Secure Scalable Microgrid Project

at Sandia National Laboratories

Steven Glover, Ross Guttromson

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.

University of Minnesota

Michigan Tech.

Texas A&M

• SNL is unlocking microgrid application

space through 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

– Reduction in centralized fossil fuel based

sources

– Self-healing, self-adapting architectures

– Microgrids as building blocks for larger

systems

Designing the power grid of the future

2

Networked, Secure, Scalable Microgrids (SSM TM) for Power Grid Architectures

Lanai, Hawaii

Bus cabinet & back panel

Master control computer

Programmable load

Construction of the SSM Test Bed

Load forecasting and dispatchable

sources enable grid performance

AGC

Gen Load Power

Prediction State

Estimator Fixed

Infrastructure

California ISO

Feedback loop controls minor frequency variations and output

voltage and power

Available resource forecast

Actual load

Day ahead demand forecast

30

26

22

20

0 4 8 12 16 20 24 Time of day (hours)

Pow

er (

GW

)

Capacity less largest unit

System Load

Hawaiian Electric Co. daily load vs capacity Forecasting is used to set generation

0 4 8 12 16 20 Time of day (hours)

Pow

er (

GW

)

1.2

1.0

0.8

0.6

Feedback is often through people

30

26

22

20

28

24

3

1200

1000

800

600

400

200

Stochastic sources complicate

forecasting

Wind power forecasting examples

6:00 9:00 12:00 15:00 18:00 Time (hrs) This is weather forecasting!

Actual wind Power

Forecast

0 2 4 6 8 10 12 14 16 18 20 22 24

400

300

200

100

0

MW

Solar Insolation, May 4, 2004 CST

Clear day

1200

1000

800

200

400

600 400

400

.

400

W/m

2

Hours

4

Renewable sources impact grid

performance

Generator

Transmission

Substation

Distribution

Load

AGC

Gen Load Power

Prediction State

Estimator Fixed

Infrastructure

PV

Wind

• Power flow direction

• Distributed sources

• Stochastic nature

• Voltage regulation

• Frequency regulation

• Change in system inertia

A solution: is negative loads

5

State Estimator

Power Prediction

PV

Wind

Gen

PV

Wind

AGC

To achieve maximum benefit renewable

energy needs to be treated as a source

Fixed Infrastructure

Load

System efficiency can increase

with reduction in excess generation capacity.

Both our generation and our loads are now random! 6

We are integrating and advancing

techniques for designing and analyzing

microgrids

• Developing enabling hardware – Microgrid test beds – Diesel generator emulator – Wind turbine emulator – Energy storage emulator

• Advancing Hamiltonian based control design – Enhances stability analysis – Distributed control development

• Creating tools to trade off information flow and energy storage – More efficiently utilize energy storage – Alternative communication requirements

• Mature technologies and create protocols for high level informatics based control – Adaptive, self healing, and secure systems

7

Key SSM system components enable

trade space evaluation

8

How do you connect System components in

an efficient, cost effective manner?

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

8

PV

Wind

State Estimator

Power Prediction

PV

Wind

Gen

UPFC

UPFC

UPFC Load

PV

Wind

AGC

PV

Wind

UPFC - Unified power flow controllers

High level control enable

prioritization and system adaptability

Gen

Gen

High level control optimizes system priorities

Nonlinear control maintains stability and performance

9

SSM is a DC system constructed of many

custom components allowing flexibility

10

Microgrid includes stochastic and

deterministic sources Solar (8 kW, 16 A)

0 5 10 15 20 25 300

10

20

30

40

50

60

70

t (sec)

Torq

ue (

Nm

)

Computed Tturb

Tturb

Wind turbine

emulator

7.5 kVA

J. Neely, et al., “Wind turbine emulation for microgrid development,” Cyber 2012.

J. Neely, et al., “An economical diesel engine emulator for microgrid research,” SPEEDAM, June 20, 2012.

Diesel generator emulator

10 kVA

Simulated turbine and emulator comparison

DC/DC converter

0

70 50 30 10

Torq

ue

(Nm

)

. 5 10 15 20 25 30

70

50

30

10

t(sec)

Energy storage emulation for power

systems Energy storage can change from experiment to experiment

• Bandwidth, 583 Hz max

• Peak power, 5 kW max

• Total energy storage

• Frequency response

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5

-20

-10

0

10

20

t (sec)

i bus (

A)

Hz 58335.0

riseT

BW

0.0495 0.05 0.0505 0.051 0.0515 0.052 0.0525 0.053 0.0535 0.054 0.0545

0

5

10

15

t (sec)

i bus (

A)

Higher level control systems can set storage reference points.

t(sec)

20

10

0

-10

-20

i bu

s (A

)

0 0.1 0.2 0.3 0.4 0.5

12

0 2 4 6 8 10 12 14 16 18 200

2

4

6

8

10

12

14

16

18

20

Time (s)

Curr

ent

(A)

Hardware data

Model

Active and passive loads accommodate a

range of profiles Resistive load and profile (6.7 kW max)

Inverter load (5 kW max)

High level control can interact with loads

Programmable load profile

Cu

rren

t (A

)

0 0 2 4 6 8 10 12 14 16 18 20

Time (s)

4

8

12

16

20 Measured Simulated

13

Adaptive topologies are enabled by a

controllable buss

208 V, 3-φ or 240 V, 1-φ buss with controllable semiconductor contactors

Eleven 25 Arms connections

400 V DC buss with controllable semiconductor contactors

Thirteen 25 A connections

Patch

Panel

14

Adaptable communication networks

manage information flow

• GB Ethernet Communication – Control network – Timing network – Allows for hierarchical control

• 30 MHz Data Acquisition – 2 TB hard drive – 48 channels installed

Managed Ethernet Switch

Controllers Bus

InterfaceDAS Master

Controller

Emulator

SNL Grand Challenge Summary

UPFC

Power DistributionConnectionsAgent

Control

Agent

Control

Agent

Control

Agent

Control

Agent

Agent

Loads

StorageSystems

DispatchableGeneration

RE

Control

Agent

RE

µG 2

µG 3

µG 1

Communication

network

Steps Forward

• Microgrid experiments are in progress

• Address Scalability – Collective design – Collective assembly – Extend design and analysis

techniques to collectives

• Impact utilities

R. Robinett III, et al., “Collective control of networked microgrids with high penetration of variable resources Part I: Theory,” Cyber 2012.

R.D. Robinett III, et al., “Transient Stability and Control …,” 2010 IEEE Multi-Conference on Systems and Control. S.Y. Goldsmith, et al., “Coordinated Harmonization of Stochastic Sources and Loads in Dual Independent PV

Arrays,” 2010 IEEE Multi-Conference on Systems and Control. 16

Should We Standardize?

• Standardizing on a microgrid system architecture could help to lower costs and to increase reliability/performance.

• “Openness” will keep market entrance barriers low, competition high, and innovation high.

Cost Performance

What Do I Mean By an Open

Architecture? • A system where design information is specified and available,

performance meets minimum standards, and it is relatively easy for a third party to upgrade or modify the system.

• The elements of an Open Architecture include the following:

– Transparency: The ability for public to observe hardware schematics, software

codes, protocol definitions, etc.

– Standardized I/O and Performance: These describe the inputs, outputs, functionality, and performance of a ‘black box’ component.

– Reconfigurability: The ability to make limited changes to internal parameters of a microgrid device.

– Extensibility: Ability to extend a device’s functionality using software or hardware.

– Plug-and-Play: The ability of a device to self-register and automatically configure itself when connected to the microgrid system.

Do We Need an Open Architecture?

•An Open Architecture will: – Increase competition –Spur creativity –Reduce cost – Increase reliability – Increase security –Allow consumers to know the following system parameters and the

tradeoffs between them • Cost • Function • Scalability and extensibility • Performance • Information flow • Required assets

Component Interface Control

Document (ICD)

• ICD is term that is used to define a part of an open architecture: the requirements a component must meet in order to connect to the system

• There should be an ICD for every component in a microgrid

• The ICD should dictate transparency, standardization, I/O and functionality, reconfigurability, extensibility, plug-and-play of the component

Microgrid

Is it possible to guarantee system performance by specifying component ICD (without knowing the rest of the system)? No, it’s not

What Might be Specified in an ICD?

• Interoperability requirements

• Plug-and-play requirements, component registration details

• Communications: latency, time stamping, protocols, etc

• Telemetry: phase lag, cyber security, sample methods (where important)

• Performance and withstand characteristics: – Power, frequency, voltage, harmonics, flicker, V/Hz, P/Hz, P/V

• State observability and controllability

• Control methods and objectives (low, mid, and high level controls)

• Failure responses (self failure or system failure)

Do We Care About Component or

System Performance? • We care about component performance because it leads to

system performance.

• To a LARGER degree, we care about system performance- or performance “at the load”.

Reference Architecture Spectrum

High Cost High Complexity

High Functionality

Low Cost Low Complexity Low Functionality

We may want to consider two reference systems in order to avoid unnecessarily over-designing components

Microgrid Reference Architecture

• In order to guarantee component performance, one must know the system. –Are there any elements with unspecified performance in the

system? –Are we seeking “gold plated”, “silver plated”, or “bronze

plated” performance? –Do seek differentiated performance within the same

system? –Is this a legacy system, or is all equipment new? –Is this an AC, DC, or AC/DC hybrid system? –More questions like these…

•Answers to the above questions will influence how the ICDs should be specified

Control Requirements Influence

Everything •Distributed and centralized control (not versus)

•Plug and play registration and interoperability

•The manner in which hardware is controlled, affects its performance and reliability

•Communications and protocols are central to controls

•The need for state observability and controllability affects the component design

• Fail-safe methods

The point: One cannot create the ICDs independent of the controls

What Types of Open Architecture

Standards Are Needed for Microgrids?

• Transparency

• I/O and functionality for systems and components

• Reconfigurability

• Scalability and extensibility

• Control Design, plug-and-play

• Physical device performance

• Communication

• Reference system

• Reliability

• Function and Performance

• Interoperability

• Security

• Connectivity to the bulk grid

• Re-application of MG technologies into the ‘Smart Grid’

BACK UP

Impedance/Capacity Mismatch (Duty Cycle)

1

10

10

10

10

10

10

10 1 10 10 10 0.1

2

3

4

5

6

2 3 4

Specific Energy (Watt-hrs/kg)

Elastic Element

Pneumatic

Flywheel

Photovoltaic Batteries

Internal Combustion

Fuel Cell

)()()()( xVxVxTxTH cc

xVxVxTxTH cc

dtHdtVVTTJI cc 88

i

N

i icc

Hm

HdtHdtJI cc

1

00

1 where,0][

8][

1

SNL’s Hamiltonian-Based Nonlinear Control Theory

Addresses Stability and Performance

Equations from a microgrid can be used to construct a Hamiltonian.

Asymptotic stability is achieved by satisfying the following constraints

Fisher Information Equivalency provides link to and minimization of information flow and energy storage.

Hdtc

Individual microgrid Hamiltonian

Addition of cost functions allow for optimization to a particular solution.

Chosen to minimize storage, conventional generation, etc.

Kinetic Energy Potential Energy

0][00

dtLGdtH cc

0)()(where ,0 *** xVxVxxH c

R.D. Robinett and D.G. Wilson, “Hamiltonian Surface Shaping with Information Theory and Exergy/Entropy Control for Collective Plume Tracing”, Int. J. Systems, Control and Communications, Vol. 2, Nos. 1/2/3, 2010

Control Theory Needs to be Expanded from Simple

to Complex Examples

Example system with control input v(t).

qkqdtkqktv dip )(

qRtvqC

qL )(1

qqkRqdtkqqkC

qLH dip

1

qVqVqTqkqC

qLH cp

)()(

2

1

2

1

2

1 222

Storage Load, L Generation, G

Control gains

PID controller:

Hamiltonian:

Derivative of the Hamiltonian:

Controller gains are chosen for specific performance within the solution space defined by:

0)0()0(where0 ,0)()()( cc VVqqVqVqTH

0][00

dtLGdtH cc

R.D. Robinett and D.G. Wilson, “Nonlinear Power Flow Control Applied to Power Engineering”, Int’l Symposium on Power Electronics, Electrical Drives, Automation, and Motion, SPEEDAM 2008, June 11-13, Ischia, Italy, pp. 1420-7.