Distributed Grid Intelligence
Dr. Bruce McMillin
Missouri University of Science and
Technology
Wednesday June 1, 2011
1
Relationship to Strategic Plan
System Demonstration:
- Plug-In Hybrid Electric and Plug-In
Electric Vehicles (PHEV/PEV)
Distributed System
Management
•Configuration
Management
•State Collection
•Fault Diagnosis
Power
Management
and Economic
Dispatch
Enabling Technology:
- Distributed Energy Storage
Device (DESD)
- Distributed Grid Intelligence (DGI)
- Reliable and Secure
Communications (RSC)
Fundamental Technology:
- System Theory Modeling and
Control (SMC)
IFM
Intelligent Fault Management
IEM
Intelligent Energy Management
PHEV
/PEV
Plug-In Hybrid Electric Vehicle
Plug-In Electric Vehicle
- Advanced Storage (AS)
IEM
2
Research Objectives
Objective: Perform the necessary research to develop
software tools and platforms suitable for the
implementation of intelligent, distributed, robust control
functions for the FREEDM System. The control functions
will be developed by SMC subthrust and other related
subthrusts, and should achieve the functionality of IEM
and IFM.
The long term research plan for DGI is to create a
Distributed Grid Operating System that manages the
energy resources of FREEDM. The research develops a
resilient (secure, dependable, self-healing) and energy
efficient management system for FREEDM
3
Research Roadmap
Year 1-4
Distributed coordination of energy resources, based on algorithmic and economic optimization of resource
allocation to and from each SST within the IEM;
Implementation of FREEDM first in a hybrid environment with distributed C++ code and PSCAD/RSCAD
simulation, followed by distributed implementation of DGI in the green hub using networked computers in
each SST interconnected by RSC.
Fault tolerance and configuration management of both DGI processes and interface to and from the IFM (at
the FID level
Year 5-6
Development of information security policies for FREEDM and implementation in a combined RSC/DGI
environment, integrating messaging, code, and physical behavior
Correctness specification and formal verification of critical FREEDM functions and security using model
checking techniques
Grid Intelligence Software
Module Broker
Resource Manager,
Coordinator/State Maintenance
SST Standard Interface
Plug and Play Device
Standard Interface
4
Major Year 1-3
Accomplishments
Custom or Third Party Applications
SCADA
Distributed
Energy
Resource
Management
Outage
Mgt
System
Resour
ce
Plannin
g
Energy
Manageme
nt System
ISORTO
Reporti
ng
Distributio
n
Manageme
nt System
AMR
& AMI
Asset &
Facilities
Managem
ent
Energy
Marketin
g
Engineerin
g&
Maintenan
ce
Security & High Fidelity Data Management
GreenBusTM
Internet-Scale Field Device Interface – DNP3.0
DESDs
DRERs
FIDs
SSTs
DGI: Distributed Operating
System for FREEDM
Scalable and Incremental Peer to
Peer Functionality supporting
plug-in Software Modules
Each Module has various
communications requirements –
most can be solved with datagram
service
Broker Maintains System State
Active/Inactive SSTs
Load/Supply State of each SST
Active/Inactive Connections to other
SSTs
Fault Tolerant
FIELD DEVICES
5
Major Year 1-3
Accomplishments
DGI @ SST
Power Management
Algorithm
Fractional Knapsack from SMC,
Year 2 – incremental
bidding/migration
Balances the power on
FREEDM to meet the net
demand/supply through
negotiation among peer SST
nodes to control individual
Power Electronics to add or
subtract power to / from a
shared power interconnection
bus
Features
Inherently Fault-Tolerant
(Omission Faults)
Reconfigurable & Scalable
Computes/Integrates with DDLMP
Demo
Software Modules
FAULT
CONSENSUS
DETECTION
SYSTEM
DD-LMP
GROUP
MANAGER
STATE
COLLECTION
POWER
MANAGEMENT
Peer SST
Peer SST
SST1
SST 0
SST n
SST 0
L
SST 0
N
SST 0
N
SST 1
H
SST1
H
SST 1
H
:
:
:
SST n
H
SST n
N
SST n
SST1
SST 0
H
SST n
SST 0
N
SST 0
N
SST 0
N
SST 1
H
SST1
N
SST 1
H
SST n
:
:
:
H
SST n
N
SST n
H
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Major Year 1-3
Accomplishments
DGI @ SST
Group Management
Manages group membership
of SST nodes by determining
the neighbors/peers
Handles transient network
partitions or failure of node(s)
(through Reorganization)
Elects a leader of the group
which has special group
information to be used by
other modules or a new node
that joins the group
Software Modules
FAULT
CONSENSUS
DETECTION
SYSTEM
DD-LMP
GROUP
MANAGER
STATE
COLLECTION
POWER
MANAGEMENT
Peer SST
Peer SST
A new node forms a
new group with itself
as leader
Election
between the
leaders of
subgroups to
merge into a
single group
Features
Inherently Fault-Tolerant
Reconfigurable & Scalable
Manages system state for
broker software modules
Demo (with power
management)
Network
partition due
to failures
leads to
election
within
subgroups
Leader node
Failed node
Member node
New node
Major Year 1-3
Accomplishments
DGI @ SST
State Collection
Fundamental Problem in
Distributed Systems
Collect a causally consistent
state of the SST nodes
within a group
Chandy-Lamport Algorithm
•
Circulates a causal marker
Features
Collects the load state
Collects program variables
for fault detection
Integrated for all message
traffic within the broker
DD-LMP
GROUP
MANAGER
Software Modules
FAULT
CONSENSUS
DETECTION
SYSTEM
STATE
COLLECTION
POWER
MANAGEMENT
Peer SST
Peer SST
Inconsistent
Consistent State
SST 0
SST 1
SST 2
SST 3
DGI Progress
Messages
Messages
are
events
recorded
are
recorded
as received
in causal order
before they
are sent (at SST 3)
Major Year 1-3
Accomplishments
DGI @ SST
Development of D-LMP
(from SMC, Year 3)
Experimentation with
multiple power
management
algorithms (consensus
from SMC Year 2,3)
DD-LMP
GROUP
MANAGER
Software Modules
CONSENSUS
FAULT
SYSTEM
DETECTION
STATE
COLLECTION
POWER
MANAGEMENT
Peer SST
Peer SST
Power System Simulation
Environment with Distributed
Systems Interface to Simulink
and PSCAD/RSCAD (Year 3)
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Major Challenges
The primary significant barrier in the development of DGI
is bridging the Cyber/Physical/Network boundaries.
Power system physics, network stability, and cyber
correctness need to be represented on a common
semantic basis to
1)
2)
3)
4)
create and validate the specification of salient control and
resilience features of FREEDM,
verify the specification of FREEDM’s resilience against models
of the implemented system,
provide test and validation of FREEDM’s operation,
assess the risks of and threats to FREEDM’s operation.
10
Response to 2010 SV:
Actions Taken
SVT: The DGI and SMC subthrusts must work
closely
Technical coordination among SMC, DGI, and Intelligent Energy Management
(IEM) and Intelligent Fault Management (IFM)
Research within SMC and DGI cultivates multiple options
SMC, DGI and RSC involve three very different disciplines: power and control
engineers, software engineers and communication and network engineers.
• Develops significant cross-disciplinary experience
• Possibility to consolidate SMC, DGI and RSC into one cluster and have a
cluster leader with strong domain knowledge to coordinate and lead the
activity.
• DGI has emerged as the driving force drawing from SMC and RSC to create
the operating system for IEM and IFM.
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Related Posters
Y3.F.C1 Project Report – Distributed Control of FREEDM System
Broker Architecture
D-LMP and Consensus
Y3.F.C14 Project Report
Interacting control approach
REU Poster – Group Management System
Information Flow/Security
Demo of DGI Power Management and Reconfiguration
12
Year 4 and Beyond
The goal of the next few years is to integrate the DGI operating system with
the IEM/IFM in the digital testbed using RSC as a delivery mechanism.
Develop lightweight RSC protocols integrated with DGI algorithms for efficiency, fault
tolerance, and security
Interface with the IFM so that faults from the FID cause a reconfiguration of DGI, and faults
detected by DGI are communicated to the FID.
Economic models of D-LMP become part of the software module plug-in of
the DGI broker architecture as Distributed Distribution LMP (DD-LMP).
As the center moves forward, fault
tolerance, correctness and security
considerations are cross-cutting throughout
DGI and RSC.
Ultimately, DGI will be deployed in the distributed green hub and digital
testbed as their operating system.
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