Steve Glover

Electrical Sciences and Experiments Department Manager

Sandia National Laboratories Albuquerque, NM 87185

Secure and Scalable Microgrids Enabling Technology and Applications

Rensselaer Polytechnic Institute Workshop on Microgrid Technologies and Applications

October 10-11, 2013

Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of

Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Outline

• Overview of the Electrical Science Group

• Microgrids

– DOE related microgrid activities

– Secure Scalable Microgrid

2

Nuclear Weapons Stockpile Responsibilities Drive Deep

Expertise in Grid-relevant Science and Engineering

3

Advanced power systems

and AC/DC microgrids

High voltage breakdown

science & experiments

Pulsed power components

and systems development

Electromagnetics

theory/code development

Electromagnetic

experiments

Systems engineering and

integration

Launch

Boost Midcourse

Terminal

Over Target

Weapon storage, transportation, maintenance, storage

on delivery platform, launch and in-flight path

Normal Environments (EMR, ESD, nearby lightning,

degaussing)

Abnormal Environments (lightning, exposure to power

sources)

Hostile Environments (nuclear weapon effects, directed

energy weapons, high power microwaves)

Syste

m &

Co

mp

on

en

ts

Ph

ysic

al

En

vir

on

men

ts

All s

tockp

ile

-to

-targ

et-

seq

uen

ce (

ST

S)

ph

ases

Grid-relevant Science and

Engineering at Sandia

E-beam supported wind tunnel

and high heat flux research

Other Capabilities include

3

Electrical and Radiation Sciences

Customers, Organization, and Facilities

National security activities for and in collaboration with:

– Department of Energy (National Nuclear Security Administration, Office of Science, Office of Electricity)

– Other federal agencies (DOD-Army/USAF/NRL, DOT-Federal Aviation Administration, DOL – Mine Safety and Health Admin.)

– Non-federal entities

– Industry (Goodyear, FMC, Inc., Lockheed Martin Technology Research)

– Universities

World class accelerator technology

development & high heat flux research

Lightning protection

Power systems

All Electric Warship

Sago mine, 2006

EMP coupling

into facilities

4

Generation

Transmission

Substation

Distribution

Loads

Today's Grid Power

Centralized generation

Excess generation & fuel storage

Fixed infrastructure

Demand forecasting

Essentially open loop control with human in

the loop

Limited ability to support renewable sources

Limited ability to support disruptions

Smart grid initiatives

Renewable

sources Forecasting is used to set generation

California ISO

Available resource forecast

Actual load

Day ahead demand

forecast

0 4 8 12 16

20 24

Time of day (hours)

Po

we

r (G

W)

30

28

26

24

22

20

Current Grid is Evolving to Accommodate Different

Energy Sources, Increased Reliability and Resiliency

5

Advanced Energy Surety Microgrid (ESM) Projects

To address current shortcomings of

power reliability and security, Sandia is

investigating advanced microgrid

approaches to make distributed energy

generation and storage resources more

reliable, cost effective, and secure to

improve overall critical mission

assurance.

Sandia’s microgrid research utilizes

smart grid technologies to enable:

• Distributed energy generation and

storage to be operated both ‘grid-

tied and ‘islanded’,

• Energy demand/response,

• Increased use of renewables

• Secure cyber control,

• Improved reliability and resiliency,

and

• Use DoD sites as initial test beds.

Provide higher energy reliability and

resiliency to critical community and

industrial infrastructure and operations

for low probability but high consequence

events (natural disasters, intentional

events, or large accidents).

Enhance energy safety, security, and

reliability for civilian applications with

a focus on:

• Providing energy resiliency using

distributed generation to maintain

critical community functions and

operations for extended outages,

• Support demand/response of

distributed community generation

and storage to support local utility

distribution system.

DOE & DoD R&D DOE & Utility R&D

6

NEDO Microgrid Project

• Energy storage (small)

• Gas Engine (240 kW)

• Fuel Cell (80 kW)

• PV (50 kW)

• Demand response? 100 kW Dummy load

Electric Chiller/Thermal storage

Community/Utility Coupled Microgrid Efforts Help to Accelerate Commercial Smart Grid Applications

7

Studio

Substation

Other Load

And PV

Residential

(under

construction)

PNM Microgrid Project

• Large-scale PV (500 kW)

• Large-scale Storage 250 kW 4 hr. energy battery

500 kW, 40 min power battery

• Smart Grid / SCADA integration

Studio 14 Feeder

(12.47 kV)

115 kV System Utility

Networked, Secure, Scalable Microgrids (SSM TM) Enable High-Penetration Renewables and Improved Operations

• Ground breaking nonlinear control theory, informatics, and innovation.

• Tools are being developed for networked microgrids spanning from conventional to 100% stochastic generation.

• Potential impact:

– Unlimited use of renewable sources

– Lower-cost provisioning at a given level of renewables

– Reduction in centralized fossil fuel based sources

– Self-healing, self-adapting architectures

– Microgrids as building blocks for larger systems

Bus cabinet

Rotational

machines

SSM test bed

Lanai

Hawaii

8

Tiered Control Structure Enables Prioritization and System Adaptability

9

The Basic SSM Test Bed Structure Enables a Flexible Research Platform

New power system

components will

increase complexity

associated with

control and

performance.

Generation

Sources or

other

Microgrids UPFC

Power Distribution

Connections Agent

Control

Agent

Control

Agent

Control

Agent

Control

Agent

Agent

Loads

Storage

Systems

Dispatchable

Generation

RE

Control

Agent

RE

Communication

network

10

SSM Test Bed Exhibits Dynamics Similar to the Grid

11

Datalink

Engine (emulator) Speed

Inter-area oscillations

Energy storage can improve resiliency Control attributes influence stability

Demonstrated Performance with 100% Stochastic Generation and Load is Enabled Through Controls and Storage

Stochastic

Source #1

Sources

2 - Stochastic

Agents were not part

of this experiment.

12

Stochastic

Source #2

Hamiltonian Based Control Approach with Full State Control – Reduces Bus Voltage Transients

Source and load profiles

Stochastic source #1

Green – commanded profile

Blue – actual profile

Red – indicates progress in time 13

Stochastic source # 2

Load

Cyan – load current

Red – diesel current

Light blue – wind current

Purple – load current

Dark blue – Bus energy storage current

Transients are not evident in the bus voltage

Understanding and Leveraging Information Flow in a Power System is Necessary for Optimal Performance

• Batch-run experiments enable apples to apples control comparisons

• Example shows the effect of Informatic control update rate on cost

100

101

102

0

1000

2000

3000

4000

5000

6000Performance vs Update Rate

Agent Update Frequency (Hz)

Co

st: J

=(

vlo

ad -

E(v

loa

d)

)2 d

t (

V2se

c)

Control bandwidth of ServoControl

Nyquist frequency of variable load

fc of bus based on min/max resistor values

Experiment Data

0 10 20 30 40 50 60 70 80 90 10050

100

150

200

t (sec)

vlo

ad (

V)

Load Voltage vs. Time - Comparison of Update Rates

1 Hz (1 sec interval)

2 Hz (500 msec interval)

10 Hz (100 msec interval)

100 Hz (10 msec interval)

ft

t

loadloadfv dvvtJ

0

2)(ˆ)()(

0 10 20 30 40 50 60 70 80 90 1000

1

2

3

4

5

t (sec)

i load (

A)

Load Current vs. Time - Comparison of Update Rates

1 Hz (1 sec interval)

2 Hz (500 msec interval)

10 Hz (100 msec interval)

100 Hz (10 msec interval)

100

101

102

0

5

10

15Performance vs Update Rate

Agent Update Frequency (Hz)

Co

st: J

=(

iA

RE

SE -

E(i

AR

ES

E)

)2 d

t (

V2se

c)

Control bandwidth of ServoControl

Nyquist frequency of variable load

fc of bus based on min/max resistor values

Experiment Data

ft

t

ESESfi diitJ

0

2)(ˆ)()(

14

Networked Microgrids can add to Power System Reliability and Resiliency

Microgrid #2 Microgrid #1

Microgrid #3

Master Controller

15

SSM Testbed Allows Study of Microgrid Collectives

• Centralized data acquisition allows plotting/analysis in Matlab

16

In Summary

• Sandia Electrical Sciences research is addressing a wide range of power system challenges

– Controls, stability, protection, and susceptibility

• Sandia’s Energy Surety Microgrid research is addressing reliability and resiliency of DoD and commercial microgrids through near term technologies

• Sandia’s Secure Scalable Microgrid research is integrating:

– Informatics theory (including cyber security),

– Hamiltonian based controls,

– Communication theory,

– and flexible experimental capabilities

• Scalable approaches to networked microgrids support the building block concept

• DC system control approaches are being migrated to AC systems 17