Document

Report
Project FALCON
Sanna Atherton
Jenny Woodruff
Ben Godfrey
11kV Network Challenges
Inform long term investment decisions
Alleviate network constraints
T1 – Dynamic Asset Rating
T2 – Auto Load Transfer
T3 – Meshed Network
T4 – Energy Storage
T5 – Distributed Generation
T6 – Demand Side Management
Engineering
Commercial
Select the best technique
Carbon
Cost
Implementation
Speed
Network
Performance
Network
losses
Telecoms blueprint for the future
Develop future load scenarios
• Are the current profiles sufficient?
• Do we need more sophisticated customer
profiles ?
• To find out:
– Model different levels of uptake of low carbon
technology
– Build customer profiles from types of use
– Create a larger set of customer types
• SIM visualises expected constraints
Share what we learn
www.westernpowerinnovation.co.uk
Phased Delivery
2011
Mobilise
Partner Contracts
Agreed
2012
2014
2013
Build
Design
SIM Blueprint
Consultation
SIM Built
Implement
Trials
New Load
Scenarios
Created
2015
Consolidate
& Share
Trials Data
Analysed
Final Report
Produced
Scenario Investment
Model(SIM)
What does it do?
• Network analysis for a Scenario
encompassing many years.
• Applies possible techniques to
constraints
• Assess solutions against multiple
criteria
(cost, practicality, CIs CMLs etc.)
• Analysis & Visualisation of results
Use of SIM
Falcon
After
Falcon
• Guidelines on alternatives to reinforcement
• Best options for this type of problem?
• In which conditions is this solution suitable?
• To support long term network planning
e.g. for capital program / price control.
• 11kV Network planning tool
• Evaluate other solutions than used in Falcon
How will it work?
Now
Time
Assessment time horizon
Optimisation
Now
Time
Assessment time horizon
SIM components
Simulation Harness
Manage simulation branching
Network Modelling Tool
Load
data
Network
data
Economic
module
Optimisation /
prioritisation
Results
store
Identify constraints
Model techniques
Network edits
Data mining
tool
Calculate CML/CI , losses
Network visualisation
Visualisation
Load estimation
Load Data
Feature
Past
Future
“Worst”
scenario
Winter
Could be winter, summer max, summer min or
any time.
Planning aim
Design to avoid
constraints
Understand duration and nature of constraints ,
may manage with dynamic techniques.
Planning data
requirements
Winter maximum for
average cold spell
Evaluate half hourly over many years
Typical days (season, day type)
Monitoring
requirements
Monitoring at primary
substation.
View of power flows throughout the circuit to
support dynamic techniques.
Plus predictions
Half Hourly Load Estimates present day
Estimation Method
Settlement data
Energy model
Network
Measurements
Quality Metrics & Analysis
How well can we estimate loads today?
Can we substitute estimates for monitoring equipment?
Cost
Fully
Estimated
Optimum
Uncertainty
Fully
monitored
Load Estimation – Industry Data
• Based on the process used for settlement
• Half Hourly estimates for non half hourly metered customers
• Uses Estimated Annual Consumption + Profile coefficients for 8
different customer types.
Add in Half hourly metered load,
unmetered supplies, losses.
Does this give us a good estimate?
If so then use past data for similar day for real time estimation.
But not so good for predicting load in 20 years time.
Energy Model
• Wider range of customer types
(Dwelling type & age, heating system, occupancy,
demographics )
• Customer Propensity
Differential uptake of new technologies.
• Models different types of electricity usage
(Heating, lighting, appliances, etc.)
• Calculate impact of new technologies / changed
efficiencies on load profile
Future Energy Profiles & Scenarios
1800
1800
1600
1600
1400
1400
1200
1200
1000
1000
800
800
600
600
400
400
200
200
EV charging
Entertainment (TV, DVD, games consoles etc.)
Changes
reflecting
Scenario
0
00:00
01:00
02:00
03:00
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05:00
06:00
07:00
08:00
09:00
10:00
11:00
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16:00
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23:00
00:00
01:00
02:00
03:00
04:00
05:00
06:00
07:00
08:00
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
21:00
22:00
23:00
0
EV charging
Entertainment (TV, DVD, games consoles etc.)
Computers
Computers
Dishwasher & Laundry
Dishwasher & Laundry
Cooking appliances
Cooking appliances
Lighting
Lighting
Heating system
Heating system
Always on ( Fridge, freezer, security system, mains wired fire alarms etc.)
Customer type A (present day)
Always on ( Fridge, freezer, security system, mains wired fire alarms etc.)
Customer type A (2020)
Engineering Intervention
Techniques
Dynamic Asset Rating
33kV
Underground
Cables
33/11kV
Transformers
11kV
Underground
Cables
11kV
Overhead
Conductors
Real Time Ampacity Calculation to Control
Cyclic Overload Ratings
11k/415V
Transformers
Temperature
Models
Technique 1 Outcomes
Impacts
• Capacity of assets
increased
• Change in Planning
Standards
• Increased capital
costs
• Potential for
greater losses
• Enhanced visibility
of asset operation
Learning Objectives
• Comparing
implementations
• Development of
thermal models
• Thermal inertia of
asset types
• Modular
installation across
an existing
network
Operational
• Integration with
existing Control
• Understanding of
reliability of
predictions
• Active intervention
prior to thermal
excursions
• Pre and post fault
running
arrangements
Automatic Load Transfer
33kV
11kV
33kV
11kV
Technique 2 Outcomes
Impacts
• Increase in
utilisation factor
• Effects on
switchgear duty
• Increased capital
costs
• Reduction of
ampere-miles
travelled and
reduced losses
• Risk of Maloperations
Learning Objectives
Operational
• Understand
variability of feeder
loads
• Dealing with
automated control
routines
• Using customer load
profile to determine
connection strategy
• Best placement of
automated
equipment
• Optimisation of
network for
different running
arrangements
• Pro-actively
anticipating load
demands
• Better management
of large loads near
multiple small
customers
Meshed Networks
33kV
11kV
33kV
11kV
Technique 3 Outcomes
Impacts
• Enhance power
quality
• Increase in
customer security
• Increased capital
costs
• Further complexity
of circuits
• Fast, reliable and
error- free
communications
needed
Learning Objectives
Operational
• How to retrofit
meshing on an
existing network
• Using new
protection
techniques across a
communications
network
• Required grading
times for IP based
protection on the
11kV
• Integration with
existing protection
• Fault level
management
requirements
• Post-fault isolation
and re-energisation
routines
• Changes to standard
switchgear
specifications
Energy Storage
33kV
11kV
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
00:00
160%
140%
120%
100%
80%
60%
40%
20%
0%
+ -
+ -
+ -
+ -
Network Management
System
+ -
Technique 4 Outcomes
Impacts
• Carbon offsetting
through storage
systems
• Physical sizing of
storage assets on
the network
• Reduction in I2R
losses
• Increase in storage
losses
• Lifespan of battery
chemistries
Learning Objectives
Operational
• Optimum
charge/discharge
windows
• Using distribution
assets for ancillary
grid services
• Multiple set
collaboration across
an HV feeder
• Best placement of
storage on the
system
• Using power
electronic devices to
address power
quality issues
• Lifespan of battery
versus running
operation
• Protection
requirements
• Integration with
control environment
Commercial Intervention
Techniques
What Services could we use?
Demand
Reduce demand
•
•
•
reducing activity
time-shift load
switch to own generation
Generation
Increase or reduce generation
Event related
An unplanned event has occurred which results in a network issue
immediately, or in the next few hours.
Seasonal
Short lived network issues occur when the network is in its normal
state. Issues are regular and predictable.
Primary substation
HV Feeder
Post Event
Demand Side
Response
Challenges
Location
Location
Location
Learning
Customers willing and able to
respond?
•
•
•
•
Commercial frameworks?
• Use of Aggregators
• Common template
Practicalities of implementation?
• Communicating requirements
• Measuring response
Reliability?
• Realistic models for use in SIM
How much load is flexible
Can customers see benefits
How much financial reward
How should reward be structured
Project FALCON
Any questions?

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