Optimerad drift av solcellsanläggningar och aggregerade tjänster Intelligent Energy Management of Distributed Energy Resources (DER)

Transcription

1 Optimerad drift av solcellsanläggningar och aggregerade tjänster Intelligent Energy Management of Distributed Energy Resources (DER) Raymond Kaiser Amzur Technologies

2 THE BIG CHALLENGE How to accommodate the variability & uncertainty of Variable Renewable Energy (VRE) sources? 7% 31% today in 2050

3 SOLAR SWEDEN Comparable solar resource to southern Germany Utility-scale solar potential estimated at 4 GW by 2050 (CNS) Rooftop solar potential estimated at 32 GW.

4 Shares of wind and solar generation that reach 35% and more will place great demands on Nordic electricity grids and markets. NETP 2016

5 Solar power production can vary dramatically moment to moment. High penetration is tough to manage without smarter technologies.

6 Solar variability introduce new challenges Fast ramp time and rapid changes in supply and/or demand is decreasing from minutes to seconds and sub-seconds Excessive operations of voltage control devices increase wear & tear on utility fixed assets (load tap changers and cap banks) Increased circuit losses and inadequate reactive power(var) support Lack of coordination with spinning reserves resulting in inefficient use of resources Competing control objectives between unmanaged resource operations and utility operations Solallén Sweden s first Net Zero Energy neighborhood

7 The grid communications & control (C&C) paradigm is changing from baseload-and-peak to inherently variable supply and dynamic, flexible demand.

8 No standard and secure DER Wide Area Network C&C = Integration Complexity Several competing DER control and transaction protocols = Operational Complexity Need to integrate with behind-the-meter DER assets (smart inverters, thermostats and electric vehicles) = Integration Complexity + Operational Complexity + Security Risk

9 Everything should be made as simple as possible but not simpler.

10 ASHRAE 201 Facility Smart Grid Information Model (FSGIM) OpenDEM is based on well-documented Information Model (ASHRAE 201 FSGIM) and industry standard Data Models (SunSpec/OASIS/SEP2). Four Model Components Meter Generator Model devices that produce Model devices that measure power or store energy Load Model devices that use energy Energy Manager Model devices that make decisions based on power, energy, price, weather, etc.

11 Meter Model devices that measure power Specify meter that uses Sunspec Meter Data Model.

12 Load Model devices that use energy Customer Energy Information Usage Cost Interval Data Energy information exchange data model. Green Button allows download of data and persistent data connection to thirdparties.

13 Generator Model devices that produce or store energy Solar PV and energy storage data models based on SunSpec information model. Forecaster Demand Solar ESS

14 Energy Manager Model devices that make decisions based on power, energy, price, weather, etc. Energy Manager based on IoT automation platform Well-supported Vendor-neutral Hardware and protocol agnostic Open source Scalable

15 User Interface Forecaster Dashboard Profiler Planning & Simulation Energy Monitor Logger Archiver Device Manager HVAC Lights Demand Solar ESS Device Monitoring & Control Calendar / Scheduler Load Manager Optimizer Economic Dispatch Dispatcher user-defined rules Utility tariffs rates emissions Load x

16 THE PILOT Flexible Demand Management and Economic Dispatch Based on open standards and protocols and open source IoT platform Controller is small, low-cost, off-the-shelf PC Energy Dashboard measure & monitor power Forecast Solar Power Production Energy Demand Battery Storage Charge and discharge battery and optimize load automatically based on power forecast, energy price and user-defined priorities

17 TACK, TACK

18 BACKUP SLIDES

19 The Duck Bill Challenge Big shift in load shape. Overvoltage Unexpected capacity / backfeed Dynamic supply changes Time of day/weather Supply Demand Mismatch Supply peaks midday Evening is new peak Quick ramp time

20 A Decentralized Services Model Microgrid shared data bus Utility DERMS Semi-autonomous Field Area Networks Aggregator Independent Services that communicate on a Shared Message Bus

21 Information Model Describes a system/data in a an abstract way and not tied to a specific implementation. Common data models IEC DER Advanced Inverters protocols Data Models Concrete representation of an information model tied to a specific representation.

22 As grid-connected solar and wind resources become more prevalent, fifteen-minute resources become more important for grid stability. LBNL study concluded that batteries, demand response, and quick-start generators provide this service much more effectively than large, fossil-fueled power plants. The flexibility of these options enables them to react quickly, and at full capacity, to imminent, short-term needs.

23 PowerShift Atlantic worked with water heaters, electric boilers and electric thermal storage (ETS) units.

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