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Integrating Multiple Microgrids into an Active Network Management System Presented By:Colin Gault, Smarter Grid Solutions Co-Authors:Joe Schatz, Southern.

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Presentation on theme: "Integrating Multiple Microgrids into an Active Network Management System Presented By:Colin Gault, Smarter Grid Solutions Co-Authors:Joe Schatz, Southern."— Presentation transcript:

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 3 rd 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 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 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

9 Interconnected Regional Constraint Management Microgrid Constraint Management Ancillary Services Energy Management DER Controller 9

10 Transition Management Planned Islanding RegionalMicrogrid Unplanned Islanding RegionalMicrogrid Reconnection RegionalMicrogrid 10

11 Islanded Frequency / Voltage Control Energy Management Black Start DER Controller 11

12 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 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 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 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

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 22 Proposed architecture for trial deployment

23 Presented by: Colin Gault, Principal Consultant, Smarter Grid Solutions E-mail: Phone:+1 (718) 260 3603 23

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