The AWS suite of managed services for IoT enables companies to quickly and easily deploy devices to the edge and synchronize their industrial time-series data from multiple sites to the AWS Cloud, where advanced analytics and machine learning can generate valuable insights about their business. In this session, learn how EDF Renewables used AWS Greengrass, AWS IoT Core, AWS IoT Analytics, and AWS Lambda to facilitate the collection, aggregation, and quality assurance of operational data from solar installations. Hear how working with AWS Professional Services transformed its approach to product development, and learn what challenges and solutions came with choosing leading-edge services form AWS.

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Distributed Solar Systems at EDF
Renewables and AWS IoT: A Natural Fit
Amy Lindsay
Product Owner: Solar & IoT
EDF Renewables
P U T 3 0 4
Matthieu Fuzellier
IoT Architect
AWS Professional Services

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Agenda
• Introduction
• Problem definition
• Technical solution
• Lessons learned
• Business results

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After this breakout session
• A few days after the event…
• The presentation will be shared as a PDF on SlideShare
• The recording will be available on YouTube
• Visit the Power & Utilities web site at:
aws.amazon.com/power-and-utilities/

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EDF Renewables

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EDF renewables
• We are in the process of building a common cloud-based digital
platform to address industry-wide challenges
• Decentralization and “prosumers” of energy
• Need for more agility, increased speed to test new services
• Breaking the silos of data and knowledge-base by providing transparency at the group level
on performance and processes
• Adopted a flavor of scaled agile framework

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Data challenges on solar assets
• Geographically distributed assets
• Unreliable connectivity
• Diverse portfolio for owned and third party assets, leading to a variety of
• Physical devices
• Asset layouts
• Data sources & data stores
• Communication protocols
• Data quality is critical since underperformance detection relies on cross-data-
source analysis

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Data challenges on solar assets
An example:
Inverters
Inverters
Inverters
DC combiner boxes
DC combiner boxes
Panel temperature
sensors
MET station
Substation
Meter
Real Time Automation
Controller (RTAC)
Supervisory Control
And Data Acquisition
(SCADA)
Data historian
Modbus or
proprietary
communications
over TCP/IP or
RS485
Modbus / DNP3
Utility
DNP3
Modbus / OPC DA / DNP3
Modbus /
OPC DA /
DNP3
Trackers
Video /
camera

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Methodology
• Working backwards: delivering a strong business use case before
addressing the technical solution
• Accelerated time to delivery of an end-to-end solution
• Ramp up internal skill sets while benefiting from expertise of AWS
teams
• Interviews of key
business users
• PR / FAQ
2 weeks
• Workshop with AWS
ProServe
• Target architecture
3 days • Feature refinement:
Proof of Concept vs
long-term
• Prioritized backlog
2 days
• Agile delivery
framework
• Demonstration of
end-to-end ingestion
(Proof of Concept)
5 weeks

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Business outcomes
“No more need to remote into multiple SCADA systems that all differ in the way they collect and store the data - you can
now see how your portfolio of plants is performing from a central location and troubleshoot issues quickly. The data
pipelines include OPC DA, OPC UA, Modbus and DNP3, covering all popular communication protocols for solar sites.”
- extract from mock PR / FAQ
Sample user stories from workshop:
“As a Site Manager, I want to be able to export a
clean data set with data quality indicators so that
reporting is accurate and shows the level of
confidence in the data”
“As a Performance Analytics Engineer, I want to
have normalized data tags so that multiple sites can
be analyzed ”
“As a SCADA Engineer, I want to have a gateway
that is easy to onboard so that I can spend more
time on higher value-added tasks”
“As a Site Manager, I want to see the data of my
multiple site refreshing every 10 minutes so that I
can troubleshoot issues quickly”

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Data acquisition from solar sites

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Solution overview
AWS Cloud
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge
Gateway
Reporting, Analytics, Machine Learning,
Monitoring/Alerting
Solar Site (Edge) AWS Cloud
Data Consumers
Operations control center,
third parties, asset owners,
utilities…

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MQTT
High-level architecture
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge Gateway
AWS CloudSolar Site (Edge)
Notifications Raw and
processed
data

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Edge detailed architecture
MQTT
Topic Structure
Shadow Sync
AWS Cloud
Shadow
Device
Registry
Greengrass
Group
Certificate
and
Policy
Device Provisioning
Site
Configuration
Solar Site (Edge)
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge Gateway
Greengrass
Lambda
function
Certificate
Shadow
Modbus over TCP

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Edge configuration and IEC61850 mappings
Site layout configuration, stored in the Cloud:
{
"siteID" : "mySite01"
"points" : [
{
"modbus_start_register":"25",
"modbus_end_register":"26",
"iec_name":"INV1MMXU1.AvWPhs.mag.f",
"explanation":"active power for inverter 1",
"type":"Input Register",
"rtac_poll_frequency_ms":"1000”
}
...
]
}
Config
File
Solar Site (Edge)
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge Gateway
AWS Greengrass
Lambda
function
Certificate
Modbus over TCP

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Edge data sampling and stacking
Payload:
{
"timestamp": "20181015 09:01:00",
"someField": 11
}
Time Value
09:00:10 10
09:00:20 12
09:00:30 11
09:00:40 14
09:00:50 9
09:01:00 10Config
File
Solar Site (Edge)
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge Gateway
AWS Greengrass
Lambda
function
Certificate
Modbus over TCP

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Solar Site (Edge)
Edge data cleaning and tagging
Payload:
{
"timestamp": 20181015 09:01:00,
"someField ":11,
"dataQuality": {
"max": 14,
"min": 9,
"sample_count": 4,
"confidence": 0.66,
}
}
AWS Cloud
Raw Data
Raw
samples
Solar site assets
GridEdge Gateway
AWS Greengrass
Lambda
function
Certificate
Modbus over TCP
Time Value
09:00:10 10
09:00:20 NULL
09:00:30 11
Time Value
09:00:40 14
09:00:50 9
09:01:00 9999

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Edge summary
{
"timestamp": "2018-10-11 11:39:29",
"gridedgeid": "000001",
"payload": [{
"type": "SOLAR",
"name": "device.name",
"values": {
"INV6MMXU1.AvWPhs.mag.f": 809.8,
...
},
"dq": {
"INV6MMXU1.AvWPhs.mag.f": {
"max": 810.3,
"min": 809.1,
"std_deviation": 0.1678,
"sample_count": 22
},
...
}
}]
}

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Cloud - Ingestion
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge
Gateway
Solar Site (Edge)
Notification
AWS Cloud
MQTT
Shadow
Rules
Engine
Reporting
EDF/3rd party integration
Datasets
Templates
and scripts
Automation

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Upcoming
Solar Site (Edge)
Solar site assets
Inverters, panel sensors, meter, met station, camera…
GridEdge Gateway
Greengrass
Certificate
Shadow
Modbus / DNP3
Raw samples Feed into ML and
complex analytics
Notification
AWS Cloud
Data Lake
Automation
Configuration
Operations
Control Center
Operators
Management and Security
Remote management
Lambda
InsightsAlerts
Detect stale data
Auto backfill data

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Lessons learned
• Infrastructure automation cannot always keep up with fast-pace
changes to AWS services
• Not all services support AWS CloudFormation e.g. IoT Analytics
• Permission boundaries for AWS Identity and Access Management (IAM) not yet in AWS
CloudFormation
• Configuring hardware outside of the cloud platform to run cloud-
native services such as AWS Greengrass requires orchestration tools to
perform necessary actions on the device and in the cloud
• As expected, the proof of concept does not answer all questions for a
deployment at scale but sets out a clear path to achieve that goal

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• Start small, keep the big picture in mind
• How to reuse / comply with existing OT / IT infrastructure
• Data architecture and data normalization are key
pieces of the solution
• Digital disruption is real: focus on change management
Lessons learned THINK BIG
Start small

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Business Results
• Demonstrated the suitability of AWS managed services around IoT for
our business requirements, within 5 weeks
• Deployed 1 test device to 1 test site
• Identified cybersecurity best practices and recommendations when
extending the cloud platform out to the edge
Proof of Concept = small:
- Deployment
- Feature set
Roll-out plan = big:
- Deployment
- Feature set

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Business results
Next steps
• Deployment at
scale
• Skill sets & partners
• Architecture
validation
4 weeks
• Hardware design
• Multi-device
management
• Industrialization
12-16 weeks
• Production-grade
• Roll-out
• Full-scale
deployment
Steady-state

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Business results
Four GW+ in AWS cloud and counting
Solution could address 100 MWs
today and many more in the
pipeline

31. Thank you!
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amy Lindsay
Solar & IoT
EDF Renewables
amy.lindsay@edf-re.com
www.linkedin.com/in/amy-lindsay
Matthieu Fuzellier
Solution Architect
AWS ProServe
mattfuz@amazon.fr
www.linkedin.com/in/mfuzellier

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