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AMI to SmartGrid “DATA”
October 20, 2011 John A Sotak – National Technical Sales Manager - Sensus
Smart Grid Communication Data Network Sources
EPRI
CONFIDENTIAL
Transformation of Data Producing Products
Common Data
Producers
Meter Reads - Monthly
OMS systems - reactive
 Work order management
systems - reactive
SmartGrid Data
Producers (Real-time)
Meter Reads – hourly / 15 minute
OMS systems – real time
 Work order mgmt systems – real time
Billing
GIS
SCADA – Real-time
Distributed Energy storage devices
Distributed Power Generators
Billing
GIS
SCADA – Real-time
Flexible demand response programs
Distribution automation (pro-active)
FCI
Relays
Sub-stations
Transformer
Price signals (Real-time)
Customer info & notifications (Real-time)
PHEV charging criteria
CONFIDENTIAL
3
Impact of Data Producers
Data volumes will
increase 3,000x!
What makes a smart grid
SMART is precisely what
causes so much difficulty:
Information volume
DATA, DATA, DATA !!!
Installed base of
smart technologies
• Smart grid data volumes can be 3,000x what we are used to handling
• It is far more than just meter data - many new smart devices and data types
• Utilities need new tools, architectures, processes to manage smart grid data
CONFIDENTIAL
4
SmartGrid Data Sources
• Meter Usage Data: data representing condition
or behavior of assets. Including: total usage,
average demand, peak demand, TOU, peak
demands. Additionally; voltages, power flows,
power factor, & power quality data
• Operational Data: electrical behavior of the grid
data; voltage & current phasors, real & reactive
power flow, demand response capacity, power
flows, real time forecasting of the operational
data
CONFIDENTIAL
5
SmartGrid Data Sources
• Event Message Data: asynchronous event
messages from grid devices; outage &
restoration messages, fault circuit messages,
non-standard event notice messages.
• Non-Operational Data: conditional behavior of
grid assets; power quality & reliability data; asset
stressor data; utilization data; additional work
asset type of non-direct data.
• Meta-Data: “KEY INTERPRETATION DATA”;
grid connectivity, network addresses & groups,
calibration constants, normalization factors,
network parameters & protocols.
CONFIDENTIAL
6
Critical Comms Criteria: Latency NOT Bandwidth
High
Business Repository data
L
A
T
E
N
C
Y
Days - Months
Business Intelligence
Dashboard & reports
Enterprise
Operations
Historical data
Minutes - days
Op/Non-Op data
Sec. – sub minute
SmartGrid Data Producers
Milli-sub seconds
Transactional Analytics
Reporting systems & processes
Real-time Analytics
Visualization systems & processes
Business Intelligence
Protection & Control Systems
Low
CONFIDENTIAL
7
SmartGrid Data Latency Examples
CONFIDENTIAL
Solving the Massive DATA
Apps/Svcs
Delivery System
Application
Based
Risk
DATA Everywhere!
CONFIDENTIAL
Reward
3 CSFs
Usability
Usability
Usability
Unified
DATA Warehousing
Solving the Massive Data Requirements
• Matching data acquisition infrastructure to required outcomes
– Number, kind, and placement of data measurement devices
– Communication networks and data collection engines
• Learning to apply new tools, standards, and architectures to manage
grid data at scale
– New open standards for interoperability
– Distributed architectures
– New analytics tools
• Transforming business processes to take advantage of smart grid
technology
CONFIDENTIAL
10
Processing Tools for the Data: Complex Event
Based & Event Stream Based
• SmartGrid devices and systems increasingly generate
asynchronous event messages
– Such event messages tend to come in bursts and floods when
something (usually bad) is happening on the grid
– Normal operations also generate event message streams
• Processing event streams requires a different approach
– Standard approaches use dynamic queries against (more or less) static data
– New approach continually runs static queries against dynamic data streams
• Two forms of Platform Based Processing: ESP and CEP
– ESP – Event Stream Processing – single stream
– CEP – Complex Event Processing – multiple streams
• Commercial platforms exist for implementation: CEP engines and
development tools; CEP rule bases support other developed business
processes (Look at the telecom, stock market, or Homeland Security)
CONFIDENTIAL
11
Complex Event
Processing Use Cases
Telecommunications &
Services
Customer Centric
Utilities
• Manage your data before it
reaches the databases
• Protect your core business
processes from the “data
tsunami”
Financial Services
Homeland Security
Security and Detection
CONFIDENTIAL
Low Latency Processing
Best Practices: Pre-Deployment Planning
Pre-deployment Analytics ensure accurate Scenario Planning,
turning terabits of Meaningful Metadata into useful tools
•
•
•
•
Distributed real-time analysis
Actionable business intelligence
Network optimized data-flows
Organic analytic processes
CONFIDENTIAL
•
•
•
•
•
Economic Modeling
Business Modeling
Measurable outputs
Scalability Validation
Rate Case Rationalization
Smart Grid Data Management Tips
• Look at the entire SmartGrid data, not just AMI.
• Recognize smart grid data volume and classes.
• Link business process transformation and
SmartGrid designs.
• Look to other tools like “CEP” to handle new
classes of data.
CONFIDENTIAL
14
Item to be Aware of:
•
Don’t underestimate the data associated with AMI and SmartGrid
Producers
•
Data ownership.
•
Data usage is becoming more critical.
•
Data accuracy and quality increases as automation increases.
•
Asynchronous Data is increasing.
•
Data Volume – More is not always better (be aware of latency vs volume).
–
–
–
CONFIDENTIAL
Protect your business logic
• What filtering, correlation, aggregation can be done up front?
• What events are critical, can be ignored, or can be processed
later?
Map your architecture to scale
• Ensure high availability
• Understand the impact of maximum throughput
• Monitor and measure system performance
Prototype and tune
• Simulation, record-playback, what-if scenarios
15
DATA, DATA, DATA!!!
“Any intelligent fool can make
things bigger and more complex...
It takes a touch of genius - and a
lot of courage to move in the
opposite direction”.
Albert Einstein
CONFIDENTIAL
16
Questions
17
CONFIDENTIAL