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

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

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

LIBRARY-BASED SCENARIOS

Cassandra platform

Login screen

Main screen

Main panel

LibrariesProjects and

entities

List of projects

List of projects

User library

User library

Cassandra library

Cassandra library

Appliances in Cassandra library

Appliances in Cassandra library

Creating a new project

Creating a new project

Adding a new scenario to our project

Installations can be added by drag’n’drop

from the user library

Persons, Activities, Appliances

Persons, Activities, Appliances

Activity models

Activity models (duration)

Activity models (start time)

Simulation parameters

Simulation parameters

Submit runs

Submit runs

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?

Baseline and test-case scenarios - Change a

set point

Baseline and test-case scenarios - Change

duration

Comparisons

SCENARIOS WITH MODEL TRAINING

Cassandra platform

Training module

Import installation measurements

Import installation measurements

Next step: Disaggregation

Training consumer activity models

Training consumer activity models

Export the models to the platform libraries

Models are visible in the user library

CONSUMER RESPONSE

Cassandra platform

Response models

Modify pricing scheme

Estimate consumer response

Modify pricing scheme

Models are posted to the platform

Models are posted to the platform

Example 1: Response from … to

Example 2: Response from … to

Complete change of habits

After 100 Monte Carlo runs of baseline and

response scenarios

…

Comparison

of runs

CONSUMER SOCIAL NETWORKS

(CSN)

Cassandra platform

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.

A network based on similar

consumption

Select a clustering algorithm

Adjust the clustering

parameters

Clusters appear in different

colors

The different consumer

groups appear

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 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)

Thank you!

Questions?