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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
Jesper Vinther Christensen
Director & Founder, Similix
Lead Architect, DONG Energy Smart Grid Programme
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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
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
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
New Utility
Network
DMS
GridHUB
SPC
OMS
ONS
SMS
Letter
ELFAS
Dansk
Energi
SAP ISUOutage
Report
NE PLAN
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
New Utility
NetworkADMS
GridHUB
SPC
ONS
SMS
Letter
ELFAS
Dansk
Energi
SAP ISUOutage
Report
NE PLAN
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
New Utility
NetworkADMS
GridHUB
ONS
SMS
Letter
ELFAS
Dansk
Energi
SAP ISUOutage
Report
NE PLAN
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
New Utility
NetworkADMS
GridHUB
ONS
SMS
Letter
ELFAS
Dansk
Energi
SAP ISUOutage
Report
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
New Utility
NetworkADMS
GridHUB
ONS
SMS
Letter
ELFAS
Dansk
Energi
SAP ISUOutage
Report
MDM
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
New Utility
NetworkADMS
GridHUB
ONS
SMS
Letter
ELFAS
Dansk
Energi
SAP ISUOutage
Report
MDMSpatial Data
Warehouse
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
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
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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.
1
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
1
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
3
• 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
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T
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C
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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]