© Siemens AG 2015 siemens.com/EUW
Monet An IoT Energy Management Platform based on MongoDB
MongoDB Event | Milano, 14 January 2016
© Siemens AG 2015
2015-11-04Page 2 Maurizio Bigoloni / RC IT EM DG SWS
Energy Management Division\ Key numbers
~ €11 bn Revenue
~ 53,000 People
~ 100 Sites
~ €350 m R&D Investments
Locations Energy Management
© Siemens AG 2015
2015-11-04Page 3 Maurizio Bigoloni / RC IT EM DG SWS
Energy Management Division\ Portfolio
Serv
ices
& S
ecur
ity
Software/ITGrid control – big data analytics – grid application
Dig
italiz
atio
nA
utom
atio
n
Communication, automation, protection, field devices
Ele
ctrif
icat
ion
Electrification SolutionsHigh-voltage direct current (HVDC) transmission – grid access – FACTS – air-insulated/gas-insulated substations – power systems solutions – microgrids / nanogrids
Products & SystemsHigh-voltage switchgear and systems – power transformers – medium-voltage switchgears – distribution transformers – low-voltage switchboards and circuit breakers
Large powergeneration
TSOs1 Oil and gas Industria Infrastructures / construction
DSOs2 and municipalities
Distributedgeneration
1 Transmission system operators 2 Distribution system operators
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2015-11-04Page 4 Maurizio Bigoloni / RC IT EM DG SWS
Digitalization \ Enables customers to turn threats into opportunities
Digital services Vertical software
Digitally enhanced electrification and automation
Customers benefit• Increased productivity and flexibility• Shorter time to market• Improved uptime and lifetime
Challenges Digitalization delivers answers
ALERT!
Balancing
Peak avoidance
Resilience
Business models
CO2 and cost avoidance
Loss prevention
Distributed optimization
Customer focus
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2015-11-04Page 5 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ Keypoints
• Micro-Services Architecture
• Scalable/Reliable• Html5 web applications• Software as a Service
• Standard protocols (MQTT, AMQP)
• General-purpose data acquisition
• Real-time data aggregation
• Real-time data analysis
CloudInternet of Things Analytics
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2015-11-04Page 6 Maurizio Bigoloni / RC IT EM DG SWS
Internet of Things & Energy Management\ Innovative Services \ Energy Efficiency
Real-time data acquisition and data aggregation are enabler for energy efficiency advanced services. Internet of Things paradigm allows integrating end-user devices to get preferences and behavior information.
Energy Rules based on:
• Real-time measures
• Load & Generation Profile/ Forecast
• User Preferences / Environmental data
Energy Rules actions:
• Load Control/Shifting
• Storage Control
• Comfort variables set points
© Siemens AG 2015
2015-11-04Page 7 Maurizio Bigoloni / RC IT EM DG SWS
Internet of Things & Energy Management\ Innovative Services \ Demand Response
Integrating energy stakeholder systems (TSO, DSO, Energy Vendor) with end-user systems and devices allows implementation of innovative services toward Demand Response:
• Energy Vendor / Dynamic Price
• DSO / Grid Emergency
• DSO / Peak Shaving
• DSO / Electric Mobility integration
• Aggregation of Consumer/Producer
© Siemens AG 2015
2015-11-04Page 8 Maurizio Bigoloni / RC IT EM DG SWS
Milan Expo 2015\ A unique opportunity
Expo 2015 a unique opportunity to build a Smart City from green field:
• 1’100’000 m2 Area
• 75MW Planned Power
• 145 Countries
• 53 Self-Built Pavilions
• Fiber optics backbone
• Wi-Fi infrastructure (2’700 AP)
Siemens strategic partner of Enel for the Smart Grid technology at EXPO Milano 2015
© Siemens AG 2015
2015-11-04Page 9 Maurizio Bigoloni / RC IT EM DG SWS
Milan Expo 2015\ Project details
SMARTMETERING
GRID TECHNOLOGIES
ELECTRIC MOBILITY
SMART LIGHTING
OPERATION CENTERS
PV PLANTSSMART SUBSTATIONS
ELECTRO-MOBILITY
50
8500ARCHILEDE OUTDOOR SOLUTIONS
SMART BUILDING
100 200 5
BUILDING MANAGEMENTROOM
AUTOMATION
ENERGYSTORAGE
1
30 300
2
© Siemens AG 2015
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Milan Expo 2015\ Energy Management System
Online since May1st
EMS backendREST API
EMS web applications
MQTT / AMQP
Energy Monitoring / Reporting Energy Profiling / Forecast Energy Efficiency /
Demand Response
Enterprise Applications
1325
6
1. Grid Substations: P measures every 5’
2. GME Meter on each MV/LV transformer – via GSM every 15’
3. Enel Meter on each LV line – via Wi-Fi every 5’
4. Multi-meter on each controllable load; temperature & lighting sensors – via Wi-Fi every 5’
5. Charging Units – via GSM every 15’
6. Public Lighting Panles – every 60’
4
© Siemens AG 2015
2015-11-04Page 11 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ IT architecture
EMS backend
Local Control
REST API
EMS web applications
MQTT / AMQP
Energy Monitoring / Reporting
Energy Profiling / Forecast
Energy Efficiency / Demand Response
Enterprise Applications
Smart Home
Personal
Devices
Distribution Network SCADA
Public Lighting
Building Mngt
System
Electric Mobility
PlantSCADA
Smart Meter
MeterDataMngt
Fiel
dP
rem
ise
Clo
ud
MongoDB
© Siemens AG 2015
2015-11-04Page 12 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ Why a NO SQL database?
During the design phase the database selection was a key step: SQL, NO-SQL, or both?
At the end the choice was to go to NO-SQL only selecting MongoDB:
• General-purpose data acquisition layer schema-less databases best option for modeling different kind of objects
• Data acquisition layer requires a large number of WRITE operations NO-SQL more promising for keeping constants the WRITE performances
• Design for Cloud MongoDB scalability fits well with Cloud
• Given the full JavaScript application stack (node.js + html5) a JSON based document database as MongoDB resulted to be the natural choices for the entire system
© Siemens AG 2015
2015-11-04Page 13 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ Data acquisition
Data acquisition layer in Monet is based on MQTT protocol (www.mqqt.org). MQTT is a standard lightweight protocol adopting the publish/subscribe paradigm.
MQTT is based on the topic concept; a topic is a stream of data coming from or going to a particular I/O of a particular device. So it can contain data from the field but also commands.
The Feed Broker is the Monet module that collects the data. It contains a MQTT broker called Mosca. When a message arrives to the broker, the payload is stored as raw data in MongoDB.
© Siemens AG 2015
2015-11-04Page 14 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ Real-Time data aggregation and data analysis
Raw data coming from field devices needs to be analyzed; for any field variable there is the possibility to calculate Trends:
• Curve at fixed precision from raw data (avg, min, max, sum)
• Daily, Weekly, Monthly, Yearly trends calculated at different precisions
Trends curves related to energy variables (energy, power) are aggregated by different hierarchies:
• Geographical
• Electrical
• Technical
• By usage, scenario, mode
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2015-11-04Page 15 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ MongoDB aggregation framework
The Aggregation Framework allows easy and efficient aggregation on raw data. Here an example on how we store raw data in the datapoints collection.
{ feedId: “ABCD” date: 16/01/2016 values: [ {v: 10, ts: 1452902400000}, {v: 20, ts: 1452903000000}, {v: 30, ts: 1452903600000} ]}
{ feedId: “ABCD”, v: 10, ts: 1452902400000}
{ feedId: “ABCD”, v: 20, ts: 1452903000000}
{ feedId: “ABCD”, v: 30, ts: 1452903600000}}
VS
Data pre-aggregation,1 document per day, has several advantages: Many fewer documents: 1 per day vs 1 per
datapoint (hundreds of them!) Index space largely reduced, thus occupying less
disk and RAM Less I/O operations working on just a single
document All of this leads to overall better performance
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IOT based Energy Management System \ MongoDB aggregation framework
Here the simple instruction to aggregate raw data into
db.datapoints.aggregate([ { $match: { “feedId”: “ABCD”, “date”: { “$gte”: yesterday }}}, { $unwind: “$values” }, { $group: {_id : {'$subtract': [{'$divide': ["$values.ts", 3600000]}, {'$mod': ["$values.ts", 3600000]}]}},
date: date,max: {$max: "$values.v"},min: {$min: "$values.v"},avg: {$avg: "$values.v"},sum: {$sum: "$values.v"}
}]);
© Siemens AG 2015
2015-11-04Page 17 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ MongoDB aggregation framework
{ feedId: “ABCD” date: 12/01/2016 values: [{ v: 10, ts: 1452556800000 }]}
{ feedId: “ABCD” date: 16/01/2016 values: [ {v: 10, ts: 1452902400000}, {v: 20, ts: 1452903000000}, {v: 30, ts: 1452903600000} ]}
{ feedId: “ABCD” date: 16/01/2016 values: [ {v: 10, ts: 1452902400000} ]}{ feedId: “ABCD” date: 16/01/2016 values: [ {v: 20, ts: 1452903000000} ]}{ feedId: “ABCD” date: 16/01/2016 values: [ {v: 30, ts: 1452903000000} ]}
{ _id: 403584, date: 16/01/2016 max: 30, min: 10, avg: 20, sum: 60}
{ feedId: “ABCD” date: 16/01/2016 values: [ {v: 10, ts: 1452902400000}, {v: 20, ts: 1452903000000}, {v: 30, ts: 1452903600000} ]}
match unwind group
Input Result
© Siemens AG 2015
2015-11-04Page 18 Maurizio Bigoloni / RC IT EM DG SWS
IOT based Energy Management System \ Some numbers
6 months system running at EXPO Milano 2015
120.000.000 raw datapoints collected
45 GB raw datapoints collection
17 GB trend curves collection
5 GB energy aggregation curves collection
© Siemens AG 2015
2015-11-04Page 19 Maurizio Bigoloni / RC IT EM DG SWS
Internet of Things & Energy Management \ Conclusion
• Connected Things• Home Devices• Personal Devices
• Electric Grid• Communication Network • Distributed Generation
• Innovative Services• Real-Time Data Analysis• Efficiency• Demand Response• Aggregation
Internet of ThingsSmart Grid Digital Grid+ =
© Siemens AG 2015
2015-11-04Page 20 Maurizio Bigoloni / RC IT EM DG SWS
Maurizio BigoloniHead of OperationRC IT EM DG SWS
Via Vipiteno, 420128 Milano
Phone: +39 02 243 23335Mobile: +39 334 8888744
E-mail:[email protected]
Energy of Things\ Contact page
siemens.com/EUW
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