– Workshop 3 –Birmingham, 10 January 2008

Current GB SQSS Approach

Cornel Brozio

Scottish Power EnergyNetworks

This Presentation

Overview of current SQSS methodology

Interpretation of Planned Transfer and Required Transfer

Variations on SQSS approach

Comparison and Conclusions

Approach 1 - SQSS Methodology

a) Current method with wind AT = 0.72 Section 1.1, Appendix 3

b) Different exporting and importing area wind AT (0.72/0.05)

Section 1.3.1

c) Variable wind A-factors Section 1.3.2, Appendix 4

Current SQSS Methodology

Transmission boundary capability at ACS peak

Planned Transfer (Appendix C of SQSS)

Interconnection Allowance (Appendix D of SQSS)

Required Capacity = PT+IA

1(a) – 1

Setting up Planned Transfer

Ranking Order technique Set Plant Margin 20% Assumption is that market will deliver around 20%, but

many closures are unknown Plant least likely to run is treated as non-contributory

Straight Scaling technique Scale generation to meet demand Scaling proportional to availability at time of ACS peak

1(a) – 2

Ranking Order Example

Unit or Module

Registered Capacity (MW)

Contribution to Plant Margin

(MW)

Cumulative Capacity (MW)

Unit 1 500 500 500

Windfarm A 600 0.4 600 = 240 740

Windfarm B 200 0.4 200 = 80 820

. . . . . . . . .

Unit J 200 200 71900

Unit K 200 200 72100

Unit L 100 100 72200

For ACS demand of 60GW

Less

like

ly t

o ru

n

1(a) – 3

WindWindet RLRA

Wind Equivalent in Ranking Order

Average availabilityof a thermal unit

(At 0.9)

Registered capacity ofequivalent thermal unit

Wind generation winter load factor (LWind 0.36)

Wind generationregisteredcapacity

Average P available from equivalent

thermal unit

Average P available from wind generation

Re = 0.4 RWind

1(a) – 4

Straight Scaling

Power output of generator i of type T

PTi = S AT RTi

Availability atACS peak

Registeredcapacity

Match generationand demand

(Applies to entire network)

With a plant margin of 20% and AT = 1.0, S = 0.833

1(a) – 5

Availability Factors

SQSS does not prescribe AT values Thermal and hydro units:

AT = 1.0

Wind generation: AT = 0.72

PT in 833021

1.

.TiP

PT in 6072021

1.

..

TiP

1(a) – 6

Planned Transfer Example

AREA 1

AREA 2

RTi = 10000 MWD1 = 6000 MWG1 = 8333 MW

RTi = 62000 MWD2 = 54000 MWG2 = 51667 MW

PT = 2333 MW

System in Planned Transfer conditionTotal ACS peak demand = 60GW

1(a) – 7

Interconnection Allowance

Planned Transfer condition set up

Select boundary, i.e. split system into two parts

Find IA from the ‘Circle Diagram’

Boundary capability: PT + IA for N-1 PT + ½IA for N-2 or N-D

1(a) – 8

Circle Diagram

)(2 21

11

DD

GD

1(a) – 9

IA Application Example

AREA 1

AREA 2

RTi = 10000 MWD1 = 6000 MWG1 = 8333 MW

RTi = 62000 MWD2 = 54000 MWG2 = 51667 MW

PT = 2333 MW

System in Planned Transfer condition

%9.11600002

83336000

)(2 21

11

DD

GD

Circle diagramx-axis:

y-axis: 2.1%IA = 1260 MW

1(a) – 10

What does the IA provide?

Capacity for a generation shortage in one area to be met by importing from another area (most of the time)

N-2 or N-D requirement (PT+½IA) can be met for 95% of actual generation and demand outcomes at ACS peak, assuming Enough generation in the exporting area No local constraints

PT PT + IAPT + ½IA

Expected boundarytransfer at ACS peak

Actual Boundary TransferF

requ

ency

BoundaryTransfer

Variations Considered for Wind

Keep PT+IA and PT+½IA at same percentile of possible boundary transfers

Probabilities of exceeding N-1 or N-2 capabilities remain broadly constant

Variations considered: Approach 1(b): Different wind A-factors for importing

and exporting areas Approach 1(c): Variable wind A-factors based on wind

volumes in each area

Different Export and Import Wind A-factors

PT+½IA captures all but the highest 5% of boundary transfers When imbalance in available power is highest Should include imbalance due to wind conditions

At 60% in PT, support from wind generation in importing area is over-estimated

1(b) – 1

Importing Wind A-factor

In exporting area 60% is approximately P90 of wind output

‘Mirror’ exporting area by using P10 of wind generator power output:

About 4% of rated capacity AT = 0.05 (around 0.05 0.833 = 0.04 in PT)

Approach 1(b) Different (but constant) A-factors Exporting area AT = 0.72 for wind (60% in PT)

Importing area AT = 0.05 for wind (4% in PT)

1(b) – 2

Approach 1(c): Variable Wind A-factors

Aims to find A-factors as functions of relative wind generation volumes for any boundary

Monte-Carlo simulation to find distribution of transfers and find P99 and P95

Using SQSS approach for same boundary, adjust wind A-factors until PT+IA (N-1) matches P99 and PT+½IA (N-2) matches P95

with minimum error.

Exporting Area Wind A-Factor

y = -0.5706x + 0.8657

0.0

0.2

0.4

0.6

0.8

1.0

1.2

-0.2 0 0.2 0.4 0.6 0.8 1 1.2

Difference between conventional and wind generation capacity in the exporting area in p.u. on system demand

Win

d A

-fac

tor

in e

xpo

rtin

g a

rea

(AW

E)

Demand System Total

Generation Wind- Generation alConvention

Win

d A

-Fac

tor

1(c) – 2

Importing Area Wind A-Factor

y = -0.0261x + 0.0593

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0 0.2 0.4 0.6 0.8 1 1.2

Difference between conventional and wind generation capacity in the importing area in p.u. on system demand

Win

d A

-fac

tor

in im

po

rtin

g a

rea

(AW

I)

Demand System Total

Generation Wind- Generation alConvention

Win

d A

-Fac

tor

1(c) – 3

Results for 2007/8

2007/8

0

2000

4000

6000

8000

10000

12000

14000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Boundary

Req

uir

ed B

ou

nd

ary

Cap

acit

y (M

W)

0.72/0.72

0.72/0.05

Variable

RT

(M

W)

Results for 2020/1

2020/21

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Boundary

Req

uir

ed B

ou

nd

ary

Cap

acit

y (M

W)

0.72/0.72

0.72/0.05

Variable

RT

(M

W)

Summary

Approach 1(a) – Single A-factor (0.72) Works well, but over-estimates wind contribution in importing area

Approach 1(b) - Different A-factors (0.72/0.05) Extends existing approach System security remains broadly constant

I.e. probability of exceeding N-1 or N-2 capability remains approximately constant

Approach 1(c) - Variable A-factors Difficult to find robust A-factor functions (scatter on graphs) Additional complexity Except high-wind export boundaries, very similar RT to constant

0.72/0.05

Drawback - Different PT for each Boundary

Both variations of SQSS approach mean that PT becomes boundary dependent

Different A-factors in each area

Single PT condition no longer exists

Importing and exporting areas not always clear

By exchanging A-factors, direction of PT can be reversed

Recommendation

As at present, approach would remain supported by cost-benefit analysis

If existing SQSS approach is to be retained, adopt Approach 1(b)

Different (but constant) A-factors in exporting and importing areas (AT = 0.72 or 0.05)