Applying digitalization trends in grid...

Applying digitalizationtrends in grid control15th INTERNATIONAL WORKSHOP ONELECTRIC POWER CONTROL CENTERSMay 12 – 15, 2019 // Reykjavik, Iceland

Rolf Apel, Siemens Smart Infrastructures

siemens.com/pvebopUnrestricted © Siemens AG 2019

Unrestricted © Siemens AG 2019 Rolf Apel , SI TI COE 15. May 2019

Agenda

1 Digitalization Trends

3 Data Analytics and Machine Learning

2 Digitalization in Power Grids

4 Digital Twin and IoT architecture


Data management and energy systems –In the age of digitalization they merge

Internet Mobiletelephone

Computer Industry4.0

>50%

new “things”get connected every day

Global data volume

Internetof Things

~1960 ~1970 ~1990~1980 ~2000 2030~2010 2020~1945

Nuclear PhotovoltaicGas WindEnergysystems

Decentralenergysystem

of the world’s datawas created last year

… but less than 0.5%was analyzed or used

by 2020


IoT allows tremendous speed in business model innovation

snapchat

Time until used by 1/4 of American population

1873 1926 1975 1991 2016

26 years

7 years months

46 years

16 years


Agenda






Digitalization in Substation already in the 4th Generation

1st generation –Standard cabling

2nd generation – Point- to-pointconnections since 1985 …

3rd generation – DigitalStation Bus since 2004 …

Mimic board

Fault recorderProtection

RTU

Parallel wiring

Parallelwiring

Control Center

HMI

Parallel wiring

Substationcontroller

Other bays

Serialconnection

Substationcontroller

Control Center

HMI

Station Bus

Parallel wiring

Switch

SwitchBay …Bay …Bay …

Digital Substation 4.0

Control Center

IEC

618

50

Substation controller

Parallel wiring CB ControllerCT/VTNCIT

3rd

Party

Sampled Values

Processbus

Station bus

IEC 61850 Apps and Data Analytics

IoT Interface


IEC 61850

IEC 60870-5-104

SIPROTEC 5 SIPROTEC 4 SIPROTECCompact

SICAM A8000 SICAM PQQ200/Q100

SICAM PAS SICAM SCC

SPECTRUM 5/7

Con

trol

Cen

ter L

evel

Stat

ion

Leve

lFi

eld

Lev

el

IEC 61850, Modbus, IEC 60870-5-103, …

SICAM A8000IoT Gateway

…3rd

Party

EnergyIPpowered by MindSphere

OPC UA PubSub

Benefits• Easy access to data of field

level devices e.g. for service• Access to expanded / entire

data set from field level forenhanced analytics by artificialintelligence or experts

Connectivity and interoperability in Grid Control

Data Exchange

IEC 60968/70 (CIM)


Big Data in Grid Control through bothAutomation Pyramid and Sensor streams

Mindsphere/ EnergyIP

Stored Data

Conversion of formats by library

Edge processed Data

Streamed sensorData

SCADAand

Control Centers

Control andprotection devices

Many other sensors (especially low-cost)

Electrical System Sensors

Data concentration/conversionby Intelligent Edge Devices (IED),e.g. SIPROTEC, SICAM

MindLib

AD conv.+Gateway

Data converted and streamedto MindsphereGateway separate fromautomation, no interference


Agenda






Why Big Data?Because resolution matters!

15 min resolution

“Low” resolution – useful to knowoverall energy consumption.

1 min resolution

“High” resolution – useful tounderstand behavior patterns andto implement algorithms.

Near real-time

High volume of data gathered –detailed information fromprocessed data.

Create the ability to visualizethe behavior of the equipmentin regard to energyconsumption

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Deep Learning Example:Online Decision Support for Power Grids

Growing share of renewable

• Wide area monitoring combined withdecision support

• Disturbance identification andcompensation

Wide-AreaDisturbanceClassification

• Increase quality of supporting informationin case of faults

• Localization of faults even in difficult cases

FaultLocalization andClassification

Growing share of renewable energy and distributed power generation call forenhanced capabilities of intelligent devices.

Operation Center: Disturbance Classification Infield: Fault location using neural networks

Inter-preter

Sourcecode

Model Training Model Generation Model DeploymentStream Data Recognize Contingencies

CounterMeasures

Embedded Analytics Framework (LEAF)

contingencyTIME


Local artificial intelligence in distribution grids

The secondary substation as thebrain of the digitalized LV-network• Intelligent control increases grid

capacity for distributed generationand electric vehicles

• Autonomous operation improvesresilience of distribution networks

• No / minimal number of datainterfaces to other OT/IT systemreduces the complexity

• Minimal communication to otherOT/IT systems during operationreduces costs and vulnerability

• Self-learning and self-configurationreduces implementation efforts

ANN: Artificial Neural Networks

MicroSCADA

Medium Voltage Low Voltage

ANN-based MicroSCADA in secondary substationsCould berealized withMindSphere


Agenda






Contextual relation example for a power grid(Only a small partial subset)


Interoperability of Digital Twins for Energy Systems

Transmission Distribution Industry,infrastructure,buildings

Cross-sector couplings

Generation

DynamicModel

PowerTransmission & Distribution

AssetManagement

Protection

SensorData

Digital Twin Graph

System Planning/Operation:Simulation

and Optimization

PredictiveOperation and Maintenance

Data analytics/Machine learning

1011

0111

0111

Electrical Digital Twin• Digital representation of the network and its resources

• Prognosis of the System behavior

• Connection of specific software tools into an overall system

• »Enabler« for new methods, efficient work flows undcooperation

• Smart, automated and logic linkage of various sourcesà lean data model

• Data validation and improvement – independentfrom the used software tool

• »Single Source of Truth« –A central system as an intermediary between application andstorage. Yet:

• Flexible and decentral storage –efficient »back end« storage inproblem-specific Data bases


Digitalization - The energy system will be anelement of an economy-wide IoT infrastructure

Cloud-based operating system for IoTe.g. MindSphere

Maintenance,monitoring & serviceAutomation & controlPlanning, simulation &

engineering

Productivityand time-to-market

Flexibilityand resilience

Availabilityand efficiency

Copyright: Tafyr

Generation Transmission / Distribution & Smart Grid Consumption / Prosumption

Use cases, applications

Connected power assets and … … connected edge devices

1) DER: Distributed energy resources like smart meters, inverters for photovoltaics, e-mobility assets, storage systems, microgrids, …

Griddiagnostics

Digital twin Grid simulation Smartmetering

Energy efficiencyand analytics

MonitoringDER1)

123 ~

Virtual powerplant

Grid planning Grid control Digitalsubstation

Assetmanagement

ü

Key areas tostep upEnhanced electrification

Automation

Digitalization

• Sensing

• Connectivity / IoT

• Monitoring

• Controlling

• Managing

• Digital twin


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