My presentation at the smart energy summit held in Singapore, March 2019. My talk focused on how to harness grid digitization capabilities to improve Distribution network reliability & integrate distributed renewable resources effectively.

1. Improving Distribution Reliability
Through Grid Digitalisation
By Moustafa Shahin
Manager- Distribution Network Development , DEWA
Head of Shams Dubai (Solar) Integration Working Group, DEWA
PhD Researcher - EGIS, Herriot Watt University
March 2019 - Singapore

2. 2
Current Smart Grid Developments (Reliability Focus)
 Advanced Distribution Management (ADMS)
 Self-Healing (FLISR) Grids.
 Dynamic Line Rating (DLR)
 Smart Asset Management.
Neural Grids of the Future
 Taking the Grid for Reliable To Resilient
 The Electrical Digital Twins
 Autonomous Energy Grids for seamless DER Integration.
Outline

3. 3
Energy Transformation
The three key Divers & Mega trends of Energy transformation: 3Ds

4. 4
Smart Grid Programme Taxonomy
Big Data Analytics (BDA)
Cyber Security
Telecommunication & IT/OT Integration (ICT)
Advanced Distribution
Management (ADMS)
EV Charging Stations
Distributed Energy Resources Integration (DERMS & VPP)
Smart Asset Management (SAM) Automated Demand Response (ADR)
Advanced Metering Infrastructure (AMI)
Wide Area Monitoring (WAM)
Smart Distribution Grid Portfolio

5. 5
Smart Distribution Grid: Reliability focus
Advanced Distribution
Management (ADMS)
FLISR
Volt/Var
Optimisation
Dynamic Line
Rating (DLR)
Digital
Substations
Advanced Metering
Infrastructure (AMI)
Automatic
Meter Reads
(AMR)
MDM
Integration
Demand
Response
Smart Asset
Management (SAM)
Asset Health
Center (AHC)
Advanced
Diagnostics/
Analytics
Optimised
Predictive
Maintenance

6. 6
Telecom Technology Used:
 GPRS
 BPLC
 RF-Mesh
 GPON: Gigabit Passive Optical
Networks.
11 KV 11 KV
Advanced Distribution Management (ADA + ICT+ AMI)
Smart Meters
/ OMS
EV
PV
Last
Gasp

7. Self-Healing Disitibution Grid (FLISR)
Closed-loop meshed MV Distribution Network
1 2 3 4 5
9 810 7 6
HV/MV
Transformer
MV BUS BAR
SS_1 SS_2
SS_3SS_4
DFI DFI DFI DFI
Bay Control
Unit (BCPU)
DFI: Directional Fault Indicators
Bay Control
Unit (BCPU)
IEC61850

8. Self-Healing Disitibution Grid (FLISR)
Closed-loop meshed MV Distribution Network
1 2 3 4 5
9 810 7 6
HV/MV
Transformer
MV BUS BAR
SS_1 SS_2
SS_3SS_4
DFI DFI DFI DFI
Faulty
sectionOpening in less then 300ms
(no interruption for the consumers , only a
voltage dip in case of S.C faults)
DFI: Directional Fault Indicators
Bay Control
Unit (BCPU)
Bay Control
Unit (BCPU)
X
X

9. 9
Dynamic Line Ratings provide real-time visibility and access at the operator’s console to the true capacity
for T&D feeders.
Dynamic Line Rating (DLR)
Additional Line Capacity
Static Rating (90 MVA)

10. 10
Without DLR, this event will be reported as a violation (exceeding the static limit) & The operator would have been
forced to intervene for curtailments/ load shedding
DLR Improved Grid Reliability & Congestion Relief
True Line Capacity
in Real Time
Peak load
 Improved Grid Reliability & Congestion Relief.
 Optimized Asset Utilization & Efficient operations.
 Faster DER Integration & Improved hosting capacity.

11. 11
Smart Asset Management
Trend Analysis, Anomaly
detection
Predictive Modelling, Health
indexing, Maintenance planning
Reactive
Maintenance
Preventive
(Time-based)
Condition-
Based
Predictive
(Reliability-Based)
Prescriptive
(Continuous Optimization)
Proactive actions &
Solutions for Asset optimisation
How can we achieve the best outcome?
Real-Time Visibility of asset
conditions

12. The Neural Grid of the future
In the new Energy Era, Being reliable is no longer enough!

13. Challenges of a New Energy Era: The Duck Curve
Solar Generation
sharp changes in energy
demand throughout the day

14. 14
Grid Balancing Challenges

15. 15
From a centrally controlled, synchronous generator-based grid to a highly distributed, inverter-based system
Low Inertia Challenge of high renewable penetration

16. Active DER Management strategy
DER Penetration Level
Technology
Low
Medium
High
Passive DER Integration
• Limited Remote monitoring .
• Stringent rules for DER feed-
in grid exports.
Active DER Management
• Advanced DER control with
Real-time data exchange.
• DER grid ancillary services.
Reactive DER Integration
• Remote monitoring with
limited control functionality.
• Lack of regulations for DER
grid ancillary services.
Evolution of Interconnection Grid Codes

17. 17
Source: NREL
The Next Digital Leap?
Digital Technology Is the Ultimate Resilience Enabler
Paradigm Shift in Grid Operations

18. 18
Past:
Traditional Grid
Emerging:
The Energy Cloud
 Centralized & distributed generation
 IT/OT integration
 2-way communication
 Distributed intelligence (IOE & AI)
 Multi-directional power flow
 IT/OT Convergence
 Operation based on real time data
analytics.
 Centralized power generation
 Uni-directional power flow
 Isolated OT & IT systems
 Operation based on historical
experience
Present:
Smart Grid
From Smart Grids to Neural Energy Cloud

19. 19
Neural Grid & Energy Cloud Platform
Digitization enables new services & improve operational resiliency throughout the energy value chain.
Source: Navigant
Smart Grid as a Service (GaaS)
Market growth to $6 billion by 2025.
Neural Grid

20. 20
Enabling technologies for Neural Grids
Internet of Energy (IoE)
Artificial intelligence & ML
Blockchain
Robotics & Drones
Digital Twins
Enhanced operational models via Machine Learning Cyber Security
Big Data analytics (BDA)
Smart Mobility

21. 21
The digital twins are the next big thing in digital grid transformation
What is a Digital Twin?
A digital twin is a dynamic digital representation of a real-world asset or system.
(Gartner)

22. 22
Asset Model Constraints
Machine
Learning
Dynamic Re-calibration
Real-Time
Operational Data
Historical Data
(O&M history, FEMA*,
Fleet Aggregated Data)
*FEMA: Failure Mode and Effect Analysis
Digital Twin = Mathematical Model + Statistical Model + ML
Process
information
Design
information
Real-time data allowing simulation and forecasting over the entire asset life cycle using sensor data,
production data and real-time process information ”
The Digital Twin is not just a blueprint
Analytics
Predictive Learning

23. Synchronized Planning and Operations Model
23
Automated synchronization and management of network models from planning, GIS, ADMS, and MDM data
Unified Model Management Concept
Source: Siemens AG 2018
 Synchronized planning
and operations model
 Improved overall
accuracy and consistency
of network models
("single source of truth")
 Improved efficiency and
process optimization in
planning and operations
 Integrated T&D modeling
and analysis
ESB

24. VPP Optimization Thru Digital Twins
Real-Time Optimization and Control of Next-
Generation Distribution Infrastructure
VPP
Engine
Request(s)
Response
AssetsDigital Twins
Grid
Demand
Constraints & Topology
Real-Time Performance
Telemetry
Control

25. 25
Active DER Management for effective DER Integration
,P Q
t
,P Q
t
Smart
Meter
RTU
+
1. Solar real-time measures
3. SS real-Time measures
2. Weather Forecast
Aggregaterd
Load/Generation data
ADMS 1. Hystorical load profiles
Secondary
Distribution
Distribution Control Centre
Smart
PV
Inverter
IEC61850 /
Modbus
OLTC
∆ V
Feeder
Demand
=
Autonomous Closed Loop Volt/Var Optimisation

26. 26
Neural Grids of the future
Autonomous T&D grid leveraging digital technologies to support resilient operations, self-healing, seamless
DER integration and self-optimisation.
Autonomous control, Real-time optimisation & Automated grid ancillary services.

27. 27
Neural grids will help utilities to ensure sustainability, resiliency, autonomy, and individualization in their
solutions to survive the competition.
Neural Grids Value Proposition
Resilient

28. Digital Grid beyond the technology
Embracing the Change & Structured Change Manage are key success factors

29. Thank You
www.linkedin.com/in/moustafashahin