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NINES Project Learning to date

Stewart Reid – SSEPD Graham Ault – University of Strathclyde John Reyner – Airwave solutions. NINES Project Learning to date. NINES Overview. 2. No Mainland connection Single DC link £500M Demand Max. 50MW-Min. 14MW Renewables 4% by capacity 7% by Unit production l.f . ~50%

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NINES Project Learning to date

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

  2. NINES Overview 2 • 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 - 2 -

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

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

  5. Modelling the Shetland Power System University of Strathclyde

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

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

  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

  13. Unit Scheduling Model: Energy Storage Domestic Space Heating: input from demand model Current SOC Target SOC Domestic Hot Water: input from demand model Current SOC Target SOC Battery Storage: flexible within scheduling process ? Target SOC Current 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 MacindoeHead of Future Networks Airwave NINESMaking the Connection

  18. Making the connection Power Sources Homes Advanced Energy Storage ANM Secure Resilient Communications Network Integrated Hub Element Manager Airwave SmartWorld • Inter-system Gateway • Devices group management • Aggregated data processingand feedback • Fast group-based comms • Integrated LIC and Communications

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

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

  21. Thank You

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