NSF Workshop Real Time Data Analytics for the Resilient Electric Grid. Data Driven Measuring and Enabling Resiliency of the Community Grids

Transcription

1 NSF Workshop Real Time Data Analytics for the Resilient Electric Grid Data Driven Measuring and Enabling Resiliency of the Community Grids Rob Hovsapian, Ph.D. Manager, Power and Energy Systems Idaho National Laboratory August 3 rd, 2018

2 Integrated Multi-Scale Real-Time Simulation Test-bed Real world PHIL & CHIL testing capabilities. 2

3 1 - INL Utility Scale Microgrid Project Red Cross Evacuation Funded by California Energy Commission s Electric Program Investment Charge PON Program Goal: Demonstration of Low Carbon-Based Microgrids for Critical Facilities Partners INL, Siemens, Tesla (Utility scale Storage) Humboldt University, PG&E

4 Blue Lake Rancheria CEC Project Microgrid provides resilience to the power supply in the area, a Red Cross evacuation route. Operating and troubleshooting complex systems in a test environment. Developers could safely conduct fine-tuning and de-risk transitions to the end-user s live systems. Partners included the California Energy Commission ($5M with 20% cost share), Siemens, Tesla and Humboldt State University.

5 California Energy Commissioner Project Future & Existing Energy Infrastructure

6 Digital Blue Print, Rapid Prototyping Design Environment and Functionality Testing via CHIL PG&E Power System Network Microgrid Modes of Operation: Blue Lake Rancheria, CA 1. Grid connected 2. Black start transition 3. Off-grid operation 4. Resynchronization to PG&E network Modbus/DNP3.0 connection Siemens MGMS INL

7 BLR Benefits / Awards Awards: FEMA s 2017 Whole Community Preparedness Award Energy Savings First year savings were 563 MWh. DistribuTECH 2018 Project of the Year for DER Integration Greenhouse Gases 159 metric tons of CO2 were abated during the first year. Job Creation This project has resulted in the creation of four permanent, new jobs at BLR. This is a 10% increase in the tribal government workforce. Public Safety The BLR campus now has a supply of locally generated green power, which together with battery storage, provides emergency power to support their role as a Red Cross shelter in times of need.

8 2 - Resilience Metrics Approach to design a Community Grid Idaho Falls Power - Smart Reconfiguration of Idaho Falls Power Distribution Network for Enhanced Quality of Service Priority 1 4 Description Very High Priority Loads (Examples: Hospitals, Control/Command center, Emergency Response/Dispatch) Idaho Falls Power Regional Distribution Network Software PMU q 5 9 High Priority Loads (Examples: Airport, Correctional Facilities, Police Department, Fire Station) V b V a Medium Priority Loads (Examples: Fire Station, State Services) d Low Priority Loads (Examples: Water Treatment, Community Care) SEL HIL (to be extended) Protection devices and Switches Control action Analog output Measurement Analog/digital output Measurement PMUs micropmus V c Hardware PMU Analog/digital output INL Energy Systems Laboratory

9 Next Generation Microgrid Design Next generation of microgrid design tools Communication emulation Co-simulation of communication, power electronics (including SiC-based devices), power systems (including real-time emulation of protection system) Cont rols I nterface I nterface V,I -AMPs NS3-based Com m unication Layer Hardware Prot ect ion Relays Controller HI L 9

10 Resilience Based Reconfiguration/Operation Example Critical Loads (priority numbered) Example Priority Example Load Description Very High Priority Loads (Examples: Hospitals, Control/Command center, Emergency Response/Dispatch) High Priority Loads (Examples: Airport, Correctional Facilities, Police Department, Fire Station) Medium Priority Loads (Examples: Fire Station, State Services) Low Priority Loads (Examples: Water Treatment, Community Care) 10

11 Real-time Integrated HIL Testing Idaho Falls Power Regional Distribution Network Software PMU q V a V b d V c SEL HIL (to be extended) Protection devices and Switches Control action Analog output Measurement Analog/digital output Measurement PMUs micropmus Hardware PMU Analog/digital output INL Energy Systems Laboratory 11

12 Black Start Preliminary HIL Testing March 17 Black Start of IFP grid and re-synchronization to transmission grid One scenario is investigated to test synchronization of City Bulb generator to a T-grid source while City Gen is serving the local command center critical loads City Bulb: 8.9MVA SEL 700G Station Transformer 4.16kV/12.47kV/46kV Out of Synchronis m In Synchronis m T-grid kept at 46kV, 60Hz, 20degrees Total load ~ 874 kw Synchronization controls are modeled in RTDS-RSCAD for seamless resynchronization SEL 700GT+ Relay is used as Hardware-in-the-Loop (HIL) simulation with analog and digital interfacing with RTDS 12

13 3 - Resilience By Design Resilient Alaskan Distribution system Improvements using Automation, Network analysis, Control, and Energy storage (RADIANCE) 13

14 Goals and Objectives (cont d.) Technical Approach: Integrated and iterative field validation of resilience-based design and operation to goals Figure is modified directly based on GMLC Lab Call document

15 1 2 Project Overview Resilience Metrics Framework for Design and Operation Develop and demonstrate practical use of resilience metrics for coordinated operation, design to minimize outages, financial losses Multiple Networked Microgrids in Distribution System Leverage rotational and virtual inertia of microgrids assets including hydro, diesel, energy storage, and micro PMU-based sensing to enhance resilience of the overall regional distribution network 3 4 Cyber-security Architecture and Rapid Prototyping of Controls Rapid prototyping of controllers as HIL and cyber-vulnerability testing in a real-time cyber-secure environment Field Validation of Resiliency Enhancement Methods Field validation of increasing resiliency of the overall distribution system by leveraging resources from multiple networked microgrids

16 Resiliency enabling process is dynamic Request backup Services and crew Storm Hardening Installation of backup Process Validation generator Automated restoration Initial Forecast Event characterized Precede Event During Event Aftermath Recovery Phase Recovery Resources strategically placed Smart Load Shedding Critical Load survival Smart recovery and Repair-based restoration Stage 1 Stage 2 Stage 3 Stage 4

17 Calculating Resiliency Metrics Building upon software tools developed in GMLC 1.3.9, CANVASS, resiliency metrics will be calculated based on threat at a nodal as well as a network level. Anticipate Withstand Recover Develop a threat model Know the infrastructure Anticipate impact of threat on the infrastructure Ability of an infrastructure component or infrastructure to endure an high-impact event, may be storm hardening, or backup individual generators Minimum spanning tree and critical-first restoration strategies and resource optimization to enable maximum resilience and minimum downtime

18 Architecture Design Resiliency Framework Operational Resilience Metrics Computation Flowchart Real-time computation of Resilience Metric Real-time Inputs (weather, power grid) Physical and Communication Infrastructure Design Historical Data Probabilistic Analysis Operation and Controls

19 Thank you