionPump storageFlywheels......
Enhanced Demand side Management
Small scale thermal MassManufacture process managementDistrict Heating......
DomesticCommercialIndustrialNew entries (cars).......
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Nathan Coote
Trial evaluation of domestic demand side management
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Scope
Project overview
Success criteria
Functionality
Outcomes and learning
Conclusions and future work
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Project Overview
Dimplex prototype devices installed during the SSET1003 trial
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Success CriteriaThe project success criteria will be to prove the
integration of the technologies and provide knowledge
and lessons learned for the NINES project and other
DNO projects.
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Functionality
Frequency response of Smart Loads
0%
20%
40%
60%
80%
100%
120%
4949
.149
.249
.349
.449
.549
.649
.749
.849
.9 5050
.150
.250
.350
.450
.550
.650
.750
.850
.9 51
Frequency [Hz]
Rate
d Po
wer
[%]
Smart load 50% gradient with 50%load at 50Hz
Smart load 25% gradient with 43%load at 50Hz
Smart load 200% gradient with 43%load at 50Hz
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Trial Participant Recruitment
Six homes identified
Personal visit to explain project
£100 ex-gratia payment
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Prototype Demonstration
(relevant environment)
System Validation
(operational environment)
Testing9
8
7
6
5
4
3
2
1
Proven Technology
Demonstration
Applied R&D
Research
Technology Readiness Level (TRL)
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ESRU
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Outcomes and key learningDevelopment of a DDSM heating system
Hot Water Cylinder
Main Design Features:
Class leading insulation
Three core elements providing variable power input
Increased storage capacity
Energy Storage Capacity:
Maximum Storage Capacity (10-80 oC)
175 l 14.0 kWh
215 l 17.1 kWh
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Outcomes and key learningDevelopment of a DDSM heating system
Storage Heaters
Main Design Features:
Highly insulated storage core
Three core elements providing variable power input
Electronic controller
Energy Storage Capacity:
Maximum Storage Capacity
P100 12.1 kWh
P125 14.9 kWh
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Outcomes and key learningDevelopment of a DDSM heating system
New switching strategy
Requirements for a communications solution
Hot water cylinder temperature measurement
Wireless solution
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Outcomes and key learningOther learning outcomes
Resource requirements
Understanding of customer perceptions
Skills development and safe working procedures
Input to further academic work on modelling household energy use to forecast customer demand
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Conclusions and future work
The trial has demonstrated the functionality of a DDSM system and
provided an initial indication of the network and customer benefits.
The next step required for progression towards Business As Usual (BAU)
deployment is to trial dynamic scheduling and control.
A large-scale roll out to 750 homes in Shetland through SHEPD’s NINES
project will enable this.
Allow SHEPD to determine the value of DDSM to DNO’s.
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Mark Stannard
Honeywell Automated Demand Response
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Overview
• Pilot demonstration of Honeywell's Automated Demand Response (ADR)
solution
– Enable DNO to reduce non-domestic demand at strategic points on the network
– Load shed triggered via signal to existing building management systems
• Benefits
– Match electrical distribution needs to changing customer demand profiles
– Provide visibility of customer usage
– Re-engage with customers to enhance future planning
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Trialling method
• Deployed at 3 customer sites:
– Bracknell & Wokingham College
– Bracknell Forest Council
– Honeywell House
• Sites: >200kW use, DR programming change to BMS, individual load
shed event participation or opt out
• Test capability of ADR to:
– Produce an aggregated figure of despatchable demand
– Reduce/shift peak loads
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Trial load shed event – single site
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Aggregated load shed eventSite Average kW shed
Honeywell House 70 kW
Bracknell & Wokingham College 56 kW
Bracknell Forest Council 11 kW
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Aggregated load shed eventHoneywell House 75 kW
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Aggregated load shed eventBracknell & Wokingham College 81 kW
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Aggregated load shed eventBracknell Forest Council 11 kW
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Using the information regarding the steps and time taken to acquire
customers we have calculated the cost it took to get to sign up
stage
Although a limited sample, it provides a valid indicative cost to a
DNO associated with recruitment for this type and scale of trial.
Customer Engagement Framework
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Customer Engagement FrameworkBuilding (company)
kW Shed Cost to DNOCost per MW load
shed (£k)
Bracknell & Wokingham College 56 798 14.250
Bracknell Forest Council 11 436 39.636
Honeywell 70 206 2.943
Overall 137 1440 10.511
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• Modelling was performed to extrapolate results in more detail.
• Began to understand how
ADR can improve network
observability on the distribution
network
Value to a DNO
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• Capable of shedding load in commercial properties by
communicating with the existing BMS
• Load shed can be triggered simultaneously to perform an
aggregated load shed
• maximum aggregated load shed of 137kW
• Streamlined Customer Engagement is Key
Conclusions/ Next Steps