First CASSANDRA Webinar Presentation

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

description

On June 11th, 2013 we hosted the First CASSANDRA Webinar for NOI Members, titled: "Modeling consumer behaviour from the ground up – A presentation of the CASSANDRA platform" During the Webinar, the platform was explained and demonstrated, and participants had the opportunity to ask questions and discuss the early development of the platform. The presenters and their topics were as follows: 1. Introduction - By Jessica Stromback, Chairman VaasaETT 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 We hope you enjoy the presenters' slides and we look forward to your continued feedback! Sincerely, The CASSANDRA Team

Transcript of First CASSANDRA Webinar Presentation

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Cassandra Network of

Interest Webinar

Welcome to Cassandra

A multivariate platform for assessing the impact

of strategic decisions in electric power systems

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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

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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

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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€

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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!

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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)

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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.

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Cassandra

Theoretical Modelling

Georgios Andreou

Aristotle

University of

Thessaloniki

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Power Distribution Network

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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

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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?

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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

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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.

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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 (Disaggregationprocedure).

– 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

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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.

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Cassandra platform

Christos Diou

Postdoctoral Researcher

Information Technologies Institute

(CERTH-ITI)

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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

• NoI members and the platform

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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

– Apache license

• Your feedback is highly appreciated!

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LIBRARY-BASED SCENARIOS

Cassandra platform – Alpha version

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Login screen

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Main screen

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Projects and entities

Main panel

Libraries

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List of projects

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User library

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Cassandra library

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Appliances in Cassandra library

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Creating a new project

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Adding a new scenario to our project

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In this case, Installations are added by drag

n’ drop from the user library

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Persons, Activities and 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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Submit runs

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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

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Behaviour change in Apartment 1

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Behaviour change in Apartment 1

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Behaviour change in Apartment 2

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Behaviour change in Apartment 2

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Appliance change in Apartment 3

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Appliance change in Apartment 3

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Submit new runs with same parameters

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Compare the runs (graph)

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Compare the runs (KPIs)

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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

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MODEL TRAINING

Cassandra platform – Alpha version

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Cassandra platform – Christos Diou

Training module (to be integrated)

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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 – Alpha version

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Response models

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Modify pricing scheme

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Estimate consumer response

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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

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from … to:

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Example 2: Response from

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from … to:

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CONSUMER SOCIAL NETWORKS

(CSN)

Cassandra platform – Alpha version

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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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Cassandra platform – Christos Diou

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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By changing the visualization

layout algorithm….

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The two different person types

appear

Visualization is Important!!!

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A new network based on Peak

Consumption similarity

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We select the clustering

algorithm to use

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Clusters appear in different

colours

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By grouping clusters…

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The different consumer

groups appear

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Another network based on

similar consumption

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Change the edge threshold

via the appropriate slider

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Select a clustering algorithm

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Clusters appear in different

colors

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Various statistics are

available, as well as the

consumption and information

of selected nodes

Sliders for minimum edge

weight and clustering values

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Cassandra platform – Christos Diou

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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Cassandra platform – Christos Diou

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

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Cassandra platform – Christos Diou

Thank you!

Questions?