the cassandra platform - christos diou

Cassandra platform

Christos DiouPostdoctoral Researcher

Information Technologies Institute

(CERTH-ITI)

Cassandra platform – Christos Diou

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

• NoI members and the platform

Cassandra 1st Webinar 2


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

– Apache license

• Your feedback is highly appreciated!


LIBRARY-BASED SCENARIOSCassandra platform – Alpha version



Login screen



Main screen


Projects and entities

Main panel

Libraries


List of projects



User library



Cassandra library



Appliances in Cassandra library



Creating a new project



Adding a new scenario to our project



In this case, Installations are added by drag n’ drop from the user library



Persons, Activities and Appliances



Activity models



Activity models (duration)



Activity models (start time)



Simulation parameters



Submit runs



What if…• The residents of Apartment 1 use the water heater less

– Because they have installed solar water heating

• The residents of Apartment 2 use their air conditioning unit less

– Because they have upgraded their apartment’s thermal insulation properties

• The residents of Apartment 3 replace their refrigeration unit



Behaviour change in Apartment 1



Appliance change in Apartment 3



Submit new runs with same parameters



Compare the runs (graph)



Compare the runs (KPIs)



One step further

• Library-based scenarios can be used to simulate working hypotheses

• The real power of Cassandra is in its disaggregation and model training functionality


MODEL TRAININGCassandra platform – Alpha version



Training module (to be integrated)



Import installation measurements



Next step: Disaggregation



Training consumer activity models



Export the models to the platform libraries



Models are visible in the user library


CONSUMER RESPONSECassandra platform – Alpha version



Response models



Modify pricing scheme



Estimate consumer response



Models are posted to the platform



Example 1: Response from



from … to:



Example 2: Response from



from … to:


CONSUMER SOCIAL NETWORKS (CSN)

Cassandra platform – Alpha version



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


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


The main graphical interface of the CSN module

The network can be created based on Installation Type,

Person Type, Average, Peak, Similar, or Dissimilar Consumption, etc.

CSNetwork based on person type. Persons of the same

type are linked.

By changing the visualization layout algorithm….

The two different person types appear

Visualization is Important!!!

A new network based on Peak Consumption similarity

We select the clustering algorithm to use

Clusters appear in different colours

By grouping clusters…

The different consumer groups appear

Another network based on similar consumption

Change the edge threshold via the appropriate slider

Select a clustering algorithm

Clusters appear in different colors

Various statistics are available, as well as the

consumption and information of selected nodes

Sliders for minimum edge weight and clustering values


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


So, what’s next?

• Beta release is planned for October, 2013

• Integration of external modules with the platform

• Evaluation of Cassandra in our three project pilot cases

• Evaluation of Cassandra in a limited number of NoI pilots (external evaluation)

• We can use Cassandra to simulate your context and benchmark a number of working scenarios.

– Use measurements and the training module to model your context

– Simulate a range of scenarios appropriate for your business case

– Prepare an analysis/report of our findings

– Ask for your feedback

– Improve the platform based on your comments


Thank you!

Questions?

the cassandra platform - christos diou

Technology

platform librariescassandra

alpha platform version

real power of cassandra

open source platform

residents of apartment

new projectcassandra

response fromcassandra

new scenario