Integrating Multiple Microgrids into an Active Network Management System
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This document summarizes a project between Southern Company and Smarter Grid Solutions to develop an active network management platform to integrate multiple microgrids. The project involves: 1) Defining use cases for interconnected, transition, and islanded microgrid operations and simulating them. 2) Deploying the active network management solution in a field trial at a test site to control distributed energy resources like solar, batteries and EVs across microgrids. 3) Implementing microgrid functionality in phases to allow multiple microgrids to operate autonomously yet coordinated.
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Integrating Multiple Microgrids into an Active Network Management System
- 1. Integrating Multiple Microgrids into an Active Network Management System Presented By: Colin Gault, Smarter Grid Solutions Co-Authors: Joe Schatz, Southern Company George Gao, Southern Company George Simard, SIMARD SG Bob Currie, Smarter Grid Solutions February 3rd 2015
- 2. The “Project” • Regional Microgrid Control: Research and Development • Multi-year project between Southern Company and Smarter Grid Solutions • Develop microgrid control platform using Active Network Management technology • Phased Approach – Phase 1: Use Case Definition and Simulation of Active Network Management (Complete February 2015) – Phase 2: Trial deployment of Active Network Management at test site (Summer 2015) – Future Phases: Phased implementation of microgrid functionality (2016) 2
- 3. Active Network Management • End-to-end autonomous control solutions • Real-time operating system providing deterministic control over distributed energy resources • Safe, secure and reliable method to increase hosting capacity of electricity grid • Complements existing SCADA and Protection systems 3
- 4. Generator DMS Energy Storage System Generator Energy Storage System DERMS Data Historian Active Network Management Reliable - Deterministic - Repeatable Scalable - Open Standards 4
- 5. Active Network Management • Applied active network management to the following use cases in live deployments – Management of power flow constraints – Management of voltage constraints – Management of distributed generation contributing to transmission system constraints – Smart electric vehicle charging – Demand Response (domestic / commercial) – Day ahead scheduling of controllable demand to coincide with renewable energy production to support frequency stability • Interfacing with range of Distributed Energy Resources – Wind | Solar | CHP |Building Management System | Electrical Energy Storage Thermal Energy Storage | Electric Vehicle Charging Equipment • Future development could include interoperability with automatic restoration and volt-var control solutions leveraging DER control 5
- 6. Generator Energy Storage System Circuit Microgrid Generator Facility Microgrid Energy Storage System Substation Microgrid Microgrid Controller Microgrid Controller Microgrid Controller DMS ANM Application DERMS Data Historian Adaptation to Incorporate Microgrids New layer of control: Microgrid Controller 6
- 7. Layers of Microgrid Control 7
- 8. Use Case Definition • Create use cases across three modes of operation – Interconnected • Microgrids interconnected with area power system – Transition Management • Microgrid transitioning into and out of islanded operation – Islanded • Microgrid operating as an island 8
- 10. Transition Management Planned Islanding Regional Microgrid Unplanned Islanding Regional Microgrid Reconnection Regional Microgrid 10
- 12. 1 MW Solar PV 1MW, 2MWh ESS Modelling and Simulation • Model of 12.47 kV Feeder with existing Solar PV: Peak demand 8MW • Large proportion of feeder load is a single industrial customer • Battery Energy Storage System to be installed later this year • Steady State Load Flow simulations using CYMDIST • Interconnected and Islanded Microgrid Use Cases Explored 12
- 13. 1 MW Solar PV 1MW, 2MWh ESS Feeder Demand Measured at Substation • Interconnected – Use of the Energy Storage to minimize total feeder maximum demand – Use of the energy Storage to minimize ratio between total feeder maximum and minimum demand 13
- 14. 1 MW Solar PV 1MW, 2MWh ESS Microgrid Isolation Points Microgrid Loads 25 kVA 500 kVA 25 kVA 14 • Islanded – Use ESS profile generated during simulation of interconnected use case – Maintain balance between load and generation on section of feeder – Loads chosen are non- industrial customers
- 15. 1 MW Solar PV 1MW, 2MWh ESS Microgrid Isolation Points Microgrid Loads 25 kVA 500 kVA 25 kVA 1500 kVA 15 • Extended Island – Extend microgrid boundary – Include additional load to stretch capability of microgrid resources
- 16. • Input Data – One year (2014) of hourly data for feeder measured at substation • Calculate “average day” profile for feeder • Generate a 24 hour schedule for battery to reduce peaks and troughs and apply to 365 days • Apply upper and lower thresholds that trigger unscheduled charge/discharge of battery Method: Interconnected 16
- 17. • Starting position uses results from interconnected study • For every hour in the year calculate the maximum duration that an island could be sustained if an “event” was to occur – Match Battery and PV to load on section of feeder – Excess energy from PV charges battery – Shortfall in PV discharges battery • Assumes battery inverter has capability to maintain frequency and voltage stability Method: Islanded 17
- 18. • Interconnected – Yearly peak demand reduced by 200 kW – Yearly minimum demand increased by 150 kW • Islanded: Peak load 500 kW – Islanding achievable 6888 hours out of 8760 – Average duration: 30 hours • Extended Island: Peak load 2,000 kW – Islanding achievable 1584 hours out of 8760 – Average duration : 7.6 hours Results 18
- 19. 19 4 4.5 5 5.5 6 6.5 7 0 2 4 6 8 10 12 14 16 18 20 22 24 Typical Day Original Profle (MW) With Battery (MW) -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0 2 4 6 8 10 12 14 16 18 20 22 24 Battery Profile Final SOC (MWh) Final Power Profile (MW)
- 20. • Shape of profile with long peaks and deep troughs makes it difficult for battery to reduce peak and increase trough significantly during interconnected mode when following a daily schedule • May be more appropriate to use battery during instantaneous events using triggers as opposed to implementing daily schedule • Islanding results show promise in being able to sustain a microgrid for significant period of time to reduce interruptions to non-industrial customers on feeder Conclusions 20
- 21. Project Next Steps • Deploy Active Network Management solution to perform field trial of use cases and compare results • Phased roll-out of microgrid functionality at pilot site and/or other appropriate sites and development of inter microgrid control philosophies 21
- 22. 1 MW Solar PV 1MW, 2MWh ESS MP MP MP Power Flow Measurement Point 22 Proposed architecture for trial deployment
- 23. Presented by: Colin Gault, Principal Consultant, Smarter Grid Solutions E-mail: [email protected] Phone: +1 (718) 260 3603 23