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November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 1
Energy Systems Research Laboratory, FIU
Design and Simulation Issues for Secure Power Networks as Resilient
Smart Grid Infrastructures
Prof. O. A. [email protected]
Tel: 305-321-5622
Energy Systems Research LaboratoryDepartment of Electrical & Computer Engineering
Florida International UniversityMiami, Florida
Keynote Presentation atIEEE SmartGridComm 2015
November 5, 2015Miami, Florida
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 2
Energy Systems Research Laboratory, FIU
• Management of increased levels of distributed and renewable energy sources. (control challenge)
• Integrating a wide variety of systems governed by different regulations and owned by different entities.(interoperability challenge)
• The variable nature of renewable energy sources. (Generation uncertainty )
• Real time energy forecasting and energy management system for generation and demand balancing. (Demand uncertainty)
• New distributed architectures with many microgrids. (Resiliency)
Challenges of integrating distributed resources
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• Interoperability between different protocols and applications (in software layer).
• Identify the communication network and bandwidth required to collect measurement and control remote sites (Distributed control).
• Data availability (Delay, corrupted data, denial of service,…etc.)
• Data security and privacy
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 3
Energy Systems Research Laboratory, FIU
0 20 40 60 80 100
Power Grid
Water
Nuclear
Government Facilities
Healthcare
Percentage (%)
Sec
tors
Power Grid Cyber Attack RiskTrustworthy Critical Infrastructures
Critical infrastructures increasingly targeted by cybercriminalsSome Governmental initiatives– Identified by NSF as a key research area
– Critical infrastructure protection (CIP) set by the US Presidential Directives
– North American electric reliability corporation (NERC) CIP requirements, 2013
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2009 2010 2011 2012 2013
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Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Smart Grid Cyber Infrastructure
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 4
Energy Systems Research Laboratory, FIU
Smart Meter Security Threats
SMART Meter Vulnerability:• The AMI network is open to external unsecured
environments such as cellular channels, power line carriers and radio signals.
Cellular,Power line modem
Radio Signal (900MHZ)
Adversary
• The AMI can provide a communication path to customer systems such as building management systems (BMS) through the customer gateway.
• If the adversary succeeds in penetrating into the AMI network and pretending to be a valid smart meter management system, he can easily send a disconnect signal to millions of customers.
AMI: Advanced Metering Infrastructure
Dis
conn
ectio
n si
gnal
.In
corr
ect p
rice
Inco
rrec
t Loa
d D
ata
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
ZigBeeWiFi, etc.
Energy Systems Research Laboratory, FIU
Smart Meter Security Threats• In January 16, 2014 Proofpoint, Inc. uncovered
Cyber attack involving conventional household "smart" appliances. The global attack campaign involved more than 750,000 malicious communications coming from more than 100,000 everyday consumer gadgets such as home-networking routers, connected multi-media centers, televisions and at least one refrigerator that had been compromised and used as a platform to launch attacks.
Secure Measures
• The network topology should prevent interaction between customers in the NAN.
• Price signal should be authenticated
• Smart meters use X.509 authentication certificate.
• Most of the smart meters doesn't update the certificate for life time (that is a problem). Example latest discovered bug “Heartbleed” in OpensSSL used to compromise the certificate
Zigbee, Wifi
X.509 Certificate is an Authentication ProtocolBetween Smart Meter and Utility. Uses SSL Certificate
Example: an attack on a customer appliance
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 5
Energy Systems Research Laboratory, FIU
Smart Grid Cyber Infrastructure (FAN Threats)
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Field Area Network (FAN)• FAN shared multi service IP
network cover Distribution automation, Integrated Distributed resources, Demand Response and field devices
• Based on Broad Band wireless resources. FAN routers has WIFI interface for field technician.
• Data integrity and confidentiality should be ensured for smart meter data and field devices.
• If adversary succeed to compromise FAN router the intruder could easily send wrong signal to switches or field devices NIST reference Model
NIST Publication 1108 Page 35
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
FAN routers located on the pole
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 6
Energy Systems Research Laboratory, FIU
Smart Grid Cyber Infrastructure (WAM Threats)
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Security challenges:• Most of the protocols were developed for efficient data
transmission in isolated control network without considering the security required for wide spread and open system.
• Phasor Measurement units PMU depend on external clock source which can be spoofed or jammed.
• PMU protocols ( C37.118 and IEEE 1334 ) doesn't support authentication.
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Spoof
Network Attack
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 7
Energy Systems Research Laboratory, FIU
• State estimator can detect bad data form faulty meters or communication errors
• Stealth attack can be designed to be hidden from state estimator.
• Several types of stealth attack can be performed against state estimator such as (state, framing and topology attack)
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Bad data from faulty meter
Bad data Identified
State estimator stealth attack
Bad data not identified
Energy Systems Research Laboratory, FIU
To design security aware WAM, different factors should be considered in the communication and system design such as:
Data authentication (insure the source of the Data)
Data integrity (detect corrupted or changed data)
Proper location of highly secured and encrypt meters to prevent state estimator attack.
Data mining techniques could be used to detect altered data.
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 8
Energy Systems Research Laboratory, FIU
• Cyber Physical security should not only be considered in the cyber component but also the power system network topology should be designed to be resilient in cases of attack.
• The control system should be designed to withstand cyber attack and cyber component failures.
• Centralized control suffer from single point of failure problems.
• Successful attack against centralized control system could lead to serious damage and loss of service
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• Decentralized control reduce the risk of single point of failures and loss of service.
• Risk of attacking area and loss of service still high
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 9
Energy Systems Research Laboratory, FIU
• Distributed control minimize the risk of cyber attack.
• Each node exchange information and cooperate with neighbor node to improve the system stability.
• Attack detection can be improved by data mining from different sources
completely distributed multi-agent control
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• The types and levels of data protection used to encrypt or authenticate signals should be coordinated with signal sensitivity and impact on the system stability.
• The attack detection should rely on physical system characteristics as well as the cyber security rules
• Cyber attack countermeasures should consider the dynamics and the special nature of the power system.
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 10
Energy Systems Research Laboratory, FIU
• We need new modeling and simulation tools to capture the dynamic nature of both cyber and physical components.
• We need test bed facility that will provide the ability to perform experiments involving integration of different technologies in one system (communication, software and physical components)
• Simulation tools and test bed implementations should provide the ability to test different types of vulnerability and Launch attack scenarios
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• Complex cyber physical infrastructure environment is required for identifying possible vulnerabilities and testing solutions
• The infrastructure should provide modular and flexible structure to implement different physical topologies and operational scenarios
• The test environment should seamlessly integrate with different protocols and support interoperability (standards???).
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 11
Energy Systems Research Laboratory, FIU
Our verification Platform–The Test Bed has the following capabilities and components:
Phasor measurement Units monitoring, protection, and control
Distributed and renewable energy sources wind, solar, Fuel cells, etc.
New operational schemes protective digital relaying Wide Area Protection
Intelligent protection schemes and their application for Prevent cascading outages Islanding situations Grid blackout
Emulation of Plug-In-Hybrid and Electric Vehicles (PHEVs) and (PEVs) Energy Storage systems, SOC and SOH for batteries
Integration of Hybrid AC-DC systems micro grid solutions for residential and industrial applications. Enhancement of Energy Efficiency and EMS
Cyber infrastructure Communication network, servers, communication protocols, HIL
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
So, Various Composable Modules areIntegrated in the Test Bed
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 12
Energy Systems Research Laboratory, FIU
IEC61850 Relays
Transmission lines
Buses
Synchronizers
SCADA
PMUs
Battery ChargingAnd
PEV system
Pulse load/super cap. micro grid
DC architecture
Software platform
Battery management
system
Wind, PV, Storage microgrid
Prof. O. A. Mohammed.
Energy Systems Research Laboratory, FIU
Configurable transmission Network
Remote controlCircuit Breaker
Remote controlload emulator
Synchronous generatorand control agent
Hybrid MicrogridDC Microgrid
Communication network
LinuxMulti Agent
Communication Protocols
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 13
Energy Systems Research Laboratory, FIU
• Communication middleware is required to enable information exchange between different controllers.
• should provide portability and interoperability between different system component.
• should provide time predictable performance, low latency and overhead to meet the real time application requirements.
• The communication middleware must support large system expansion and adding new types of data.
• The Communication Middleware could be message centric or data centric
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• Message centric middleware enables different nodes to send messages to each other without regard to physical location or message contents.
• Messages must be predefined based on required data exchange and operation case which limit the system expansion.
• The application is responsible of insuring correct data format and parsing received information which add extra overhead in development control application.
• Data filtering is done at the application level which lead to poor utilization of network bandwidth.
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 14
Energy Systems Research Laboratory, FIU
• Data centric middleware provide data aware communication approach which overcome the disadvantages of message centric. The message is built by the middleware to exchange and update the system state.
• Messages are derived from the system data model. (no predefined message structure)
• Data format validation and parsing information are done on the middleware level. (reduce the complexity of control application)
• Data filtering is done at the middleware level which improve the utilization of the network bandwidth.
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Efforts saved By
Data centric
Middleware
Dat
a ce
ntr
ic is
ch
ose
n t
o b
e U
sed
at
th
e sm
art
gri
d T
est
bed
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Emphasized by Industry (see Smart grid
Interoperability Panel)
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 15
Energy Systems Research Laboratory, FIU
• Data Distribution service is a communication standard based on data centric and publisher subscriber approach created by Object Management Group (OMG).
• Supported By Standard application Programming Interface API which simplify integration with different applications.
• Utilize real time publisher subscriber protocol (RTPS)
• IEC 61850 implements RTPS communication.
(provide interoperability between different vendors)Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• No message broker or server which avoid single point of failure.
Communication failure
DDS DATA BUS
Client server communication schema
• Single point of failure• Low update rate• High latency
DDS publisher/subscriber communication schema
• Reliable communication (no single point of failure)• High update rate• Low latency (no intermediate message broker)
Tra
nsm
ittin
g no
des
Transmitting nodes Receiving nodes
Rec
eivi
ng n
odes
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 16
Energy Systems Research Laboratory, FIU
Unicast communication• Multiple stream for multiple
destination• Consume high bandwidth• Not suitable for remote or
distributed control where multiple agents need to access the same data
• Multiple copy of the same data sent from the source to Each distention.
• Consume high bandwidth
• Not suitable for Wide area measurement since allocated bandwidth for remote site usually low.
• Transmitting multiple stream add extra processing overhead on the transmitting nodes and reduce the update rate
Three copy of the same data
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• Single stream for all destination
• Reduce the network bandwidth
• Reduce the processor overhead
• Suitable for low bandwidth link and remote sites
• Reach set of Quality of Services profiles QoS (Predictable delivery)
• QoS defines the data transmission priority, life time, ordering based on time stamp and allowed latency
Multi cast communication• Single stream for multiple
destination• Optimize network bandwidth• suitable for remote or distributed
control where multiple agents need to access the same data
Single copy of the data
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 17
Energy Systems Research Laboratory, FIU
DDS Gatewy
DAQ/RTU
DATABASE
Distributed Data service DDS
DDS Gatewy
PROTECTION RELAYS
DDS Gatewy
LOAD EMULATORES
DDS Gatewy
GENERATION CONTROL
DDS Gatewy
RENEWABLE ENERGY EMULATORS
DDS Gatewy
Power system analysis SW packages
DDS Gatewy
Smart Meters
DDS Gatewy
ENERGY STORAGE
MANAGMEN
DDS Gatewy
DEMAND SIDE MANAGMENT
The gateway is the bridge between different types of protocols and DDS
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• Performance tests were performed to measure the latency and maximum possible update rate for the implemented DDS.
• 10,000 messages were sent with different message rate (from 50 to 1000 Message/sec) and the delay time is observed.
• The test was repeated with different message size (from 32 B-63 kB)
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 18
Energy Systems Research Laboratory, FIU
Performance Test for DDS Unicast and Best effort QoS.
Performance Test for DDS Multicastand Best effort QoS
Max 1.2 ms delay Max 1.4 ms delay
Max 0.3 ms delay
Higher message size Higher message size
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Max 0.35 ms delay
Energy Systems Research Laboratory, FIU
Micro Grid Component Infrastructure
• DC Microgrids Components– Modular MIBBC– Battery Bank– Programmable Load emulator– DC bus module– High Freq. Inverter– more
• Hybrid PEVs Charging system Components
– LC Filter– Bidirectional ac/dc converter– Bidirectional dc/dc converter– Hardware Overview– Lithium-ion Battery– Management,
Diagnostics Software
• AC/DC interconnected network components
– Uncontrolled rectifier
– Dynamic load emulation
– AC Filter
– DC Filter
– DC/Dc Boost Converter
– AC/DC Measurements and Protection
– DC Power Module
– Medium voltage DC Transmission line model
• Components of Microgrids for pulse load studies
– Super capacitor bank– Bidirectional converter– Multi port Boost Converter– Lead Acid Battery Bank– Programmable DC Load
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 19
Energy Systems Research Laboratory, FIU
Smart Grid Test-bed Components (The CPS infrastructure)• Distributed control components
– Embedded agent platform– HIL simulators– DDS infrastructure– Smart Meters– Developed Interface library
• Phasor measurement Components– PMUs– PDCs– RTACs– Interface for control and protection modules– Real time phasor data server
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Hybrid HW/SW CPS Simulation Environment
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA
High Level ArchitectureIEEE Standard for
Federated Simulation
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 20
Energy Systems Research Laboratory, FIU
Test Bed Interface Library• Interface Library developed to
provide control function and data collection capability from local and remote network
• Real time publisher subscriber protocol (RTPS) insure interoperability
• Provide Flexible environment for Distributed control test and validation
• Currently available interface for generators, Micro Grids, CB, measurement nodes, PMU, Load emulators and renewable energy emulators
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Generator block (slack mode) provide
interface to• Start and shutdown the
generator• Control generator speed• Read terminal voltage, line
current and frequency in real time
Generator block (Power control mode) provide
interface to• Start, shutdown and
synchronize the generator• Control generator torque• Read terminal voltage, line
current and frequency in real time
Microgrid blockprovide interface to
• Control active and reactive power flow from the Micro grid.
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 21
Energy Systems Research Laboratory, FIU
Wind turbine emulatorprovide interface to
• Control wind speed• active and reactive
power reference• Voltage and current
feedback in real time
PV emulatorprovide interface to
• Control the PV panel temperature and irradiance
• Voltage and current feedback in real time
Load emulatorprovide interface to
• Load active and reactive power
Network configuration block
Bus measurement block Circuit Breaker control block
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• To ensure proper operation and initialization an automated startup algorithm where developed using finite state machine.
• The controller is built using state flow toolbox
• The automated startup algorithm is divide into two layer.
• The top layer (supervisory layer) which monitor the state of the CB and generators and ensure correct startup sequence
• The bottom layer which handle the generators startup and synchronization process
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 22
Energy Systems Research Laboratory, FIU
Generator in Pcontrol mode
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Control algorithm modeled by Simulink
Developed interface library
Control signal
Con
trol
sig
nal
Control signal
Feedback Fee
dbac
k
Feedback
SIMULATION
Real System
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Different types of attacks can be performed on actual comm.
network
Attack models can be simulated in real time(e.g. false data injection, delayed attack, …)
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 23
Energy Systems Research Laboratory, FIU
Generator Interface Block
Load emulatorsInterface Block
Bus measurements Interface Block
Control Model
Load pattern
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
0 20 40 60 80 100 120 140 160 1800
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Time(sec)
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z)
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)
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Time (sec)
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Time (sec)
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mp)
Bus voltageGenerator Frequency
LoadGenerator Current
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 24
Energy Systems Research Laboratory, FIU
Multi Agent Data Information Model for Power Systems
Decentralized control is established using multi agent frameworks
Agents interact and cooperate to achieve a global or local objective (through an optimization function)
In future active distribution networks, simultaneous power system operations will be controlled by the system operator and private microgrid operator entities:
• Frequency and voltage support (Ancillary Service) • Online DER Scheduling (Optimal Dispatch) • Market models (Auctions, Dynamic Pricing)
There is a need to perform concurrent control. Multi agent control applications are required.
Agent Entity
Peer-to-peer Communication
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
• An agent needs to interact with its environment through sensors and actuators.
• A sensor acquires the data from the outside world and the actuator responds according to the agent’s decision.
Agent Platform
Sensors
Decision Making
Actuators
Environment
Perception
Action
How Can We Link Power System Physical Objects to Agent Platforms?
• For Actual Multi Agent Field Implementation :Need to link agent objects to distributed industrial control systems.
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 25
Energy Systems Research Laboratory, FIU
Can IEC 61850 Meet Decentralized Control of Active Distribution Network Demands?
The smart grid concept covers an extensive control, automation and protection applications.
IEC 61850 does not meet all the required forms of monitoring and information exchange demands.
Active distribution networks require dynamic adjustment of primary, secondary and tertiarycontrol levels.
• Frequency and voltage support (Ancillary Service) • Online DER Scheduling(Optimal Dispatch) • Market models (Auctions, Dynamic Pricing)
Advanced intelligent multi agent frameworks are necessary with a flexible ability to create tailor‐made decentralized control schemes while allowing the legacy protocols.
AESPO Agent
Microgrid Agent
DER Agent
Microgrid Agent
DER Agent
Microgrid Agent
DER Agent
DER Agent
DER Agent
DER Agent
Tertiary Level Control
Agent Communication
Secondary Level Control
Agent Communication
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Agent codes are developed and performed in real‐time power system applications
OPC UAMIDDLEWARE
Cloud Communication
Interface
Client / Server
Java ClientFIPA Messages
IEC 61850Manufacturing Message Specification (MMS)
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
MULTI AGENT FRAMEWORK
The foundation for intelligent
physical agents (FIPA)
November 2015
Prof. O. A. Mohammed, IEEE SmartGridComm_Keynote, Miami, FL USA 26
Energy Systems Research Laboratory, FIU
Proposed Multi Agent Framework The foundation for intelligent
physical agents (FIPA) is an organization which intends to evolve inter-operable agent communications with semantically meaningful messages, such as how messages are transferred and presented as objects.
Taking the specific benefits of two major frameworks, We want to provide a flexible framework for active distribution network application layers
Merging IEC 61850, FIPA and the open connectivity unified architecture (OPC UA) standards
OPC UA a middleware for abstracting various IED protocols into an interoperable interface for secure and reliable data exchange.
OPC UAMIDDLEWARE
Cloud Communication
Interface
Client / Server
Java ClientFIPA Messages
IEC 61850Manufacturing Message Specification (MMS)
Prof. O. A, Mohammed, IEEE SmartGridComm, Miami, FL USA
Energy Systems Research Laboratory, FIU
Conclusions• The smart grid requires new set of modeling, simulation and
experimental tools to implement and validate new designs.• The smart grid test bed provide unique integrated environment for
testing developed techniques involving cyber and physical component
• The DDS provide real time performance and distributed architecture which simplify the data exchange and control implementation.
• The RTPS ensure the interoperability between different nodes• The interface library for the smart grid test-bed provide flexible
and powerful tools to integrate with simulation packages.• The federation simulation provide flexible tool for co-simulation of
CPS system to identify full system behavior. • Agent based control schemes provide decentralized operation
capability for power systems with data information modeling and protocols.
Prof. O. A. Mohammed, IEEE SmartGridComm, Miami, FL USA