1. Current GB SQSS Approach
Cornel Brozio
Scottish Power EnergyNetworks
– Workshop 3 –
Birmingham, 10 January 2008

2. This Presentation Overview of current SQSS methodology
Interpretation of Planned Transfer and Required Transfer
Variations on SQSS approach
Comparison and Conclusions
Overview of the approach followed presently.
Something about PT and RT and what they mean.
Know that current method is limited – considered how it could be adapted or modified to work better for wind.
Results from variations and comparison.

3. Approach 1 - SQSS Methodology
Current method with wind AT = 0.72
Section 1.1, Appendix 3
Different exporting and importing area wind AT (0.72/0.05)
Section 1.3.1
Variable wind A-factors
Section 1.3.2, Appendix 4
These variations are:
Called approaches 1(a), (b) and (c).
Link to report sections.

4. Current SQSS Methodology
1(a) – 1
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
Approach 1(a)
MITS requirements at ACS peak
Boundary splitting system into two parts – transmission capacity across this boundary.
PT refers to a system (at winter peak) with PM <= 20% and generation scaled to meet demand.
2-Stage process: PT and IA

5. 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
PT refers to a system (at winter peak) with PM <= 20% and generation scaled to meet demand.
Scaling sets up PT condition.
PT now exists on any circuit or boundary in the network.

6. Ranking Order Example For ACS demand of 60GW Less likely to run
Unit or Module
Registered Capacity (MW)
Contribution to Plant Margin (MW)
Cumulative Capacity (MW)
Unit 1
500
Windfarm A
600
0.4  600 = 240
740
Windfarm B
200
0.4  200 = 80
820
. . .
Unit J
71900
Unit K
72100
Unit L
100
72200
Less likely to run

7. Wind Equivalent in Ranking Order
Average P available from equivalent thermal unit
Average P available from wind generation
Wind generation
registered
capacity
Average availability
of a thermal unit
(At  0.9)
Convert each wind farm, or group of wind farms, to an equivalent thermal unit.
Equivalent thermal unit has same average power availability as wind generation.
Assume wind will always run at maximum available power, therefore, average available power = load factor (in winter).
Divide by thermal available power to convert to equivalent thermal unit (full registered capacity is used in ranking order).
Mention that 36% is based on data measured in Southern Scotland. Load factors were:
Winter: 36%
Summer: 23%
Year: 30%
Registered capacity of
equivalent thermal unit
Wind generation winter load factor (LWind  0.36)
Re = 0.4 RWind

8. (Applies to entire network)
Straight Scaling
1(a) – 5
Power output of
generator i of type T
Registered
capacity
PTi = S  AT  RTi
Match generation
and demand
(Applies to entire network)
Availability at
ACS peak
Apply when PM has been reduced to <= 20% by ranking order technique.
All contributory generation is scaled.
Imports/exports like France or NIE are ignored here. However, they are not scaled, but are treated as demand (Pos = export, Neg = import).
If all AT are the same, its value does not matter; S x AT will be the same.
S = 1/1.2 = 0.833
With a plant margin of 20% and AT = 1.0, S = 0.833

9. Availability Factors SQSS does not prescribe AT values
Thermal and hydro units:
AT = 1.0
Wind generation:
AT = 0.72
Sometimes hydro AT = 0.96 (P  0.80 in PT)
If plant margin is exactly 20%…

10. Planned Transfer Example
RTi = MW
D1 = 6000 MW
G1 = 8333 MW
AREA 1
PT = 2333 MW
AREA 2
 RTi = MW
D2 = MW
G2 = MW
PT would now exist on any boundary.
PM = 20%, so S = and total generation is 72GW.
PM (North) = 67%, PM (South) = 14.8%
** Shown how PT is set up, now moving on to application of IA.
System in Planned Transfer condition
Total ACS peak demand = 60GW

11. 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
Applying IA to the system.
Steps to set up system with IA or IA/2.
Under these conditions, for secured event (N-1, N-2, busbar, mesh corner),
there may not be
loss of demand
unacceptable overloading
voltages outside limits
system instability

12. 1(a) – 9
Circle Diagram
Origins a bit hazy, but reported to be based on observed transfers in the 1940’s.
Reviewed in early 1990’s and found to still be appropriate for system.
See appendix D in SQSS.
Total ACS peak demand = D1+D2
D1+G1 = Dem+Gen in small area (Area 1 in example).

13. IA Application Example
Circle diagram
x-axis:
RTi = MW
D1 = 6000 MW
G1 = 8333 MW
AREA 1
PT = 2333 MW
AREA 2
 RTi = MW
D2 = MW
G2 = MW
Find IA from circle diagram
N-1: 3593MW
N-2: 2963MW
y-axis: 2.1%
IA = 1260 MW
System in Planned Transfer condition

14. 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

15. Actual Boundary TransferPT
PT + IA
PT + ½IA
Frequency
PT is the median transfer. Depending on actual demand and generation outcomes, the boundary transfer could be higher or lower (even negative).
PT+IA/2 gives around P95 (but, N-2/D less likely than N-1)
PT+IA gives around P99 (but, more likely than N-2/D)
Wind will change the shape/parameters of the distribution – we want to keep N-1 and N-2 probabilities/percentiles constant.
With wind, PT and the shape of the distribution will be different, but we want to approximately maintain PT+IA/2 at P95 and PT+IA at P99.
Boundary
Transfer
Expected boundary
transfer at ACS peak

16. 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

17. Different Export and Import Wind A-factors
1(b) – 1
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
Approach 1(b)
We are trying to capture the high 5-10% of transfers where available power in Area 1 is much higher than the available power in Area 2. I.e. when the imbalance in available power is highest. This should include imbalance due to wind conditions.
An important side effect of this is that the PT now becomes boundary dependent, i.e. a different PT needs to be set up for each boundary to study.

18. Importing Wind A-factor
1(b) – 2
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  = 0.04 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)

19. 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.
Consider a particular boundary.
Assumption is that N-1  P99 and N-2  P95.
Simulation was carried out for all boundaries.
Simplified simulation was used to determine A-factor functions; these were then applied to scenario.

20. Exporting Area Wind A-Factor

21. Importing Area Wind A-Factor

22. Results for 2007/8
RT (MW)
Results for Approaches 1(a), 1(b) and 1(c)

23. Results for 2020/1
RT (MW)

24. 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
For high-wind boundaries, economics are very likely to justify more transmission.

25. 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
Approaches 1(b) and (c)

26. 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)