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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. What are we really trying to do with Energy Storage?. Energy storage continuum. Enhanced Demand side Management.
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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
Energy storage continuum Enhanced Demand side Management Demand Side Response Bi-directional storage Fuel Manufacture Domestic Commercial Industrial New entries (cars)....... Small scale thermal Mass Manufacture process management District Heating...... Batteries Flow Batteries Thermal conversion Pump storage Flywheels...... Sabatier process (Methane) Electrolysis (Hydrogen) Haber Process (Ammonia) Inter sector energy exchange...
Nathan Coote Trial evaluation of domestic demand side management
Scope • Project overview • Success criteria • Functionality • Outcomes and learning • Conclusions and future work
Project Overview Dimplex prototype devices installed during the SSET1003 trial
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.
Trial Participant Recruitment • Six homes identified • Personal visit to explain project • £100 ex-gratia payment
Technology Readiness Level (TRL) } } } } 98 76 543 21 Proven Technology Demonstration Applied R&D Research Testing Prototype Demonstration (relevant environment) System Validation (operational environment)
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:
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:
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
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
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.
Mark Stannard Honeywell Automated Demand Response
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
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
Customer Engagement Framework • 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.
Value to a DNO • Modelling was performed to extrapolate results in more detail. • Began to understand how ADR can improve network observability on the distribution network
Conclusions/ Next Steps • 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