1. EDGE WP5 Communication Infrastructure - Status February 25 - 2015
Jacob T. Madsen (AAU)
Mislav Findrik (FTW)

2. WP5 Timeline Now 2 case studies Layered Network Model Generalization
Network Model Specification

3. Network Aware Information Management
NAIM components are mapped to the case studies, and described in D5.1
In the case studies we are focused on:
Information Quality metric mmPr for different types of controllers
(Information Quality Assessment)
Adaptation of data collection process based on mmPr
(Observation Points & Data Collection)

4. EDGE Communication Architecture Status
What do we have now?
Detailed specification of data flows, network architectures/topologies and technologies for the case studies
Jacob (AAU) – Wind Park Control
Simulation of the fatigue estimator over the communication networks
Preliminary analysis of data quality metric
Mislav (FTW) – Control of Flexible Intelligent Customers
Analytical mmPr models for periodic controllers
Network topology definition for simulation studies
Inital analysis of Network-Control adaptations

5. WP5 Progress reports on case studies
FTW
Mislav Findrik

6. Case Study: Control of Flexible Intelligent Customers
Main goal summary in T5.2:
I - Enable meta-data for quality characterization of consumption/ generation/actuation data.
II - Provide and evaluate algorithms for access to and forwarding of sensor and actuator information across variable, heterogeneous communication networks.
Network QoS (WP5.1)
Dynamic Requirements
Data Access Mechanism
Quality Characatization
Controller
Sensors/ Controllers
Input Info.+
Meta Data
Input Information
Actuators
Actuation Commands

7. Case Study – Motivation
Top level controller running in a periodic time steps
Quality of data
Top level controller
„Simplified Approach“
Time step
1 controller, 1 sensor
Controller
Time step
Aggregator
Pulling data
Pulling, Pushing
Data, Event based
Sensor
Flexible loads
Pushing data
Three basic ways to access the data:
- Pulling (request-respond)
- Pushing (periodic updates)
- Event-based

8. Wind farm scenario Control scenario defined by Jesús
Impact of network on fatigue estimator:
2 fatigue estimators
2 different sensor readings
Comparing gives us a mismatch probability
Communication network is:
IP-network: Fiber optics
Sensor network: Bus (exponential delay)
UDP as communication protocol

9. WP5 Directions and future work
AAU
Jacob T. Madsen

10. Directions and future work
Current scenarios mainly consider Information Quality assesment and Data Collections
Future work will have to consider Network QoS monitoring and Network QoS estimation & prediction
Considerations for entire communication network not yet analysed

11. Directions and future work
For the EDGE project:
Communication architecture for the network betwen modules
Timing requirements for modules communication between each other
QoS requirements for modules
Prioritization of information for module information
Analysis of QoS measurement requirements
For WP6:
Given the architecture and timing requirements we find the most interesting part of the communication network to simulate
Add simulation of network to WP6 framework
QoS measurements in WP6 framework
Analysis of mismatch probability in communication network
Possibility of adding responsive control based on measured QoS