Future Transmission Networks

Richard Smith Future Transmission Networks Manager 4th Annual Smart Grids & Cleanpower 2012 Conference www.cir-strategy.com/events

2

The future: efficiency, decarbonisation and electrification

new homes & retrofit

Heat pump

Decarbonised electricity… and decarbonise transport

Transport Electricity Heat

Efficiency and innovation Insulate and reduce Smart Meters &

Appliance efficiency

De-carbonise heat

Biomethane

CNG

Gas backup & embedded generation

3

Network capacity will need to increase

Distribution networks will need to more than double their capacity…

2010 2030 2050

Household demand* ~2.5kW ~4.7kW ~7kW

Number of homes 26m 31m 36m

Embedded generation ~8GW ~15GW ~20GW

Network loading (kW/km)

~75 ~170 ~300

Network scale X2.3 X4.0 Network scale vs

2010 levels * After diversity average peak demand

Distribution network operation will change in future… ¾  More distributed and micro generation (solar

PV, CHP etc.)

¾  Electric vehicle and heat pump demand increasing load dramatically in hot spot areas

¾  Grid Supply Points being permanently interconnected, opening up the possibility of loop flows through the distribution networks

¾  Possibility of local dispatch within Distribution networks to control local flows

¾  Two-way, variable power flows increase with demand side response

Smart network initiatives will see a move away from radial operation…

4

When will capacity need to increase?

Appliance efficiency will also determine the optimum transition point and may extend the ‘window’

Emissions intensity pre appliance (g/kWh)

0

200

400

600

800

1,000

2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity (total grid) Marginal electricty for transport Marginal electricty for heatNatural Gas Gas-Biogas mix OilOil-Biofuel mix

‘Window’ for transport

‘Window’ for heat

5 5

Where might this happen?

6 6

Transmission is already largely smart

Condition monitoring

Remote asset management and

monitoring (RAMM) Voltage Control

Circuit Rating Enhancement

Operational Tripping Schemes (OTS)

Auto-switching schemes

Power Flow Control Remote Substation Control

Network Output Measures Risk management

7

Now to 2020: generation build more significant than EVs and heat pumps

Change under Gone Green (GW)

(30)

(20)

(10)

0

10

20

30

40

Generation Demand

Gas Nuclear CoalHydro Interconnector WindBiomass Marine GasOil Electric cars* Heat pumps*

* Electric vehicle and heat pump at mid-range peak demand.

France

existing electricity network

potential wind farm sites

potential nuclear sites

interconnectors

France

Netherlands

Belgium

Norway

Ireland

8

The need for more smart actions

Scotland to England unconstrained transfers

-2000.0

0.0

2000.0

4000.0

6000.0

8000.0

10000.0

12000.0

0.0 1000.0 2000.0 3000.0 4000.0 5000.0 6000.0 7000.0 8000.0

Hours

MW 2013

2020

Gone Green Scenario simulated with ELSI

2020 proposed intact netw ork f irm N-2 capacity

2013 planned intact netw ork f irm N-2 capacity

2 x HVDC links + Series compensation

smart operation task increasingVolume of required operational management actions increasing

9 9 9

Generation Demand

Variable generation

0

200

400

600

800

1,000

1,200

1,400

1,600

0

200

400

600

800

1,000

1,200

1,400

1,600

01-Jan

05-Jan

10-Jan

15-Jan

20-Jan

25-Jan

30-Jan

01-Jan

05-Jan

10-Jan

15-Jan

20-Jan

25-Jan

30-Jan

MW

Large generation

Inflexible generation

Active distribution networks

Smart(er) grids & meters, energy storage

Active demand

Time of use tariffs

30

35

40

45

50

55

60

00:0

0

01:0

0

02:0

0

03:0

0

04:0

0

05:0

0

06:0

0

07:0

0

08:0

0

09:0

0

10:0

0

11:0

0

12:0

0

13:0

0

14:0

0

15:0

0

16:0

0

17:0

0

18:0

0

19:0

0

20:0

0

21:0

0

22:0

0

23:0

0

Time of Day

Ele

ctri

city

Dem

and

(G

W)

2020 Demand ~ 15GWh (daily) - 1.5million vehicles

Typical winter dailydemand

Pea

k C

om

mu

tin

g T

ime

12,000 miles p.a.

Pea

k C

om

mu

tin

g T

ime

Optimal Charging Period

Distributed generation

Smarter transmission

Smart zones HVDC Series compensation WAM

Balancing supply and demand

10 10 10

When the wind blows…

0

500

1000

1500

2000

2500

3000

3500

4000

00:0003

:0006

:0009

:0012

:0015

:0018

:0021

:0000

:0003

:0006

:0009

:0012

:0015

:0018

:0021

:0000

:0003

:0006

:0009

:0012

:0015

:0018

:0021

:0000

:0003

:0006

:0009

:0012

:0015

:0018

:0021

:0000

:0003

:0006

:0009

:0012

:0015

:0018

:0021

:0000

:0003

:0006

:0009

:0012

:0015

:0018

:0021

:0000

:0003

:0006

:0009

:0012

:0015

:0018

:0021

:00

02/01/2012 03/01/2012 04/01/2012 05/01/2012 06/01/2012 07/01/2012 08/01/2012

Wind Forecast Wind Actual

4m/s 15m/s 25m/s

Pow

er

Wind Speed

Wind Cut-out 3rd January 2012

11 11

Making transmission smarter

Timely provision of information to inform

decisions

‘Fit for Purpose’ Network

Develop services to deliver energy securely and

efficiently

¾  Optimising asset utilisation

¾  Improving power system access

¾  Enhancing boundary transfer capability.

¾  Better network modeling and prediction

¾  Improved planning & operational flexibility

¾  Balancing generation with demand

¾  Intelligent network automation

¾  Managing the generation mix

¾  Flexible networks

¾  Demand side management.

12 12

New technology & systems

¾  Manage network stability ¾  Coordinate power flow and voltage control

between regions ¾  System integrity protection schemes ¾  Regional congestion management

Wide Area Protection & Control

¾  Widespread installation of sensors and monitors ¾  Network expansion ¾  Data storage and capacity management ¾  Applications to support real time management

System Monitoring & Visualisation

¾  Assist Control Engineer workload ¾  Manage complex processes ¾  Automatic fault restoration ¾  Foundations of regional autonomy

Network Automation

13 13

Plan

ning

/Con

sent

ing

Diff

icul

ty

(lead

tim

e)

Primary asset cost for given capacity

<1 sec 0-5 mins 5-20 mins 20 mins – 6 hrs post fault continuous rating

LOW

ER

HIG

HER

CONTROL RISK

Control Philosophy Transition

Traditional approach. People centric

process. Conventional asset

N-2

ENSG approach Assets worked

dynamically into very short term ratings

Steady state flows Solving peak half hour implies operable at all points

Dynamic flows Need to solve all points and transitions

very hard

hard Operator Response Time

Control philosophy change

14

Delivering resilience

Process Safety Robust automation

Understand complexity Identify ‘Fail safe’ modes

Develop end to end solutions

Network management Regional autonomy

Information flow Managing Third Party actions

Interfaces with legacy systems Coordinate

System Awareness Good prediction

System monitoring Scenario analysis

Modelling validation Quality of information

Operational complexity

System security

Network utilisation

Transmission Smarter Transmission

15 15

At the heart of the energy transformation…