1. Stewart Reid – SSEPD Graham Ault – University of Strathclyde John Reyner – Airwave solutions NINES Project Learning to date

2. 2 - 2 - NINES Overview No Mainland connection Single DC link £500M Demand Max. 50MW-Min. 14MW Renewables 4% by capacity 7% by Unit production l.f. ~50% Population ~22,000

3. NINES System Overview LIC New Small Wind LIC Lerwick Power Station SVT Power Station Burradale Windfarm LIC Existing Generation New Large Wind DDSM 1MW BatteryThermal Store LIC Active Network Management System

4. NINES Update LIC New Small Wind LIC Lerwick Power Station SVT Power Station Burradale Windfarm LIC Existing Generation New Large Wind DDSM 1 MW BatteryThermal Store LIC Active Network Management System

5. Modelling the Shetland Power System University of Strathclyde

6. Customer demand forecast model Unit scheduling model Economic and commercial model Strategic and operational risk model System development optimisation model Estimate of energy demands for operational period Transient stability envelope for system operation Operational Models Evaluated system development options Strategic Models Allocation of costs and benefits. Operating schedule and cost for given system configuration. Operational risks Dynamic system model Scheduling services enduring commercial arrangements Shetland System Modelling: Overview

7. Shetland System Modelling: Outcomes Operational Models –Customer Demand: Quantification of flexible heat demand and thermal energy storage for domestic customers –Power System Dynamics: Envelope of stable/secure system operation –Unit Scheduling: Estimate of renewable energy access and role of flexible demand and energy storage Strategic Models –Economic and Commercial: Private costs and benefits of Shetland repowering options and commercial arrangements concepts –Strategic Risk: Extensive mapping of Shetland low carbon smart grid risks and repowering investment decision tree –System Development: identification of future system development options and optimisation model specification

8. Control Philosophy for the Active Network Management (ANM) Scheme Scheduling Engine Works ahead of real time based on forecasts and current system state Real Time Application of Schedule Applies schedules to flexible demand and battery storage Automatic Real- Time Monitoring and Control Manages generation set- point within constraints. Monitors energy delivery to flexible demand and monitors forecast error. Control Centre Manual Intervention Power system operators able to intervene in response to system conditions.

9. Resource status and forecasts Local Interface Controllers Homes with Heaters/Tank Domestic DSM ‘Element Manager’ ANM System Customer Demand Model System Dynamic Model Unit Scheduling Model Aggregate zone/group energy demand data Controls and Schedules Demand sampling requirements Energy forecast Load/storage state Schedule block sizes Consumer classification Aggregation and scaling methods System stability constraints/rules Required frequency response Scheduling constraints/rules System stability constraints/rules Control Room / EMS / DMS Control Instructions Monitored parameters Model Inputs to Operational System

10. Shetland System Dynamic Simulation: Transient frequency limits 2% under- frequency limit Dynamic models of all system components in NINES: –Frequency responsive demand, thermal and renewable generation, energy storage Identification of allowable/stable/secure system states through simulation

11. System constraints on wind generation access Identification of allowed ‘envelope’ for wind generation operation (forms input to scheduling model and operations) Modification of ‘envelope’ dependent on de-risking NINES innovative solutions

12. Unit Scheduling Model: Overview Model configuration and setup: –Demand Model input: customer constraints –Dynamic Model input: stability/security constraints –System model, objectives and flexible demand and energy storage parameters Uses Optimal Power Flow with linkage between time periods across scheduling horizon (e.g. 24 hours): –Applies constraints in priority order to generate schedule of energy flows to/from connected devices –Maximisation of low carbon generation Demand and wind forecasts Stability Rules Network Rules Conventional Generation Smoothing Optimised energy schedule

13. Current SOC Target SOC Current SOC Domestic Space Heating: input from demand model Domestic Hot Water: input from demand model Battery Storage: flexible within scheduling process Unit Scheduling Model: Energy Storage Target SOC ?

14. Scheduling Example: Stability Rules Starting with fixed component of demand and wind power forecast: schedule flexible demand (DDSM) within stability/security constraints Domestic flexible heat demand scheduled into period of low fixed demand and high wind power output

15. Scheduling Example: Network Rules With interim stage schedule: apply network constraint rules to achieve ‘network constrained schedule’ Domestic heat demand rescheduled into periods when wind power would otherwise be constrained

16. Scheduling Example: Final Schedule and Actual Outcome Final schedule is subject to forecast error in delivery so ‘optimal’ schedule must be adjusted in real time Acceptable deviations to conventional generation schedule

17. Ross Macindoe Head of Future Networks Airwave NINES Making the Connection

18. Making the connection Power Sources Homes Advanced Energy Storage ANM Inter-system Gateway Devices group management Aggregated data processing and feedback Fast group-based commsIntegrated LIC and Communications

19. Wider Long Term Benefits Airwave SmartWorld Fault Monitoring DDSM Distributed Generation TelemonitoringSocial Alarming Security and Alarming Outage Management

20. REAL PROGRESS = REAL LEARNING ANM system Live Battery installed 6 home trial complete Comms contract Customers validated benefits of Quantum Heaters THE KIT THE PEOPLE THE BUSINESS CASE Design for the customer not just for our “smart” aspirations DSM/Storage portfolio management is essential Detailed modelling and 6 homes confirming initial expected benefits NINES informing solutions elsewhere

21. THANK YOU