This document summarizes the Cassandra project, which aims to develop a software platform for modeling energy markets from an end user perspective. The project involves 9 partners across Europe and will last 30 months. It will develop theoretical models of energy stakeholders, increase market power of small consumers through coalitions, assess energy performance, and create a decision support tool. It will test the platform through 3 pilot cases involving a multi-residential building, consumer network, and benchmarking lighting products. The goal is to accurately model individual and aggregated energy demand and empower end users.

1. FP7-288429-Cassandra
Cassandra
A multivariate platform for assessing the impact of
strategic decisions in electrical power systems
Project Coordinator
Center for Research and Technology –Hellas / Informatics and Telematics Institute

2. Power System Status – the near future
• Decentralized, small-scale production
sites
• Renewable energy
• Market liberation
• Smart grid
• More players involved
Big market potential unexploited!
 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

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

4. Cassandra vision/actors…

5. Cassandra at a glance
• Duration: 30 months
• Partners: 9 (1 Res. Center, 4 Universities, 4 SMEs)
• Person-months: 340
• Workpackages: 8
• Deliverables: 49
• Requested EC
contribution: 2,834M€

6. Cassandra Partners
1. CERTH Center for Research and Technology – Greece
Co Hellas
2. Aristotle University of Thessaloniki Greece
3. VaasaETT Global Energy Think Tank Finland
4. Politecnico di Milano Italy
5. Coventry University Enterprise UK
6. Luleå University of Technology Sweden
7. Cleopa GmbH Germany
8. Erasmus University Netherlands
9. Draxis Greece

7. The Partner Puzzle
VaasaETT Draxis
Dissemination Cleopa
Exploitation
VaasaETT VaasaETT VaasaETT
Multi
Consumer Lighting
3 Pilots residential
Network products
building
PoliMi Lulea CUE Cleopa
CERTH Draxis Erasmus
Software Development
CERTH Modeling AUTH
Draxis Requirements PoliMi

8. Cassandra methodology
• Five SE Phases
• Two-round iterative
software development
• Two Software prototypes
(early-final)
• Three Pilot Cases

9. Pilot Case 1:
Multi residential building
• Scope: To evaluate the Plants model User profiles
performance of the Cassandra Building
model
Weather
conditions
platform in a small scale
consumer network
• Main objectives: To test and validate
– Basic and Aggregate Consumer Modeling
– Load Modeling
– Heating/Cooling combined with building envelope
• Secondary objectives: To test and validate
– Consumer Network Modeling
– Behavioral aspects

10. Pilot Case 1:
Multi residential building
• Site: Residential building Plants model User profiles
in Northern Italy Building
Weather
model
• Specific Info: conditions
– Approximately 30 apartments
– Shops
– Monitoring and automated control equipment partially exist
• Methodology:
– Monitoring of the electrical and thermal consumption
– Modeling and Simulation
– Demand response and energy efficiency modeling and
implementation

11. Pilot Case 2:
Consumer Network
• Scope: To evaluate the performance
of the Cassandra platform in a
medium scale consumer network
• Main objectives: To test and validate
– Basic and Aggregate Consumer Modeling
– Consumer Network Modeling
– Behavioral Aspects
• Secondary objectives: To test and validate
– Load Modeling
– Heating/Cooling combined with building envelope

12. Pilot Case 2:
Consumer Network
• Site: Living Lab in Sweden
• Specific Info:
– More than 50 households
– SABER: a complete solution for the
full monitoring of energy consumption
• Methodology:
– Monitoring of the total energy
consumption
– Modeling and Simulation
– Research, modeling and implementation of behavioral stimuli
within the Consumer Network

13. Pilot Case 3:
Benchmarking lighting products
• Scope: To evaluate the performance
of the Cassandra platform as a market
enabling tool for a company
• Main objectives: To test and validate
– Load Modeling
– Strategic Planning capabilities
• Secondary objectives: To test and validate
– Basic and Aggregate Consumer Modeling

14. Pilot Case 3:
Benchmarking lighting products
• Site: UK, Germany,
sites of Pilot Cases 1 and 2
• Methodology:
– 2-3 lighting products will be developed
for deployment at different application
levels
– Factors affecting energy consumption for lighting will be
researched in the sites of Pilot Cases 1 and 2
– Modeling and Simulation

15. Assessable Outcome
• Cassandra is essentially a:
Modeling Software Platform
• To provide:
 Modeling of electrical installations (small or large scale, individual
or combinations of arbitrary number of installations)
 Knowledge regarding consumption patterns and demand-response
incentives
 Decision support (analysis of what-if scenarios)
 Open platform for energy companies/communities
(Global energy think Tank, PowerTAC)
 Empowerment of the end consumer
 Environment for studying change and sustainability

16. Assessable Outcome
• We expect to:
– Model accurately individual installations
– Model accurately the aggregated demand served
by a utility
– Offer the capability to understand macroscopically
the behavior and response of its customers
– Offer a tool that will either produce realistic
results with little effort, or dynamically produce
real results with considerable initial effort.

17. Assessable Outcome
• We do not expect to:
– Model accurately all individual customers of a
power utility
– Forecast the real response of individual
customers