Transcript Document

An Introduction and Overview
of Technology
Damien Coyle
1
Agenda
Introduction
Technology
Why Smart Street?
2
Connecting the North West
£8 billion of network assets
4.9 million
2.4 million
25 terawatt
hours
3
Smart Street project overview
£11.5m,
4 year innovation
project
Trials period
Sep 2015 –
Aug 2017
£8.4m from
LCNF, £1.5m
from Kelvatek,
£1m from ENW
Project
overview
Facilitates
quicker cheaper
connection of
domestic LCTs
Started in Jan
2014 and
finishes in
Dec 2017
4
Project partners
5
Smart Street trial areas
6 primary substations
11 HV circuits
Wigton &
Egremont
38 distribution substations
163 LV circuits
Wigan
& Leigh
Manchester
Around 62,000 customers
6
Smart Street trial design
Two years
One week on
One week off
Five trial techniques
One year’s worth of
data
LV network management
and interconnection
To be designed to
avoid placebo affect
Five trial regimes to
test full effects
LV voltage control
HV voltage control
HV network management
and interconnection
Network configuration
and voltage optimisation
7
LV capacitors in street furniture
80 LV capacitors
Tried and tested
high spec
One on each
closed ring
8
HV capacitors
4 ground mounted
HV capacitors
4 pole mounted
HV capacitors
Housed in containers
but not on street
Installed similar to pole
mounted transformers
9
Weezap & Lynx
489 Weezaps
240 LYNX
Fitted across 163 LV
Circuits
Installed in 80 LV link
boxes
10
Existing radial network
Network limitations
Diversity between feeders is
untapped
Fuses unable to cope with cold
load pick up
Customer impact
Customers’ needs invisible to the
network
Demand and generation levels limited by
passive voltage control systems
Reliability driven by fix on fail
11
Voltage profile
Normal
voltage
range
Drift
range
Historic networks have no active voltage regulation
12
Problem - LCTs create network issues
Drift
range
LCTs rapidly surpass voltage and thermal network capacity
13
Smart Street – the first intervention
W
C
L
W
Low cost  Quick fit  Minimal disruption  Low carbon  Low loss  Invisible to customers
Voltage stabilised across the load range  Power flows optimised
14
Network reliability improvement
Spectrum
C2C
C
TC
C
W
C2C
CLASS
L
W
W
C
C2C
C2C
Capacity to Customers
L
C
C
Capacitor
W
WEEZAP
L
LYNX
TC
On-load tap changer
Builds on C2C and CLASS  Storage compatible  Transferable solutions
15
Smart Street benefits
Now we can stabilise voltage
We can set the voltage level lower
This will lead to:
Reduced demand
Reduced customer energy consumption
Maximised DG output
GB
How much could customers save?
Reinforcement savings via DUoS
Reduced energy consumption, 2013 (from CVR ≈ 3 - 7%)
Maximise DG output (from maximising Feed In Tariff income)
£330 over 25 years
£8.6b over 25 years
£15 - £30 pa
£390 - £780m pa
£70 pa
£20m pa
Efficient network solutions  Energy savings  Carbon benefits
16
Smart Street summary
•
•
•
•
Faster LCT adoption
Less embedded carbon
Re-usable technology
Optimise energy and
losses
• Combine into one endto-end system
• Network optimisation
Carbon
Footprint
Low Risk
Challenge
Benefit
• First example of CVR
• First example of
centrally controlled LV
network
• Range of intervention
solutions
• Lower energy bills
• More reliable supply
• Reinforcement savings
17
QUESTIONS
ANSWERS
&
18
Want to know more?
e
[email protected]
www.enwl.co.uk/smartstreet
0800 195 4141
@ElecNW_News
linkedin.com/company/electricity-north-west
facebook.com/ElectricityNorthWest
youtube.com/ElectricityNorthWest
Thank you for your time and attention
19
Smart Grids and Community Energy
Cara Blockley
Low Carbon Projects Manager
20
Our smart grid programme
Leading work on developing smart solutions
Deliver value
from existing
assets
£30 million
Three flagship products
Capacity to
Customers
21
Agenda
Community projects
Supporting community
energy
22
Community projects
23
Power Saver Challenge
Demand
Pilot project to
look at ways of
reducing ‘peak
demand’
24 hours
24
Community engagement
What we’ve done
What we’ve learnt
Promote the project
Incentivised
involvement
Benefited community
groups
Community groups
build trust
Customers will
change behaviour
What we want to
achieve
Stronger, cohesive
communities
Help our engineers
and customer facing
employees
25
Supporting community
energy
26
NEDO smart community project
£20m smart
600 electric and
Working with
Three-year
community project gas hybrid heat
Electricity North
demonstration
led by Japan’s pumps installed in West and Wigan
phase running
New Energy
social housing
& Leigh social
from this April
Development
properties in
housing project 2014 to the end of
Organisation
Wigan and
March 2017
(NEDO)
Greater
Manchester,
some with PV
Heat pumps and information and communication technologies
(ICT) aim to reduce carbon and help provide a demand response
27
Problem - LCTs create network issues
Drift
range
LCTs rapidly surpass voltage and thermal network capacity
28
Smart Street – the first intervention
W
C
L
W
Low cost  Quick fit  Minimal disruption  Low carbon  Low loss  Invisible to customers
Voltage stabilised across the load range  Power flows optimised
29
Smart Street benefits
Now we can stabilise voltage
We can set the voltage level lower
This will lead to:
Reduced demand
Reduced customer energy consumption
Maximised DG output
Efficient network solutions  Energy savings  Carbon benefits
30
Summary
Reduction in
greenhouse gas
emissions
achieved through
community
energy schemes
Community energy
schemes best
supported with
trusted Partners
Visibility and
automation to
provide networks
responsive to
customers’ needs
Lower energy bills,
more reliable supply,
connection savings
31
Want to know more?
e
[email protected]
www.enwl.co.uk/smartstreet
0800 195 4141
@ElecNW_News
linkedin.com/company/electricity-north-west
facebook.com/ElectricityNorthWest
youtube.com/ElectricityNorthWest
Thank you for your time and attention
32
Electricity North West’s
Demand Response demonstration
Simon Brooke
Low Carbon Projects Manager
33
Electricity North West’s innovation strategy
Offer new
services and
choice for the
future
Generate
value for
customers
now
Delivering
value to
customers
Proven
technology
deployable
today
Maximise
use of
existing
assets
Innovative
solutions
to real
problems
34
Our smart grid development
Leading work on developing smart solutions
Deliver value
from existing
assets
Three flagship products
Customer choice
£30 million
Capacity to
Customers
C2C, CLASS and Smart Street demonstrate demand response
35
What is Capacity to Customers?
Capacity
to Customers
Technical
innovation
Utilised
capacity
Current
demand
New commercial
contracts
Latent
capacity
Combines proven technology
and new commercial contracts
Remote control equipment on
HV circuit and close the NOP
Innovative demand side
response contracts
Releases significant
network capacity
Enhanced network
management software
Allow us to control customer’s
consumption on a circuit at the
time of fault
Facilitates connection of new
demand and generation
without reinforcement
Effectively doubles the
available capacity of the circuit
36
Key hypotheses
Demand
reduction
Creates a post
fault demand
response
capability
Active network
management
Efficiency
Customers
Network
Defers/
Existing or new
automation
optimises
customers
creates self
reinforcement
can directly
healing
and reduces
benefit
capability and carbon intensity financially by
facilitates
providing the
capacity release
demand
response
37
Contract arrangements
Demand and generation
New
customers
Existing
customers
NTC
DCUSA
Managed
connection
agreement
Construction
& installation
agreement
Contract
Contract
38
Contract arrangements
Direct relationship with I&C
customer for ‘value’ discussion
Early
lessons
Share contracts early and support
customer through discussions
Works best with one point of
contact - a customer relationship
manager for BaU
39
Demand response results (EXISTING)
Size,price
sector
andfrom
price
of
Size, sector and
of DR
existing
customers
DR from existing customers
35
341kVA
130kVA
30
£k/MVA/yr
25
185kVA
630kVA
800kVA
600kVA
487kVA
2020
15
800kVA
10
5
1800kVA
Utilities
Leisure
Manufacturing
Retail
5200kVA
0
40
Demand response results (EXISTING)
Post fault response is attractive
to customers and Electricity
North West
Early
lessons
Wide range of trial participants,
appears most favourable to
small manufacturers
Very attractive to multiple site
operators
41
Demand response results (NEW)
New connectionNew
customers'
managed
capacity, kVA by sector
connection
customers'
Managed Capacity, kVA by sector
kVA
14,000
10,500kVA
Utilities
IT
Manufacturing
Transportation
12,000
10,000
9,900kVA
7,050kVA
8,000
8,000kVA
6,000
6,000kVA
4,000
2,700kVA
5,000kVA
2,000
600kVA
500kVA
-
500kVA
42
Demand response results (NEW)
Good range of enduring post
fault DR capacities
Early
lessons
New DR predominantly from
small manufacturers again
Post fault DR can operate in
with other DR programmes
43
Project benefits summary
Full set of results and learning from Capacity to Customers will be included in
closedown report with dissemination events planned starting early 2015
Rapidly
deployable
solution
Reinforcement
deferral
Develops new
DR market
Cost
deferral
Carbon
reduction
£
Will better
Releases
Creates post
exploit existing
network
fault demand
assets, thus capacity for use
response
cost-effective
by customers’ market which is
and quickly
LCTs
less intrusive to
implemented
customers
Can defer
reinforcement
costs and the
time taken to
complete the
associated
works
Minimises
carbonintensive
infrastructure
44
Want to know more?
e
[email protected]
www.enwl.co.uk/thefuture
0800 195 4141
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youtube.com/ElectricityNorthWest
Thank you for your time and attention
45
Low Voltage Network Solutions
Breakout 3.1 - LV Network Management
Dr Rita Shaw
46
LV Network Solutions
£
Our largest Tier 1
LCN Fund project
2011 - 2014
www.enwl.co.uk/lvns
£1.5 million
Modelling and
analysis
47
Project scope
Improve LV
assessment and
policy for
all network
Monitor 200 LV
substations
and feeders
To understand
our LV
networks
now
Text
and in future
scenarios
Model
LV networks,
identifying LCT
impacts and
solutions
Assess
monitored LV
network
performance
48
LV monitoring deployment
Challenge
Develop installation
procedures
Site selection / surveys
£
Determine monitoring
requirements without
customer interruptions
Train installation crews
Prepare functional
specifications
Prepare for data capture
Tender and procure
equipment
Roll out to site - 28 pole
mounted and 172 ground
49
Monitoring equipment
2012 UK Energy Innovation
award for the ‘Best Smart
Grid Technology’
GridKey monitoring
equipment at 100
substations
50
Monitoring equipment
Nortech monitoring
equipment at 100
substations
51
Communications approach
Monitoring unit fitted with SIM card
Assigned private, static IP address
Time stamped data logs created every
1 – 10 minutes
DPN3 Protocol
between iHost and
monitor
Unsolicited event
reporting transfers
data logs in near real
time
GPRS /3 G
iHost server at Electricity North
West consists of
communication modules,
databases and web user
interface
Export produces CSV files to be
used by the University of
Manchester
1 set of Rogowski coils fitted per LV way 3 phases
and neutral measured
52
LV monitoring – outcomes
10,000 days of good 10-minute data
At transformer and head of each feeder,
per phase + neutral
Value of monitoring within LVNS
Challenging
but
achieved!
Performance evaluation of monitored LV networks’
Review / improve load estimates for whole network
Validation of network models
Monitoring used in other innovation
projects and BAU
53
Also ... LV feeder midpoint monitoring
100 midpoints and 100
endpoints outside LVNS
project
Smart joint technique
developed by us
54
University of Manchester’s inputs (1)
Build network models
600
500
•Real LV networks = big step forward
[m]
400
•Three-phase four-wire power flow
(OpenDSS)
•Using our GIS + MPAN data +
impedances
300
200
100
100
200
300
400
500
600
700
800
[m]
Challenge: Transforming data from GIS into a power flow engine format
55
University of Manchester’s inputs (2)
Create diverse sets of load and generation profiles
Created pools of 1000 domestic load
/ PV /HP / EV/ microCHP profiles as
inputs to Monte Carlo analysis
Reflect uncertainty of impacts by
picking from pool
24 hours – 5 min resolution
24 hours – 5 min resolution
3
1
0.9
2.5
0.8
0.7
2
[kW]
[kW]
0.6
0.5
1.5
0.4
1
0.3
0.2
0.5
0.1
0
0
0
50
100
150
200
24 Hours - 5 min resolution
250
300
0
50
100
150
200
24 Hours - 5 min resolution
250
300
56
Monte Carlo Impact Assessment Method
PV
• Random
allocation
for each
customer
node
• Random
allocation of
sites and
sizes
Loads
This process is repeated
100 times for each feeder
and penetration level (% of
houses with PV panels).
• Time Series
Simulation
• 3 Phase
four wire
power flow
Power Flow
Results
Storage
Impact Assessment:
1. Customers with
voltage problems
2. Utilization level
3. Energy losses, etc
57
Voltage analysis for one feeder
60
% customers
with voltage
problems
Customers [%]
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
90
100
110
PV Penetration [%]
% customers with PV
Against BS EN50160
Eg 95% of the 10 min mean rms values within +/- 10%
58
Assuming balance understates issues
60
Customers [%]
50
Customers
(% )
Balanced Case
Unbalanced Case
40
30
20
10
0
0
10
20
30
40
50
60
70
80
90
100
110
PV Penetration [%]
PV penetration (%)
59
30 min resolution understates problems
60
1 min
50
1-15 min
resolution
5 min
10
15
30
60
Customers [%]
40
Customers
(% )
min
min
min
min
30-60 min
resolution
30
20
10
0
0
10
20
30
40
50
60
70
80
90
100
110
PV Penetration [%]
PV penetration (%)
60
Multi-feeder analysis What is the hosting capacity for LCTs?
70
Detailed Monte Carlo analysis of
128 LV underground feeders
60
% of Feeders with Voltage Problems
% of Feeders with Thermal Problems
50
40
[%]
Graph shows issues on feeders with
>25 customers
30
20
Often our feeders can accommodate
lots of LCT without thermal or
voltage issues
10
0
PV
EHP
uCHP
EV
EV Fast EV Shifted
1/3 of feeders would have no problem with any PV uptake level
61
If there is a problem ...
Voltage or thermal first?
100
90
80
70
[%]
60
50
40
Voltage
problems before
thermal
Voltage
Problems
before
thanproblems
Thermal Problems
Thermal
Problems
before
Voltage
Problems
Thermal
problems before
voltage
problems
30
20
10
0
PV
EHP
uCHP
EV
EV Fast EV Shifted
62
But if there is a problem ....
First voltage problem occurs at wide variety of % PV uptake
10
9
8
Number of
cases
Number of Cases
7
6
5
4
3
2
1
0
10
20
30
40
50
60
70
80
90
First Problems due to Voltage Issues - PV Case
100
% Customers with PV
Can we predict for a particular feeder?
Utilisation? Length? Impedance? Customer numbers?
63
Scatter even on the best metrics
Many feeders present no problems even at 100% uptake
110
110
100
100
data
data
fittedcurve
curve
fitted
90
90
% Customers
with PV
Penetration level
80
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
00
00
6
8 1200 10 1400 12
200 2 400 4 600
800
1000
1600
Custumer
Number
and Length
[%*m]
Utilization
Level and
Total Path
Impedance
[%*ohm]
14
1800
5
x 10
DNO
Combined
friendly network metric
==
(initial
(customer
utilisation
numbers
x totalx path
total impedance)
length)
64
Connect and manage/monitor for PV
Our network can often accept lots of LCTs,
so let customers connect quickly!
But hosting capacity is variable and difficult to predict,
so monitor to check voltage etc
The analysis can only broadly suggest when problems
will occur, so monitor early!
Eg on average no problems until around 45 PV on feeder,
but we monitor at ~20 PV systems
65
Analysis of solutions
Subte1 - Feeder4
80
Network reinforcements
Radial Operation
Meshed Operation
70
On-load tapchangers in LV
networks
Customers (% )
Customers [%]
60
50
40
30
20
10
Loop connection of LV feeders
0
0
10
20
30
40
50
60
70
80
90
100
PV Penetration [%]
PV penetration (%)
Link to ‘Smart Street’ project
% of customers with voltage
problems
66
What we have learnt
Products +
procedures
What /when/ where to
monitor in future
How to
monitor
at LV
How
our LV
performs
now
In detail for
monitored networks
Improved load
estimates for whole
LV+HV network
How our LV network
will perform
with LCTs
Hosting capacity of underground LV networks for LCTs
Potential network solutions, with implications for future DNO policy
A (rough) future capacity headroom model for whole LV+ HV network
67
Why are we doing this
Leverage learning to support business
Drive value for our customers
68
QUESTIONS
ANSWERS
&
69
Want to know more?
e
[email protected]
www.enwl.co.uk/thefuture www.enwl.co.uk/lvns
0800 195 4141
@ElecNW_News
linkedin.com/company/electricity-north-west
facebook.com/ElectricityNorthWest
youtube.com/ElectricityNorthWest
e
[email protected]
Thank you for your time and attention
70
Network Management:
Centralised or Distributed?
Dr Geraldine Bryson
Future Networks Technical Manager
71
What does it mean?
C
Centralised
Applications layer
NMS layer
SCADA layer
Communications layer
Distributed
72
Distributed – historic
Protection relays
Voltage control
Substation
Limited communications requirements
Report when operated
Operate based on setting
73
Distributed – BaU today
Protection relays
Voltage control
Substation
Remote control
Increased communications requirements
Instructions sent from control engineer or NMS
74
Distributed – smart
Protection relays
Voltage control
Distribution
substation
Remote control
Sensors on network
LoVIA – Low Voltage Integrated Automation
75
Distributed management
Not communication reliant
Improvement in performance – no latency
No integration with NMS
Pros
No protocol issues
Only localised control
Network awareness can be expensive
High cost to maintain local systems
Cons
76
Communications
Hard wired to strategic sites
Controllable devices at 132kV and 33kV
Historical
Unreliable to remote sites
Reliability and resilience improved
Driven by increased use of mobile devices
Today
Controllable devices at 11kV
Controllable devices at LV
Smart meters
Future
Increasingly reliable communications
77
Centralised - historic
NMS
Centralised
SCADA
Central system to show operational status
Operations commanded by control engineer
Mainly at higher voltages
78
Centralised - today
NMS
Centralised
ARS
SCADA
Fault restoration algorithms
Knowledge of network topology
Operations commanded by application
Utilises remote control at distribution substations
79
Centralised – smart
ARS
Centralised
C2C
CLASS
Smart
Street
Others
NMS
SCADA
Data from remote sensors
Knowledge of network
Applies algorithms to wide area of network
Only central logic to be kept updated
80
Centralised management
Offers control over a wider area
Optimise across a number of apps
Network aware at lower cost
Pros
Lower cost to maintain central system
Heavily reliant on communications
Needs local fail safe mechanism
Cons
81
Conclusions (1)
Increased monitoring of network
Need to distinguish data from information
Sensors
Data to app for processing
Increasingly more reliable
Increased use of controllable devices
Communications
More forms of communication
Centralised with reliable comms – way forward
Works in other industries
Algorithms
Deterministic or iterative
82
Conclusions (2)
ENWL have both centralised and distributed
Both have roles in smart grids - application dependent
Centralised solves more at lower cost
Deployment
Distributed require repeated investment to maintain
Vendors have basic building blocks
Need exact requirements from Industry
Availability
ENA active network management group
UK need to influence EU standards
EU standards influence vendors
Standards
Need BaU industry standards
83
Want to know more?
e
[email protected]
www.enwl.co.uk/thefuture
0800 195 4141
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facebook.com/ElectricityNorthWest
youtube.com/ElectricityNorthWest
e
[email protected]
Thank you for your time and attention
84