First Cassandra Webinar Presentation

Cassandra Network of
Interest Webinar
Welcome to Cassandra
A multivariate platform for assessing the impact
of strategic decisions in electric power systems

Welcome to the Cassandra Webinar
 During this Webinar we will review:
 2. Concept and theoretical aspects of CASSANDRA
– By Giorgos Andreou, Lecturer at Power Systems Laboratory Department
of Electrical and Computer Engineering Aristotle University of
Thessaloniki
 3. Explanation and demonstration of CASSANDRA Modeling
Platform
– - By Christos Diou, Postdoctoral Research Associate at Centre for
Research and Technology Hellas ITI - CERTH
 4. Next steps and opportunities in platform development
for NOI Members
 5. Questions
Cassandra Webinar Network of
Interest
2June 11, 2013

Network of Interest
 Bring together stakeholders who can provide insight on
possible user requirements
 Form a community of possible users
 Allow companies to either test the platform or have their data
processed
 Enable interested parties to adapt this open source platform for
commercial use
Cassandra 1st Project Review 3Brussels, 11 Jan 2013

Cassandra at a glance
Duration: 30 months
Partners: 9
1 Research Center, 5 Universities, 3 SMEs
Person-months: 340,5
Workpackages: 8
Deliverables: 39
Requested EC
contribution: 2,834M€

Power System Status – the near future
 Lack of tools for modeling the new Power System status
 Inability to aggregate the market power of small-scale consumers
 Necessity for dynamic models for assessing the impact of actions
and policies to be applied
 Decentralized, small-scale
production sites
 Renewable energy
 Market liberation
 Smart grid
 More players involved
Big market potential unexploited!

The Consumer
 Individual consumption is insignificant with respect to the
consumption of “bigger” players (Industrial, Commercial,
Public Service, Recreational)
 However aggregate small-scale consumption is significant
– Entire residential and large part of the commercial sector
 In fact, consumer modeling is difficult to achieve, due to:
– Lack of metering equipment (i.e. smart meters)
– Inability to model consumer activities
– Inability to model response to incentives (Demand side)

Filling the gap… Cassandra!
A software platform for modeling the energy
market from an end user perspective
 Main Cassandra objectives:
1. Theoretical and software modeling of stakeholders in terms of
energy profiles and consumption patterns, as well as their
interactions
2. Increase the market power of low level consumers through
Consumer coalitions (Consumer Social Networks - CSNs)
3. A Key Performance Indicator (KPI) methodology, in order to
assess energy performance and CO2 emissions reduction
4. A modular, expandable software platform to model and
benchmark scenarios and act as a Decision making tool.

Cassandra
Theoretical Modelling
Georgios Andreou
Aristotle
University of
Thessaloniki

Power Distribution Network
9Cassandra Project 1st Webinar June 11, 2013
Small Industry
MV/LV Power
Transformer
Commercial
MV/LV Power
Transformer
MV/LV Power
Transformer
Residential
Residential
Commercial
Commercial
Overhead or Underground
Power Lines
HV/MV Power
Substation
Residential

Power Distribution Network
• Consumer Side (Demand Side)
• Demand Side Management
– Consumption optimization
– Energy efficiency
– Profit
• Problems
– Which is the profile of each
consumer?
– How to cluster/categorize
consumers?
– Which DSM program/incentive to offer
to each consumer?

Cassandra as a solution
• A helping hand in order to:
– Simulate the consumption of consumer populations,
– Understand behaviors that drive consumption,
– Cluster consumers into groups for more efficient incentivisation,
– Simulate consumer response to specific Demand Response programs
• Two modeling approaches:
– Input based on demographic data → aggregate results for a consumer
population
– Input based on consumer level measurements → bottom-up approach
with results regarding individual consumers and/or consumer
populations

Basic modeling concepts
• Reality:
– Installation (Aggregation of all the appliances installed within the
premises of a consumer).
– Person(s) performing activities by the use of appliances according to
their utility.
– Person(s) have habits (recurrent behaviour).
– Person(s) receive incentives to modify consumption, and choose either
to respond or not according to their utility.

Basic modeling concepts
• Modeling:
– An Installation consists of its Appliances.
– Measurements of the installation are used in order to determine its
Appliances, as well as the consumer Activities (Disaggregation
procedure).
– Appliances are described by Consumption Models (mathematical
representations of their active and reactive power consumption).
– Consumer utility is modelled through Utility Models.
– Incentives are modelled through Incentive Models.
– Response is modelled through Response Models.
– Auxiliary Models:
• Pricing Schemes Models
• CO2 Emission Calculation

Functionality according to quality of input
• Basic simulation rule: The more information you offer as input,
the more accurate results you will obtain.
• Demographic data input: The simulation will be based on statistics,
thus it will not produce accurate individual consumer results.
• Measurement data input:
– The Cassandra modeling is based on per minute measurements of
active and reactive power for an installation (loss of information)
– Accuracy of results depends on information compensation.

Cassandra platform
Christos Diou
Postdoctoral 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 16

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 SCENARIOS
Cassandra 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 TRAINING

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 RESPONSE

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)

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

The different consumer
groups appear

Another network based on
similar consumption

Change the edge threshold
via the appropriate slider

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?

First Cassandra Webinar Presentation

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