Fundación Deusto - DeustoTech Energy uses multi-agent simulations to address challenges in energy, water, waste and urban systems. It focuses on areas like energy distribution, water networks, waste management and integrating energy systems. Case studies include using multi-agent models to simulate waste management systems, increase energy efficiency in buildings, and monitor drainage and sewerage networks. Simulations provide benefits like testing solutions without lengthy real-world deployment and gaining insights more quickly than real data collection allows.

2. Fundación Deusto – DeustoTech
Energy
DeustoTech Energy was created to give response to the present and future
needs of companies within the energy, water, waste management and urban
sector.
Our research focuses on the following areas:
•Energy
distribution
systems
knowledge
•Water
networks
•Waste
management
Integration of
energy
systems
Environment
and clean
technologies
DeustoTech Energy

3. Uso de modelos multi-agentes para la edificación y
urbanización sostenible.
Casos de éxito en eficiencia energética, gestión de
residuos urbanos y redes de drenaje y saneamiento.
Use of multi-agent models for sustainable construction
and urbanisation.
Success cases in energy efficiency, waste management
systems and drainage and sewerage networks.
Oihane Kamara Esteban
oihane.esteban@deusto.es
Fundación Deusto - DeustoTech Energy

4. Why are simulations beneficial?
• Sometimes the solution requires a lengthy process of configuration and
deployment.
• Large amount of time needed to acquire a sufficient data for analysis.
• High economic investment and time restrictions related to the deployment of
technologies in real or scaled environments.
• Simulation environment also provides the benefit of consistent, constant, and
immediate feedback.
• Helps the decision making process.

5. What are multi-agent systems?
• Multi-agent systems are I.T. systems composed of multiple interacting
intelligent agents within an environment.
• Intelligence may include some methodic, functional, procedural approach,
algorithmic search or reinforcement learning.
• Active agents (proactive) and passive agents (they only react to stimuli initiated
by other agents).
• Agents can communicate with one another and may decide to operate
individually or work together towards a common goal.

6. What are multi-agent systems simulations?

7. Case 1: Waste management systems

8. Objective:
Move forward the current waste management practices into a circular economy motto demonstrating the value of integrating and
validating 20 eco-innovative solutions that cover all the waste value chain. The benefits of these solutions will be enhanced by a holistic
waste data management methodology, and will be demonstrated in 4 complementary urban areas in Europe
Waste4Think: Moving Towards Life-Cycle Thinking by
Integrating Advanced Waste Management Systems

9. Waste4Think: Moving Towards Life-Cycle Thinking by
Integrating Advanced Waste Management Systems
Characterise
waste generation
Create
what-if scenarios
Multi-agent system
Changes in the
waste
collection
system
n
KPIs evaluation
New
incentives
1
New paying
schemes
2
• % of sorted wate
• % of improper waste
• …
• % of sorted wate
• % of improper waste
• …
• % of sorted wate
• % of improper waste
• …

10. Case 2: Energy efficiency

11. Greensoul: Persuasive Eco-awareness for User
Engagement through Networked Data Services
Objective:
Achieve higher energy efficiency in public buildings by altering the way people use energy consuming shared and personal devices:
• Persuade users to increase their energy-awareness and change their e-consumption habits through a variety of techniques, from
persuasive social applications to physical interaction mechanisms linked to the networked devices
• Embed intelligence into the networked devices to allow them autonomously decide about their operational mode for energy
efficiency purposes.

12. Characterise energy
consumption profiles
Find ideal persuasive techniques to increase Eco-awareness
Multi-agent system
Greensoul: Persuasive Eco-awareness for User
Engagement through Networked Data Services
6. Intelligent control at device level (+5%)
5. Manual control due to behavior change (+4%)
4. Awareness through GreenSoul platform (+3%)
3. Energy awareness spread to personnel (+4%)
2. Awareness of building energy manager (+3%)
1. Smart monitoring (+2%)
Indifferent but
prone to change
Indifferent and
against change
Energy aware
Persuasive
social
applications
Interaction with
devices
Gamification

13. Case 3: Drainage and sewerage neworks

14. EstolZAIN: Advanced Management of
Drainage and Sewerage Networks
Objective:
Development of a platform for on-line monitoring and simulation of the entire urban sanitation network, allowing a continuous
monitoring of the system:
• Detection of drainage network stagnation zones.
• Forecast episodes of uncontrolled spills and flooding.
• Quantitative risk analysis for floods and uncontrolled spills.

15. Characterise water
consumption profiles
Studiy the resiliency of the network
Multi-agent system
Storm water and
sewerage model
Rainfall events
Alert system
EstolZAIN: Advanced Management of
Drainage and Sewerage Networks

16. Thank you for your attention.