The electrical system 2

Generation(power stations)

p.93-112 +117 (California)

Literature for today

Shively Ch. 4.

I-D E/S

HS

I-D E/S

HS

Terminology

What is the difference between power and energy?

Speed & Distance

Speed(KM/Hr)

Hours(Hr)

Distance(KM)

12 KM/Hr 1 12 KM12 KM/Hr 2 24 KM

Power & Energy

Power(MW)

Hours(Hr)

Energy(MWh)

200MW 1 200MWh200MW 2 400MWh

Speed & Distance

KM/hr Hr KM

Power & Energy

MWh/Hr Hr MWh

=MW

Terminology

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000G

erm

any

Fran

ce UK

NM

S10

Italy

Spa

inP

olan

dS

wed

enN

orw

ayN

ethe

rland

sB

elgi

umC

zech

Finl

and

Aus

tria

Rom

ania

Gre

ece

Por

tuga

lB

ulga

riaH

unga

ryD

enm

ark

Slo

vaki

aIre

land

Slo

veni

aE

ston

iaC

roat

iaLa

tvia

Cyp

rus

Lith

uani

aLu

xem

bour

gM

alta

Annual consumption in 2011 in GWh

5 €cent/KWh= 0.05€/ KWh= 50€/ MWh

• I have a nuclear with a capacity of 500MW (power).• How much energy can this power plant produce in a

year?

• How many hours are in a year?• 24*365= 8760

– (Q&D, +/- 10.000 minus 12%)

≈500MW * 10.000 hours≈ 5.000.000MWh≈ 5.000GWh≈ 5 TWh=4.4 TWh

• In the EU in 2012 there was a capacity of 120GW (power) in solar. This produced 100TWh in 2012.

• What is approximately the capacity factor of EU solar?

• How many hours are in a year?– 10.000 minus 12%

• If it ran at full capacity (100% c.p.) it would have produced about 120 * 10.000GW≈1.200.000 GW≈1.200 TW≈1.000 TW (minus the 12%)

• But it produced 10 times less…• Thus c.p. is ≈ 10%

Where the world gets its energy

?

Renewables EfficiencyCarbon emissions

EU’s 20-20-20 strategy for 2020

Acceleration of Germany Nuclear Phase-out

Acceleration of Germany Nuclear Phase-out

Germany to start up more coal-fired power stations than at any

time in the past 20 years

Irsching-5 in Bavaria, Germany (EON )

A gas-fired power station,Commissioned in 2010

“Germany needs flexible gas plants to underpin a greater share of renewable sources”

German environment Minister Peter Altmaier

?

“energy providers have little interest in building new power plants”

Der Spiegel, October 10, 2012

German electricity wholesale market

December, 25th,2013, 2:00, a negative hourly price record: -222 €/MWh

2. Why coal rather than (new) gas

generatiors?

1.Why a diversity of generation

types?

3. Negative prices?

Effect of climate policy

INTROOverview of generation

types

Hydro-plant

VIDWednesday 2_ Hydroelectic Power - How it Works (hq).mp4

Nuclear plants

Baseload

Nuclear Fission

Cost escalation curse

1979: Three Mile Island

1986Chernoby

Nuclear FusionExperimental but breakthrough is

imminent (since 1954)

"Our children will enjoy in their homes electrical energy too cheap to

meter...

“famines will be known as matters of history”

Lewis Strauss, 1954Chairman of the US Atomic Energy Commission

referring to the prospects of nuclear fusion (not fission).

Nuclear Fusion

Best nuclear fusion reactor has a net energy output of -30%

1952

Large coal plants

Baseload

Combined heat & power (must-run)

Gas burning plants

Peaker

http://iea-etsap.org/web/Highlights%20PDF/E02-gas_fired_power-GS-AD-gct%201.pdf

OCGT

CCGT

OCGT

VIDWednesday 2_ Gas Turbine Basics (hq).mp4

CCGT

Oil burning plants

Peaker

Wind turbines Solar panels

Renewables(not dispatchable)

Renewables(dispatchable)

Biomass

Renewable energies

Concentrated solar power

VID• Wednesday 2_ Wind Turbines - How does it actually work- Investment-

(hq).mp4• What is Biomass- (hq)

Location of main electric plants

Jiří Krejsahttp://www.cez.cz/en/power-plants-and-environment/maps-of-power-plants.html#!&category%5B%5D=obnovitelnevodnielektrarny&zoom=7

HydroThermal (mostly black and brown coal)Nuclear

TOP 10 producers in ČR 2010

Source: energostat.cz, ERU

1. ČEZ, a.s. 56004,4 65,20%2. Sokolovská uhelná, právní

nástupce, a.s. 3366,6 3,92%

3. Dalkia Česká republika, a.s. 1 961,83 2,28%4. Elektrárny Opatovice, a.s. 1853,66 2,16%

5. Alpiq Generation (CZ), s.r.o. 1399,25 1,63%6. UNIPETROL RPA, s.r.o. 1167,62 1,36%7. Energotrans a.s. 1132,82 1,32%

8. ArcelorMittal Ostrava a.s. 1010,14 1,18%9. United Energy, a.s. 616,49 0,72%10. ENERGETIKA TŘINEC, a.s. 607,87 0,71%

Total ČR 85900,1 80,47%

Jiří Krejsa

I-D E/S

HS

NEED:Backup capacity

NEED:More transmission lines

Multiplication by 4!

The future of the EU transmission network

2050 Increase from

34 GW to 127 GW

Feed-in tariffs

500 €/MWh 200€/MWh

Coal or gas plant costs

40€/MWh

2004 2012

Case of Germany

Coal or gas plant costs

0.04€/ KWh=40€/ MWh

CZ

Jiří Krejsa

Jiří Krejsa

ConsumersP (€/kWh)

62

63

Consumers

P (€/kWh)

64

Industry

P (€/kWh)

65

The electrical system 2

Generation(power stations)

2. Why coal rather than (new) gas

generatiors?

1.Why a diversity of generation

types?

3. Negative prices?

Climate policy

Today’s lecture based on:

p.32, p.34-39, p.44-48.

Optimal Dispatch

Nuclear Coal Gas Oil Shortage

Exceptionally high

Very highModerateLow

Load curve

00 05 07 10 13 15 18 24

Very Low

Low

Moderate

Very high

Exceptionally high

Very Low

P

0

20

30

50

P=0

P=20

P=30

P=50 P=CAP

Hours

71

Demand & Supply curve

Power Energy(Capacity)

For finding the cheapest technique it is useful to know the average cost…

Fixed cost Power (MW)

years Days/ year

Hrs/ day

Hrs / year

total hours

FC/ MWh

1,300,000,000 500 30 365 24 8760 262800 9.9

5,000,000,000 500 30 365 24 8760 262800 38.1

≈40

≈10

Levelized costs of generation

Technology Costs Table

Multitude of generation types

Trade-off:Economics of scale

Flexibility

Baseload power plants

Midload power plants

Fixed cost per MWh

Variable cost per MWh

Baseload 40 0

Midload 20 30

Peaker 10 50

Peaker power plants

Technology Costs Table

9 12 15 170 24

Daily Demand in MW

1

2

3

TIME

DURATION (%)

Yearly Demand in MW

365

720

1085

100

Load-Duration Curve:Duration[y] = Pr[Demand > y]

16 250

Load Curve

9 12 15 170 24

1

2

3

TIME

DURATION (%)10033

365

720

1085

160

Yearly Demand in MW

Daily Demand in MW

Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

9 12 15 170 24

1

2

3

TIME

DURATION (%)10025160

365

720

1085

Yearly Demand in MW

Daily Demand in MW

Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

9 12 15 170 24

1

2

3

TIME

DURATION (%)10025160

365

720

1085

Yearly Demand in MW

Daily Demand in MW

Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

9 12 15 170 24

1

2

3

TIME

DURATION (%)10025160

365

720

1085

Some random variation in the levels

Yearly Demand in MW

Daily Demand in MW

Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

9 12 15 170 24

1

TIME

DURATION (%)10025160

Demand in MW

365

720

1085

Some random variation in the levelsDaily

Demand in MW

2

3

Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

Load-Duration Curve:Duration[y] = Pr[Demand > y]

Source: ERU

Load-Duration Curve:Duration[y] = # Hours where [Demand > y]

Load-Duration Curve:Duration[y] = Pr[Demand > y]

9 12 15 170 24

1

2

3

TIME

Daily Demand in MW Load Curve

Daily variations (UK)

DURATION (%)100500

1

2

3

9 12 15 170 24

1

2

3

TIME

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

DURATION (%)100500

9 12 15 170 24 TIME

1

2

3

1

2

3

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

FIND THE MISTAKE!!!

DURATION (%)100500

9 12 15 170 24 TIME

1

2

3

1

2

3

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

33.3

DURATION (%)100500

9 12 15 170 24 TIME

1

2

3

1

2

3

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

33.3

A bit a difficult load-duration curve (and also

quite a-typical)

DURATION (%)100500

9 12 15 170 24 TIME

1

2

3

1

2

3

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

How to get this more typical,

nicer LD curve?

DURATION (%)100500

1

2

3

9 12 15 170 24

1

2

3

TIME

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

DURATION (%)100500

9 12 15 170 24 TIME

1

2

3

1

2

3

Daily Demand in MW

Daily Demand in MW

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Load Curve

DURATION (%)100500

1

2

3

Fixed cost per MWh

Variable cost per MWh

Baseload 40 0

Peaker 10 50

Daily Demand in MW D=3-2* Duration

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Technology Costs Table

0

60

40

Capacity factor

Baseload

Peaker

100%60%

10

(=8760 hours/year)

Fixed cost per MWh

Variable cost per MWh

Baseload 40 0

Peaker 10 50

0%

Cost/MWhScreening curve

(Capacity-cost based)

Technology Costs Table

Screening curve(Capacity-cost based)

Screening curve(Energy-cost based)

0

60

40

Capacity factor

Baseload

Peaker

100%60%

10

(=8760 hours/year)

Fixed cost per MWh

Variable cost per MWh

Baseload 40 0

Peaker 10 50

0%

Cost/MWh

Use baseload when capacity factor > 60%

Use peakers when capacity factor < 60%

Screening curve(Capacity-cost based)

Technology Costs Table

Use baseload when capacity factor > 60%

Use peakers when capacity factor < 60%

0

60

40

Capacity factor

Baseload

Peaker

100%60%

10

DURATION (%)100500

1

2

3

BASELOAD

D=3-2* Duration

1.8

PEAKER

Daily Demand in MW

60

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]

Screening curve(Capacity-cost based)

Nuclear

Oil

Old, inefficient plants (old Coal & OCGT)

Gas (CCGT)

Coal

Daily Load-Duration Curve:Duration[y] = Pr[Demand > y]