ADMS + ANM - CIRED 2015

Lyon (France), 15-18 June 2015
Advanced Distribution
Management System
Applications: Managing Active
Distribution Networks
Graham Ault – Smarter Grid
Solutions
Graham Ault – UK – Tutorial 2 Distribution Management Systems

Objectives and Outline
 Description of Active Network Management
(ANM)
 Learn from example ANM projects
 Set out requirements for ANM
 Explore future ANM Directions
2

 Solutions to resolve the grid challenges of a low carbon world
through real-time, autonomous, deterministic control technology and
supporting services.
 Founded in 2008
 HQ in Glasgow with consultancy, technology development and test
infrastructure.
 Offices in New York and London
 Over 50 engineers focused entirely on the development and
deployment of Active Network Management solutions
 12 years of development in collaboration with utility customers and
one of Europe’s leading power systems universities (University of
Strathclyde)
3Graham Ault – UK – Tutorial 2 Distribution Management Systems

Lyon (France), 15-18 June 2015Researchproject
commences
Fieldtrialofautonomous
generationcontrol
Companyfounded
UK’sfirstfullyoperational
smartgrid–OrkneyRPZ
KeyroleinDGforsecurityof
supply,demandresponse
andEVintegration
Firstprojectinmainland
Europe
BloombergNewEnergy
FinancePioneer,secured
majornewprojectswithUK
PowerNetworksandSSEPD
andfirstmanorprojectwith
SPEnergyNetworks
FirstprojectswithWestern
PowerDistributionand
NorthernPowergrid
FirstprojectswithCon
Edison,SouthernCompany
andNorthernIreland
Electricity.LaunchofNYC
office.Firstframework
contractwinforANMroll-out
withSSEPD
4

Products
Consultancy, Analysis,
Tools and Training
Systems Integration
and Support
Active Network
Management
products
• Strategic
Consultancy
• Power systems
analysis
• ANM system design
• Capacity analysis
tools
• ANM planning and
operational training
• Services to
support the
deployment of
Active Network
Management
• Ongoing support
and maintenance
of operational
systems
Project Lifecycle
What SGS do
5

Outline of ANM and fit with
other network control
infrastructure and
applications
6

To rest of network….
12 MVA
Bus 1 Bus 2
FG0 - 15 MVA
NFG
3 - 12 MVA
12 MVA
v, i
v, i
ANM Controller
v, i
Real-time Export
SCADA/EMS/DMS
0 - ? MVA
Storage
Substation or Control Room
7
Active Network Management: Concept
7

What is Active Network Management?
 A part-distributed control technology to manage
distributed energy resources.
 Delivering real-time autonomous deterministic control
providing guaranteed repeatability and time-bounding
of end to end control actions.
 To enable second by second control of distributed
energy resources and grid devices to deliver smart
grid functionality.
 Typical applications include real and reactive power
control, voltage management and energy balancing.
8

What ANM is not …
 SCADA or DMS: ANM complements such systems integrating
easily via standard industry protocols to enhance network
visibility and grid control.
 DER Management System (DERMS): ANM complements such
systems by providing a robust, reliable and secure device
integration and interaction layer.
 Substation Automation (SA): ANM extends beyond the
substation into the field but leverages existing substation
equipment and communications where possible.
 Distribution Automation (DA): ANM tends to be focused on power
systems constraint problems rather than reliability improvements
but can sometimes be considered a new type of Distribution
Automation application.
9

Commercial Benefits of ANM
 Maximise grid utilisation by increasing DG and DER
hosting capacity
 New connection options to reduce connection times
and cost
 Increased financial return from existing assets
 Increased network revenue
 Increased connection charges for more connected
customers
 Avoid or defer capital expenditure and grid upgrades
 Reduce network charges to demand customers for
distributed generation reinforcement
 Improved customer service
10

Technical Benefits of ANM
 Ease of adoption
 Products fit with existing DG/DER connections process and
agreements
 Autonomous operations and simple to use configurability
within a single platform
 Reduced complexity and quick to deploy
 Associative relationships, sensitivity factors, timers and
deadbands remove the need for the connected network
model and complex mathematical optimisation techniques
 Extensible platform for implementation of additional
functionality
 Time bounded control loops and repeatability coupled with
fail to safe mechanisms provide peace of mind to control
room operators and protection engineers
11

Scenario:
• DG causes power flow
overloads on overhead
lines and grid
transformers.
Operation:
• Current monitoring at the
locations where the
overload occurs
• ANM system calculates
the capacity and any
required curtailment
• The ANM generators are
curtailed per their
connection agreement or
agreed contractual terms
when the power flow limit
is breached
• Generators are associated
with multiple constraints
(e.g. control zone A and C)
Generator
Primary
Substation 1
Control Zone A
Generator
i v
Generator
Primary
Substation 2
Control Zone B
Generator
i
Generator
Generator
Grid Substation
Control Zone C
i i
SCADA / DMS
Transmission
Network
Generator
Generator
Existing
generation
outside of ANM
system
ANM enabled
generator
within control
of ANM system
ANM 100
ANM 100
12
Example Scenario 1

Scenario:
• Generation export of real
power raises voltage at point
of connection and along the
feeder resulting in AVC
scheme operation and low
voltage measurements on
parallel feeders.
Operation:
• Real-time monitoring at PCC,
end of line voltage on lowest
voltage feeder and at the
substation.
• Curtail real-power when
beyond voltage design limits
• Regulate the production or
absorption of reactive power
• Adjust the target voltage of the
on load tap change controller
Primary
Substation 1
SCADA / DMS
Generator
Generator
Existing
generation
outside of ANM
system
ANM enabled
generator
within control
of ANM system
i v i v
Generator
Generator
i v
Generator
i v
v
ANM 50
Generator
i v
Generator
i v
AVC
Scheme
ANM 50
13
Example Scenario 2

Scenario:
• Generator exporting real
power, sometimes exceeds
voltage at the PCC or at the
substation.
Operation:
• Delivers real-time monitoring
at PCC and if necessary at
the substation
• Curtail real-power when
beyond voltage design limits
• Can be integrated in the
future to ANM system
• Can be integrated back to
SCADA / DMS or without
centralised monitoring.
Substation SCADA / DMS
Generator
Generator
Existing
generation
outside of ANM
system
ANM enabled
generator
within control
of ANM system
i v
Generator
Generator
i v
ANM 50
ANM 100
14
Example Scenario 3

Scenario:
• Load Growth Results in a
Peak Power Flow that
Exceeds Capacity at primary
substations and grid
substation.
Operation:
• Real-time monitoring of
power flow at primary and
grid substations
experiencing peak power
capacity constraint.
• Curtail real-power set-points
for connected devices when
thresholds are breached
• Regulate the second by
second production or
consumption of energy from
Distributed Energy
Resources
Primary
Substation 1
Non-ANM
Generator
Generator
Primary
Substation 3
Variable
Load Generator
Energy
Storage
System
Primary
Substation 2
Generator
Variable
Load
i v i v
i vi v
SCADA / DMS
ANM 100
ANM 100 with Energy
Storage Module
15
Example Scenario 4

Active Network Management: Timescales and
applications
16

ANM Supervisory Control Protection
Deterministic Non-deterministic Deterministic
Autonomous Human operator Automatic
Software Software Firmware (or
electromechanical)
Defined network area Whole network Unit/non-unit
Locally-centralised
& Local/Distributed
Centralised Local/Distributed
ANM, SCADA and Protection
17

Example ANM Architectures
Based on Smart
Grid Architecture
Model
18

Distribution DER
X X
Power control
G
Process
Enterprise
Operation
Station
Field
UKPN substation DG substation
Market
Customer
Premise
TransmissionGeneration
ANM
UKPN
SCADA
PI historian
Vendor support
Smart devices
Measurements
Generation
Customerpremises
UKPN Control Centre FPP
comms
Generator
controller
Transmission
Distribution
DistributionEnergyResources
Source: UK Power Networks
19

20
Source: Scottish &
Southern Energy

ANM system configuration
Settings required:
Thresholds
Operating margins
Timers
Fail safe mechanisms
Power Flow At Constraint Location
System limit
Global Trip
Sequential Trip
Trim
Trim Less
Reset
Reset Less
Global Trip Operating Margin
Sequential Trip Operating Margin
Trim Operating Margin
Reset Operating Margin
 

































 RTF
dt
dP
dt
dP
RTDTD
dt
dP
dt
dP
OM
downNFGupexisting
Trim
upNFGupexisting
Trim
,,,,
Theoretical under-pinning:
Logical principles of escalating control action:
21

Lyon (France), 15-18 June 2015Trial results: Power Flow
0
5000
10000
15000
20000
25000
30000
35000
40000
18:37:00 18:38:00 18:39:00 18:40:00 18:41:00 18:42:00 18:43:00
Power(kW)
March Grid Transformer DG1 Power DG2 Power DG3 Power
Firm Generation Power DG1 Setpoint DG2 Setpoint DG3 Setpoint
Global Trip Seq Trip Reset Trim
Trim Less Reset Less
TrimBreach 2. Thermal limit
reached at MP
1. Firm DG ‘forced’
increase to create
thermal breach
3. DG set-points
calculated and
issued on pro-rata
basis
4. DG ramp-down in
compliance with
set-point
instructions
5. Power flow at
network constraint
below threshold
7. Driving
force on
constraint
removed
8. DG full
release starts
6. Adjustments
possible to fully use
thermal capacity
22

29.00
30.00
31.00
32.00
33.00
34.00
35.00
36.00
37.00
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
12000
13:01:00 13:02:00 13:03:00 13:04:00 13:05:00 13:06:00 13:07:00 13:08:00 13:09:00 13:10:00
Power(kW)
DG 20 Reactive Power DG 20 Reactive Setpoint DG 20 Real Power DG 20 Real Setpoint
Firm Generation Power MP 20 Voltage Upper 1 Nominal
Upper 2 Lower 1 Lower 2 Release Low
Upper1Breeach
1. Firm DG ‘forced’
increase to create
voltage breach
2. Voltage limit
breach identified at
MP 4. DG Real Power
set-point issued
with DG ramp-down
started
5. Voltage target
achieved (above
nominal)
3. DG Reactive
Power set-point
issued with
response (but not
enough!)
6. DG Real Power
release starts
7. DG Reactive
Power release
starts once DG
Real Power
fully released
23
Trial results: Voltage

24
Example of control round trip
Central ANM
Controller Comms
Local ANM
Controller
DG control
System
Curtailment
instruction
Curtailment
Confirmation
DG
Plant
Normal Operation
Configurable timer settings
Communications delay
Local system
delay
Generator Plant
delay
Application
delay
e.g. TCP/IP keep alive, RF mesh hops e.g. Device timer e.g. Ramp ratesApplication timerFine Tune
Breach of a
constraint threshold
Constraint
managed
TotalTime(Seconds)
Systemresponsetime
Breaker
G
Power export
reduced
Source: UK Power Networks

Example ANM
deployment projects
25

Challenge
Increase grid capacity, reduce time to connect
and cost of connection for distributed generation
in Cambridgeshire. Technical challenges
include thermal overloads and localised voltage
rise constraints.
Solution
♦ Non-firm actively managed grid connections
for distributed generation using ANM 100.
♦ Integration with Dynamic Line Rating relays
and Quad Booster Control System.
Delivered Benefits
♦ 15 generators (55 MW) accepted ANM
connection offers out of the 24 connection
offers made
♦ Reduction of CAPEX in connection offers of
75-95% to individual generators
♦ Aggregate saving of £44m
♦ 29 week decrease in connection time.
EPN licence area heat map for
DG connections
Cambridgeshire ANM area Norwich ANM
area launched
Dec 2014
following
success of
Cambridgeshire
26
Cambridgeshire

HighlevelschematicofCambridgeshiresolution
Connection costs and estimated
curtailment levels for normal connection
versus ANM connection
DLR
AVC
M
M
M
M
M
Power Flow
Constraint B
AVC
Client
RTU
Client
RTU
Power Flow
Constraint C
Voltage
Constraint B
Voltage
Constraint A
SCADA
(Control Room)
Generator 1
Generator 3
Generator 4
Generator 2
Generator 5
Power Flow
Constraint A
RFMeshIEC 61850
IEC 61850
IEC 61850
IEC 61850
IEC 61850
IEC 61850
27
Cambridgeshire

Example ANM deployment projects
 More case studies showing different
functionality in Appendix:
 London (UK Power Networks)
 Skegness and Corby (Western Power Distribution)
 South East Scotland (SP Energy Networks)
 Shetland Isles (Scottish & Southern Energy Power
Distribution)

ANM Requirements

Core ANM Requirements
 Autonomy
 Minimal Complexity
 Time-Bounded Operation: Real-Time Operating
Systems and Deterministic Applications
 Predictability and Repeatability
 Scalability and Consistent Performance
 Open Integration and Security
 High Availability: Failover and Redundancy
 Fail-Safe Functionality
 Operating on the Data
30

Other ANM Requirements
 Supporting tools
 Capacity analysis tools available for network
and connections planning teams to model
ANM connections):
 Supporting commercial/market arrangements
 Integration with other control systems
 Support
 Extensibility
31

Implications of not meeting the
requirements
 Increased operator intervention
 Breach of power systems limits
 Reduction in hosting capacity
 Breach of commercial contracts
 Increased systems integration costs
32

Future ANM Directions
33

Challenges to ANM Deployment
 Commercial rules for DG constraint management
 DNO business models for ANM investment and cost
recovery
 Network Operator resources
 Standards (ANM solutions, Security and Quality of
Supply, etc)
 Communications and data
 New interruptible contracts
 Planning tools and satisfying customer concerns
 Including investors in new generation projects
 Cost-benefit analysis
 Triggers for reinforcement
34

Future directions for ANM
Scale:
 Wider power system implications (transmission, balancing, etc)
 Multiple voltage levels and transmission/system/market issues
Scope:
 New functionality (real time constraints and objectives for
network control)
 Non-real time functionality
 New devices and data sources
 Emergence of microgrids
35

Jurisdiction:
 Regulatory incentives: New regulation driving ANM deployment –
RIIO in UK and REV in NYC as examples
 Market need and functionality
 Emerging trends and issues (by geography)
Issues of Integration:
 Control coordination for multiple ANM applications
 Systems of systems: ANM interacting with Gas, Heat and
Transport networks
 ADMS
36

Platforms:
 Next generation platforms
 Scalability and extensibility
37

Applying ANM learning to Microgrids
 ANM products and applications are suited to managing the interaction
between multiple Microgrids and the network operator and energy
supplier
 Provide visibility and control of individual/collective DER
 Manage network constraints, voltage profiles and schedule devices
 Local balancing of supply, demand and storage
 Respond to system events and real-time conditions
 Deliver “mission critical” coordinated control, fail safe functionality and
redundancy of key elements in the end-to-end system
 Manage the process of intentional islanding and also mitigate the risks
of unintentional islanding and reconnection
38

Microgrids in IEEE 1547.4
 Microgrids contain
generation and load
 Ability to disconnect
from and parallel with
wider system
 Different scales from
customer to substation,
local to wider area
 Intentionally planned
39

Generator
Energy
Storage
System
Circuit Microgrid
Generator
Facility Microgrid
Energy
Storage
System
Substation Microgrid
Microgrid Controller
DMS
ANM Application
DERMS
Historical Database
40
Example Layout of ANM for Microgrids

Concluding Remarks
 Active Network Management (ANM) has become a
well defined tool in the wider ADMS sphere
 ANM is being deployed on an off-DMS platform with
specific requirements
 Early project implementations with DNOs are
delivering benefits while pointing towards new
requirements and challenges
 Future directions for ANM are emerging in new
requirements, new applications and underlying new
platform technologies.
41

Appendix: Additional
project case studies

Challenge
Demonstrate how ANM can be used to
increase visibility of distributed generation,
improve security of supply, manage different
DER types and avoid demand driven
reinforcement.
Solution
♦ ANM 100 configured to second by
second manage export and import of
distributed generation (20+ MWs from
CHP), demand aggregators (3
aggregators) and EV charging (50 charge
points totaling 600 kW).
Delivered Benefits
♦ A third more distributed energy plants to
export power to urban networks
♦ £43m of savings identified through the
visibility and contribution of Distributed
Generation to security of supply.
Example trace of ANM delivering autonomous
demand response
43
London

Technical overview of the ANM
trials
EHV
HV
DG Control
System
Primary User
Interface
RTU Measurement
Points
Primary Substation
Local Demand
Response Site
Central ANM Controller
M M M Central Demand Response
Control Centre
Low Carbon London
Operational Data Store
UKPN
SCADA
Modbus/IP
(VPN)
TCP/IP
TCP/IP
various
DNP3/IP
ANM Data Historian
GPRS
Electric Vehicle
Charging Network
Operator
Electric Vehicle
Charging
Infrastructure
Modbus/IP
(VPN)
DG Control
System
Local Distributed Generation Site
various
GPRS
Power
Current
HV/LV Network
44
London

Challenge
Roll-out ANM connections for DG customers within 6
months. Technical challenges include thermal and
voltage constraints for wind and PV developments.
Solution
♦ Non-firm actively managed grid connections for
distributed generation using ANM 100.
♦ ANM 100 delivered and operational within 3
months.
♦ Consultancy services, capacity analysis and
training to build internal knowledge and capability.
Delivered Benefits
♦ Skegness: several generation connection offers
accepted
♦ Corby: several generation connection offers
accepted
♦ Several 10’s MW generation connection
acceptances
♦ Other ANM areas scheduled
SGS and WPD engineers
commissioning the Skegness ANM
system
45
Skegness and Corby

Single line diagram of
the Skegness network
showing ANM
connecting generation
with thermal and voltage
constraint locations.
46
Skegness and Corby

Challenge
♦ To increase the speed and cost of connection for
DG projects (e.g. PV, wind and thermal) in the
South East of Scotland.
♦ Reduce wasted engineering effort in connection
quotations which are not accepted (currently
>90%)
♦ Technical challenges include thermal overloads
and voltage.
Solution
♦ ANM-enable grid supply points with ANM 100 to
manage distribution and transmission constraints
♦ Deliver an online capacity analysis tool for
distributed generation customers to screen
connections before applying
Status
♦ Customer connection portal in trial and being rolled
out across the area by June 2015
♦ 3 grid supply points ANM-enabled and integrated
to existing communications and SCADA ready for
distributed generator connections
Available Capacity
Limited capacity
No capacity
ANM enabled area
Project area and constrained circuits for
distributed generation connections
47
South-East Scotland

Challenge
Develop and manage the non-interconnected island
grid more efficiently and increase role of renewable
energy in meeting future energy needs.
Technical challenge includes stability, primary
reserve, network operation and thermal overload
constraints.
Solution
♦ Actively manage new generator output against
stability and security constraints and schedule
new controllable demand to reduce renewables
curtailment and enhance system operation
♦ Distributed Energy Resources integrated include
domestic demand (2 MW of flexible electrical
heat demand and 16 MWh of energy storage);
several MW of new renewable generation and
battery energy storage.
Delivered Benefits
♦ 5 generators accepted ANM connections
(8.5MW)
Population ~23,000
Demand 11 – 47 MW
Diesel generation at Lerwick
Power Station (50+ MW) but
reaching end of life and requires
replacement
Energy supply and frequency
response from Sullom Voe Oil
Terminal but mainly there to serve
local load and cannot be
guaranteed in the long term.
Platform and
application
components
used to
deliver the
Shetland
ANM system
48
Shetland Isles

ANM Functions
♦ Forecasting of network constraints
based on load and generation
forecasts
♦ Calculation of day ahead schedules for
all controlled devices with an objective
of maximising renewable contribution
♦ Real time (second by second)
balancing to calculate and issue
override signals to respond to
unforeseen events, changes in
conditions and short term variations
♦ Management of system stability to
identify configurations that may result
in unacceptable oscillatory behaviour
and set operating limits, including
frequency response characteristics
Domestic
demand side
management
scheduling and
set up screen
Multiple
system
constraints
managed
through ANM
49
Shetland Isles

ADMS + ANM - CIRED 2015

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