Transcript Document

Project 3.4
Integrated Data Management and Portals
Dr. Hassan Farhangi, Dr. Ali Palizban, Dr. Mehrdad Saif, Dr.
Siamak Arzanpour, Dr. Mehrdad Moallem and Dr. Daniel Lee
Students: Moein Manbachi, Maryam Nasri and Babak Shahabi
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• Static Volt/VAR Optimization
Conventional Distribution • Conservation Voltage Reduction
Loss Reduction Methods
Smart Meters
Volt/VAR Optimization
Conservation Voltage
Reduction (CVR)
• Consumption Data
• Real-time V/I/PF Data
• Dynamic Voltage Optimization
• Dynamic VAR Reduction
• Dynamic consumer Voltage Reduction
• Adaptive VRs and Transformer LTCs
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Adaptive
Real-Time
CVR and
Volt/VAR
Optimization
Typical Electricity Distribution Network
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Static (Pre-programmed and independent of real-time events)
Un-Intelligent (Absence of embedded device-level processing)
Independent Functions and constraints
Conventional
VVO and CVR
Individual Volt/VAR device settings and control
Absence of system-wide visibility and monitoring
Absence of system-wide synchronization and coordination
Absence of automatic Fault Recognition and Restoration
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Opportunity:
Could Smart Meters facilitate the evolution
of Static VVO/CVR to Dynamic & Adaptive
VVO/CVR?
Challenges:
 Management of massive amount of realtime data generated by Smart Meters
 Dynamic, Adaptive & Cost-Effective
Volt/VAR Optimization Algorithms
 Distributed Command & Control
 Suitable Communication Protocols
 Data Base and Portal Architecture
Proposed
Solution
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Adaptive &
Dynamic
CVR &
Volt/VAR
Optimization
Real-time (On-Demand or Event Based)
Intelligent Agents (Multi-Agent Technologies)
New Proposed
Intelligent
Agent-based
VVO/CVR
Optimization Algorithm multi-O.F and multi-constraints
Dynamic control of Volt/VAR components
Reliable and Secure Communication Network
System-wide situational awareness
Pre-emptive/self healing Distribution Network
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VVO/CVR Intelligent Agent Primary Structure
Receive Data
Data from specific
feeder
Data from
neighboring Agents
Database
(Receiving Goose)
VVO Engine (VVOE)
Send Commands
Solving real-time
VVO/CVR
Objective Function
based on dist.
Network
constraints
VVOE Algorithm
Re-configure
distribution
network
Optimize system
operation
(Sending Goose)
Goose /other Protocols
Downstream
Agents
Upstream
Agents
Control
Center
Distribution
Network
IEDs
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Intelligent
Agents
Real-time Data Processing
System Anatomy
Need for peer-to-peer Messaging and
Negotiations
No Central Supervisor
Dynamic changes in load profile
Different Types of data: INFORM,
LEAKAGE, ALARM
Real-time operating system
Various smart components: Sensors,
Smart-meters
Database structure for storage and mining
of system wide data
Limitation of smart-meter memory size
Data aggregation and data filtering in
nodes.
Solution: Intelligent Agents
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IEC-61850 Goose Messaging Over PLC
Goose Messaging
• Data Exchange
between
substation
components
• Self-describing
objects and
functions (IEC61850)
Communication
Structure
• PLC: Taking
advantage of
the existing
media
connecting
distribution
components
• Standard
communication
protocol
between smartmeters and
substation
Barriers
• PLC has a
hostile medium
with severe
noise and
attenuation
• PLC signal is
attenuated
significantly
after crossing
MV/LV
transformer.
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Design realtime VVO
Engine
(Algorithms)
PLC signal
attenuation in
step down
distribution
transformers
Bandwidth
demand for
the
application
layer
Data
Aggregation,
Management
and Selection
Project
Gaps and
Challenges
Have IEC
61850 Goose
beyond Dist.
Substation
Database
Architecture
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Optimal
Agent
Topology
Thank You
Questions?
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