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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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Presentation on theme: "David MacLeman – SSEPD Nathan Coote – SSEPD Mark Stannard – SSEPD Matthieu Michel – UKPN Alistair Steele - SSEPD Energy Storage and Demand Side Management."— Presentation transcript:

1 David MacLeman – SSEPD Nathan Coote – SSEPD Mark Stannard – SSEPD Matthieu Michel – UKPN Alistair Steele - SSEPD Energy Storage and Demand Side Management

2 What are we really trying to do with Energy Storage? Balance generation and demand locally and nationally Keep the lights on Manage energy flow within a network constraints

3 Energy storage continuum Demand Side Response Fuel Manufacture Sabatier process (Methane) Electrolysis (Hydrogen) Haber Process (Ammonia) Inter sector energy exchange... Bi-directional storage Batteries Flow Batteries Thermal conversion Pump storage Flywheels...... Enhanced Demand side Management Small scale thermal Mass Manufacture process management District Heating...... Domestic Commercial Industrial New entries (cars).......

4 Nathan Coote Trial evaluation of domestic demand side management

5 Scope  Project overview  Success criteria  Functionality  Outcomes and learning  Conclusions and future work

6 Project Overview Dimplex prototype devices installed during the SSET1003 trial

7 Success Criteria The 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.

8 Functionality

9 Trial Participant Recruitment  Six homes identified  Personal visit to explain project  £100 ex-gratia payment

10 Prototype Demonstration (relevant environment) System Validation (operational environment) Testing 987654321987654321 Proven Technology Demonstration Applied R&D Research Technology Readiness Level (TRL) }}}}}}}}

11 ESRU

12 Outcomes and key learning Development 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 o C) 175 l14.0 kWh 215 l17.1 kWh

13 Outcomes and key learning Development 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 P10012.1 kWh P12514.9 kWh

14 Outcomes and key learning Development of a DDSM heating system  New switching strategy  Requirements for a communications solution  Hot water cylinder temperature measurement  Wireless solution

15 Outcomes and key learning Other 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

16 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.

17 Mark Stannard Honeywell Automated Demand Response

18 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

19 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

20

21 Trial load shed event – single site

22 Aggregated load shed event SiteAverage kW shed Honeywell House70 kW Bracknell & Wokingham College56 kW Bracknell Forest Council11 kW

23 Aggregated load shed event Honeywell House75 kW

24 Aggregated load shed event Bracknell & Wokingham College81 kW

25 Aggregated load shed event Bracknell Forest Council11 kW

26  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

27 Building (company) kW ShedCost to DNO Cost per MW load shed (£k) Bracknell & Wokingham College5679814.250 Bracknell Forest Council1143639.636 Honeywell702062.943 Overall137144010.511

28 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

29 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


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