Analytics for Smart Grids...SAP-PI. Integration Architecture –Sending of SMS 31 Outage...

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Analytics for Smart Grids

- DONG Energy Case Study on Optimization of Business Processes and Integration of IT Platforms

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Signe Bramming Andersen

DONG Energy, Senior Manager

Head of Asset & Energy Management

[email protected]

Jesper Vinther Christensen

Director & Founder, Similix

Lead Architect, DONG Energy Smart Grid Programme

[email protected]

mailto:[email protected]

mailto:[email protected]

DONG Energy Results 2015

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5

Mission: Clean, Independent & Cost Efficient Energy

Henrik Poulsen, CEO, DONG Energy Sustainability Report 2015

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Goal

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Distribution of Electricity

8,4 TWh distributed in 2015

From 2015 Annual Report

What is Grid Analytics about?

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• Business wide understanding of

the asset portfolio

• Optimizing long term investment

planning

• Optimizing maintenance cost

• Safety

• Your data is some of your most

important assets

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Smart Energy is about implementing a data and process centric strategy.

Operation

PlanningMaintenance

• Defining a transparent and

communicated master data

management strategy, delegating the

responsibility of data ownership for

each data component.

• Having aligned business processes

across business units, integrating the

Planning, Maintenance and Operation

of the Critical Infrastructures into

unified processes

• Implementing a seamless integration

between software platforms ensuring

process support and maintaining high

data quality

DONG Energy Smart Grid Projects

* Proof of Concept – Esri Alpha Program for new Utility Network

** Future possible projects - Not decided

20142013 20162015 20182017 202020192012

Advanced Distribution

Management System (MV)

GridHub/HAS(Smart Grid Analytics)

Outage Management

System

Integrated SCADA

Platform + HV

ADMS**

MDM/AMI & Smart Meter Roll-out

Merge of DMS &

OMS

Low Voltage

ADMS**

2021 2022

New Esri Utility Network*

Smart Grid Architecture – From an IT-perspective

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Processes

Information

Software

Infrastructure

That support the

Planning,

Maintenance and

Operationof Electric Power Systems

Processes, Systems and Integrations

▪ Projects

▪ Scheduled Maintenance

▪ Incidents

▪ Customer Connection

▪ Long Term Grid Planning

▪ Near real time load estimation

▪ Outage Reporting

▪ Customer Service Information

▪ Equipment Value Estimation

▪ Work Planning

▪ SCADA Engineering

Note: Most processes are different on high, medium and low voltage levels.

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SAP PM

GIS

DMS

GridHUB

SPC

OMS

ONS

SMS

Letter

ELFAS

Dansk

Energi

Designer

Express

SAP ISUOutage

Report

NE PLAN


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

GIS

DMS

GridHUB

SPC

OMS

ONS

SMS

Letter

ELFAS

Dansk

Energi

Designer

Express

SAP ISUOutage

Report

NE PLAN


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

Network

DMS

GridHUB

SPC

OMS

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report

NE PLAN


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

NetworkADMS

GridHUB

SPC

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report

NE PLAN


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

NetworkADMS

GridHUB

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report

NE PLAN


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

NetworkADMS

GridHUB

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

NetworkADMS

GridHUB

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report

MDM


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

NetworkADMS

GridHUB

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report

MDMSpatial Data

Warehouse


▪ Projects


▪ Incidents







▪ Work Planning



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SAP PM

New Utility

NetworkADMS

GridHUB

ONS

SMS

Letter

ELFAS

Dansk

Energi

SAP ISUOutage

Report

MDMSpatial Data

Warehouse

Condition

Based

Maintenance

The ADMS Project Scope

Data is needed!!

Grid Asset Data (Inside the Fence)

Grid Asset Data (Outside the Fence

Base Maps & Ortho Photos

Schematic Representation of Network

Current Network Switching State

SCADA Points

Costumer & Consumption Data

HV Cables

Load Profiles

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Optimizing the Grid in Real Time

By combining Grid data, Asset information, Customer Consumption, Load Profiles, and real time SCADA measurements the ADMS calculation engine is able to calculation the energy flow in the entire grid in near real time.

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Dataflow

DATAACQUISITION

DATA ENRICHMENT & ANALYTICS

DATADISTRIBUTION

Esri ArcGIS• Supports Design and Maintenance

processes

• Leading system for the Static Network and owns the Normal Network State

• Visualization & Cartographic representation

Schneider HAS/GridHub on MS SQL• Risk, Contingency and Investment

planning• Time Series Analysis• Snapshot of dynamic model• 50 Billions Records added per year

Schneider ADMS• Operational perspective• Leading System for the Dynamic State of

the Network and owns the Current Network State

• Fault & Alarm handling• Study & Playback scenarios

Model-based Integration

based on CIM IEC 61970 + 68

ETL Engine record snapshots of the dynamic network state

Schneider DMS Platform

SCADA

Maintaining the Network Model in DMS

Ente

rpri

se S

ervi

ce B

us

SAP Platform

ArcGIS Platform

CIM

Ad

apto

r (I

mp

ort

Pro

cess

)

CIM

Ad

apto

r (E

xpo

rt P

roce

ss)

Network Model &

Asset Data

Asset Data

Historian

Network Model Repository

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1

3 4 5

Master Data

Electric Network

Measurements

Dynamic Network Model

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Case: New Transport Hub in Høje Taastrup

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Network patch introducing new substations to the network

Project Life Cycle – Extending and Maintaining the grid

GIS Project Assistant▪ Documents the plans for the project in GIS.▪ Creates patch exports for DMS.▪ Post changes in GIS when project is in production in

DMS.▪ Documents final implementation once information is

received from project manger.

Grid Operator▪ Controls the switching state of the network▪ Communicates with the field crew during commissioning or

decommissioning of equipment.▪ Energize patches in DMS which updates the electric model and

triggers feedback to GIS.

DMS Model Manager▪ Evaluates patches and approve them for later

energization or reject them and return them to GIS for corrections.

▪ Draws schematic layout in DMS.▪ Ensures that new data sent to DMS is correct.▪ Handles full feeders containing final

documentation of the network.

Project manager▪ Plans the work to be carried out▪ Delivers plans to GIS documentation

department▪ Delivers finial documentation when the job

is carried out.

Field Crew▪ Follows the orders of the grid operator.▪ Carries out the work planned by the project

manager.▪ Delivers information for final documentation

of the finished project to the project manager

Plan

Document

Prepare

Commission

Systems for gathering and

managing meter readings

and events. If meters

supports last gasp.

Systems for handling 0.4 and

10kV planned and unplanned

incidents. Input from SCADA,

Call Center and eventual AMI.

Systems for managing outage

information on web-site,

Social Medias, and data

exchange with management,

customers, and authorities.

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Outage Notification & Reporting

DMS

SCADA

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OMS

AMI

MDM

Outage

Notification

Outage

Incidents Web Site

SMS’s &

Letters

Reports

Ou

tag

e N

otifica

tion

Se

rvic

es

Exchange formats

Call Center

Customer Calls

Outage

Notification

Send Letter

Handling Planned Outages

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Outage

Notification

Database

Outage

Notification

Services SA

P P

I

OMSPlannedOutageServices

OMS Platform

Send SMS 1

2

3

OMS will send messages about planned work to SAP-PI.

Based on the messages from OMS, the Outage Notification Services determine what kind of letters that should be send to the customers.

SMS’s are send using service endpoints on SAP-PI and a 3rd party SMS Service Provider. SMS’s can either schedule or cancel an outage.

If we are unable to send a SMS, a letter are send using service endpoints on SAP-PI. Letters can either schedule or cancel an outage.

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2

4

3

4

OMS will send messages about unplanned and ongoing work to SAP-PI.

Integration Architecture – Sending of SMS

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Outage

Notification

Database

Outage

Notification

Services SA

P P

I

OMSUnplanned

and ongoing work adaptor

OMS Platform

Send SMS

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2

3

Based on the messages from OMS, the Outage Notification Services determine what kind of SMS's that should be send to the customers.

SMS's are send when a unplanned outage is confirmed, ETR is changed, or closed.

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2

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• Send SMS’s three days before a planned outages or if we are not able to send SMS’s to a customer sending a postal letter 7 days before the outage

• Send a reminding SMS 24 hours before the outage

• Send SMS’s to customers affected by an incident

• Send SMS’s if estimated time to restoration is extended

• Send SMS’s when power has been restored

In summery we are able to

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The Moving Parts

Access to DMS Clients from

Office Network

Integrations

and

Data Exchange

Services for the

Control Room

ICC

P

Data Replication

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The GridHub Datamodel

▪ Snapshot of complete MV grid with topology and measurements every 10th

minute.

▪ Customer load with synthesized load curves.

▪ Load flow every 10. min with calculated loads and voltages for all components

▪ Short circuit for breakers and switches every 24 hours.

▪ Contingency (N-1) every 4 hours.

Which data do we have?

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Querying & Visualization of time series

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Grid Analysis – Minimum Voltage

What is the minimum voltage during a year in the secondary substations?

Normal configurationAbnormal configuration

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Example of usage: Utilization Profile

High Quality Data – The cornerstone of a Smart Grid

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Smart Grid Ambition

Data Requirement

Smart Grid Ambition

Data Requirement

• Data Quality is relative to the usage. Working with Smart Grid

this fact becomes very evident

• The business case of the Smart Grid strongly depends on the

organization's ability to produce and maintain high quality data

• The real option for automating the grid requires accurate data

• The data model must capture a rich and precise electric

representation of the grid

• Completeness and classification correctness must be close to

100% (if not 100%)

• Data is shared among multiple systems for multiple purposes

Implementing the GIS-ADMS integration

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▪ Form a Master Data Management Strategy

- Get an overview of what data is needed in which system and in which process

- Delegate the responsibility of storing each needed data element to a particular system

- Ensure that all data elements are maintained as close to the business process changing the configurations

▪ Work with business processes

- Understanding the actual processes

- Select the ones that will be supported

- Draw the primary data flows

▪ Enrich the data

- Identify the critical data for supporting processes in ADMS

- Validate the current state on these data: Completeness, accuracy, classification, topology?

- Plan the data cleansing processes, and how the data is validated in source and target systems

▪ Make a masterplan

- Establishing the needed organization

- Defining the key milestones

- Align Expectations

• Further integration of maintenance processes across technology platforms

• Extend the use of GIS to analyze, explorer and visualize data

• Streamline the current integration and dataflow

• Support new business process for asset management and “Smart” Maintenance

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Future Directions

Un/installBreaker()

(Orchestration)

Un/installBreaker() SAP PM

Un/installBreaker() ArcGIS

ConfirmOperation() ADMS

Local Central

Switching Plan

1) Breaker1 Done

2) Ground Cable1 Done

3) Breaker2 Released

4) Ground Cable2 LOCK

ADMSUn/installBreaker()

Future – GIS will expand to be a customer system

▪ Capacity extension by flexibility

▪ Modelling flexibility

▪ Predicting electrical vehicles, heat pumps, solar panels

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MAINTENANCE STRATEGIES

Condition-based maintenance (CBM):

CBM periodically evaluates the state of equipment deterioration expressed quantitatively as a score or failure risk, and maintains equipment when the condition falls below acceptable thresholds. Additionally, CBM approaches rank assets within a given asset group with respect to each other, thereby enabling a prioritization of investments.

Time-based maintenance (TBM):

TBM is performed at regular and scheduled intervals, loosely based on the service history of a component and/or the experience of service personnel. This maintenance policy can be expensive and may not minimize the annualized cost of equipment.

Reliability-centered maintenance (RCM):

RCM considers both the probability of equipment failure and the system impact should a failure occur. RCM approaches rely on frameworks for estimatingnetwork reliability indices based on the failure rates of the different components. Most commonly, suchframeworks operate at the level of individual feedersand can be divided into analytical and simulationapproaches.

The Smart Grid Journey

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Control room silo

• Security = no integration

• Data redundancy

IT/OT integration

• Cyber security

• IT master data shared with OT

Predictive analysis

• OT dynamic data shared wit IT apps

• Big data

Real time analytics

• Analytics based operation

• Augmented reality?

Process control zone

•Low IT department involvement

Common Information

Model, Process data zone,

security patching

• IT infrastructure, CIM, EBS

Cloud, Incolumnstore, performance

tuning

•MS Xvelocity, Hadoop, Azure

Machine learning

•Algorithms, data lake

Infrastructure architecture

Integration architecture

Information modelling

Cloud architecture

Data science

NextGen software design

Mathematical modelling

B

u

s

i

n

e

s

s

T

a

s

k

s

C

o

m

p

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t

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Lessons learned

Key to success:

• Strategic partnerships with selected vendors

• System Architecture

• Data Quality

• Organizational Change Management

Together enabling the Smart Energy business processes across the utility value chain - transforming the business into a data driven utility.

• Bridging traditional IT and organizational silos

• Focusing on data modelling and data ownership

• Establishing cross department trust and understanding of business processes

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Signe Bramming Andersen, Senior Manager, Head of Asset & Energy Management, Group IT, DONG Energy.Responsible for implementing IT-platforms for supporting DONG Energy’s Smart Energy Programmes including ADMS, Wind Farm Management, Power Hub (VPP)

Signe has worked with DONG Energy since 1999 and holds a Master in Economics & Business Administration.Contact: [email protected]

Jesper Vinther Christensen, founder and Owner of SIMILIX, a consultancy company offering independent advisory consultancy on IT and Organizational Transformations. Since 2011 Jesper has been the Lead Architect of the DONG Energy Smart Grid Programme.

Jesper holds a Ph.D. in GeoScience & Computing Science and has 20 years of experience with IT-projects, especially with System Integration, Enterprise Architecture and Geographic Information Systems.Contact: [email protected]

Analytics for Smart Grids...SAP-PI. Integration Architecture –Sending of SMS 31 Outage...

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