3. christos diou (certh/iti) - outline of the platform’s operation and main features
DESCRIPTION
First CASSANDRA Workshop PresentationTRANSCRIPT
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Cassandra platform
Christos Diou
Kyriakos Chatzidimitriou
Postdoctoral research associates
CERTH/ITI
A multivariate platform for assessing the impact of
strategic decisions in electric power systems
1st CASSANDRA
Workshop
Coventry, 11 September, 2013
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Outline
• Library-based scenarios in the alpha platform version
– Use pre-existing library components
• Measurement-based scenarios
– Model training to build models automatically
• Response models
– Consumer response to different incentives
• Consumer Social Network analysis
– Grouping of small-scale consumers into Consumer Social Networks
• Development status and next steps
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About the platform
• Currently in alpha version, development is highly active
– Some functionality has not been integrated yet
• Open source platform, publicly available through GitHub
– http://github.com/cassandra-project
– Apache license 2.0
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LIBRARY-BASED SCENARIOS
Cassandra platform
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Login screen
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Main screen
Main panel
LibrariesProjects and
entities
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List of projects
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List of projects
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User library
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User library
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Cassandra library
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Cassandra library
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Appliances in Cassandra library
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Appliances in Cassandra library
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Creating a new project
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Creating a new project
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Adding a new scenario to our project
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Installations can be added by drag’n’drop
from the user library
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Persons, Activities, Appliances
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Persons, Activities, Appliances
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Activity models
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Activity models (duration)
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Activity models (start time)
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Simulation parameters
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Simulation parameters
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Submit runs
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Submit runs
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Scenario 1: A mall
• What if …
– Roof-Top-Units (RTUs) are shut down 1 hour prior to mall closing time
taking advantage of thermal inertia in the sales area?
– Gradually start A/C units from 08:00-09:00?
– Set points from 21 to 24 degrees Celsius?
– Shut down all office A/Cs after 22:00 with manual override?
– Set the minimum fresh air from 20% to 5%?
– Change escalators from always on to escalators with motion sensors?
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Baseline and test-case scenarios - Change a
set point
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Baseline and test-case scenarios - Change
duration
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Comparisons
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SCENARIOS WITH MODEL TRAINING
Cassandra platform
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Training module
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Import installation measurements
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Import installation measurements
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Next step: Disaggregation
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Training consumer activity models
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Training consumer activity models
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Export the models to the platform libraries
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Models are visible in the user library
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CONSUMER RESPONSE
Cassandra platform
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Response models
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Modify pricing scheme
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Estimate consumer response
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Modify pricing scheme
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Models are posted to the platform
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Models are posted to the platform
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Example 1: Response from … to
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Example 2: Response from … to
Complete change of habits
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After 100 Monte Carlo runs of baseline and
response scenarios
…
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Comparison
of runs
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CONSUMER SOCIAL NETWORKS
(CSN)
Cassandra platform
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CSNs
• Groups of similar consumers
– Multiple similarity criteria
• CSNs have potential:
– Increased market power of aggregated small-scale consumers
– Coordination of consumption activities at group level
– Targeted incentives at group level
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CSN module
• CSN module: A tool for identifying links and grouping of consumers in
a meaningful way
– Existing social network connections
– Explicit attributes (e.g. working, non-working person, locality in the grid
topology)
– Implicit attributes (e.g. consumption similarity, peak similarity, behavioural
similarity)
• Early version implemented for experimentation
• Next version:
– More similarity criteria
– Estimation of group response to incentives
– GUI integration
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The main graphical interface
of the CSN module
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The network can be created
based on Installation Type,
Person Type, Average, Peak,
Similar, or Dissimilar
Consumption, etc.
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CSNetwork based on person
type. Persons of the same
type are linked.
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A network based on similar
consumption
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Select a clustering algorithm
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Adjust the clustering
parameters
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Clusters appear in different
colors
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The different consumer
groups appear
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In summary, with Cassandra you can
• Simulate working scenarios/pilots
• Benchmark different energy efficiency solutions/products in simulation
before testing them in real-life
• Create detailed models that describe consumer behaviour
• Identify and evaluate optimal consumption schedules
• Estimate consumer response to a range of incentives
– Pricing schemes
– Consumer awareness
– Environmental impact
• Identify meaningful consumer groups and benchmark the application
of targeted incentives
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So, what’s next?
• Beta release is expected before the end of 2013
• Further development and integration of response and CSN modules
• Integration of external modules with the platform
– thermal controllers, lighting models
• Evaluation of Cassandra in our three project pilot cases
• Evaluation of Cassandra in a limited number of NoI pilots (external
evaluation)
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Thank you!
Questions?