Long Term generation/transmission planning Process
The main objective is to develop a national generation and transmission master plan – Identify optimal generation development scenarios (for the period from year 2022 to year 2033). – Determine the optimal transmission scenarios to facilitate generation plan for year 2022 to 2030. – Determine the most economically and technically feasible transmission expansion plans and corresponding generation development scenarios.
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Develop long term generation/ transmission expansion planning scenarios for the period from year 2022 to year 2030 by performing techno-economic analysis. • Analyze various generation planning scenarios and group them based on the requirement for the development of bulk transmission expansions (0ver 50 identified in a recant study in South America) • Base case (plan as is) • Other scenarios based on known generation resource availability • Account for uncertainties (load forecast, economic, technology and policies) • Derive the optimized generation plan for each scenario (OPTGEN based simulations) (sub -optimized) • Select optimal generation development (based on potential development options) • Staging generation development, • Cost of development and cost of energy • Identify potential transmission expansion scenarios to cater for generation planning scenarios • Optimize transmission developments considering economic benefits (SDDP program based simulations) • Identify additional transmission development required to comply with N-1 reliability criteria (detailed load flow studies) • Perform preliminary stability studies (PSSE) • Perform detailed emt studies (PSCAD – can be deferred to later stages of development) 3
Generation development Scenarios A number of generation development scenarios are developed to account for the uncertainty associated with the data inputs to generation/transmission planning process • Generation resource availability is known • Excess energy resources are available compared to expected load • Multiple generation scenario options are possible • Base case • High RE case • Very high RE case
Generation/Transmission scenarios Economic factors
Load growth
• • •
Medium load growth High load growth Low load growth
• • •
High fossil fuel cost Low VRE cost Low gas price
Technological/policy factors • • •
Battery technology, Aggressive cross-border power trade Nuclear energy
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Key inputs and expected outcomes of master plan development
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• Step 1: Long term generation plan will be developed based on load demand projections and availability of resources. • Step 2: DC Load flow optimization technique used to optimize generation costs and transmission upgrades. • Step 3: AC Load flow based reliability analysis to refine and update preliminary transmission master plan • Step 4: Expected cost advantage of given generation and transmission development scenario is calculated
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Projected Load growth
•
25.0
Demad (MW)
20.0 15.0 10.0 5.0 0.0 20162018202020222024202620282030203220342036
Uncertainties in projected load growth over the planning period are accounted for in a study • Low expected growth • Medium • High
Year
7
• Load Blocks Load Curves 120.00
Block 4
Block 3
Block 2
Block 1
Block 6
Block 5
Block 7
Normalized Load (%)
100.00 80.00 60.00 40.00 20.00 0.00
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Hour Mya nma r
Block Hours
1 (1-6)
La os
2 (7-9)
Cambodi a
Vi etnam
Thai l a nd
3 4 5 6 7 (10-13) (14-16) (17-18) (19-21) (22-24)
• 7 Load blocks are selected to capture load curve characteristics of each country & availability of renewables (day/night) 8
25
Significance of representing transmission network with sufficient details is demonstrated using an simple example. • Network C is represented using a single node (simplified) and three nodes (detailed). Simplified Representation
High Level Representation
Thermal Generation
Hydro Generation
G = 50 MW (100)
H G = 100 MW (100) A
Hydro Generation
T
H
B 10 0
(1 50 )
M W
C
MW 0 ) 5 50 (1
A
G = 75 MW (100) 75 M (15 0)
Note: All branch impedances are assumed to be equal. (green- transmission and generation capacity)
G = 75 MW (100) C
W
(5 0)
(50) M W
50
T
MW 75 0) (15
0 MW 50
25 MW
150 MW
Thermal Generation
W M
0) (5
B
25 MW
100 MW Note how transmission constrains can impact the dispatching of cheaper (hydro) generation
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Economic benefit analysis Sensitivity of total cost for transmission development Cost Maximum benefit
Total cost
Transmission investment cost Operation cost of generation
A
B
A. Operation without any new transmission additions B. Operation with refined transmission plan with maximum economic benefit C. Operation with initial transmission plan with all the lines (≈ Operating cost without any transmission thermal constraints applied)
C Number of transmission10 lines
Study Updates: Sensitivity analysis for the selected scenarios: Once the study results are available, sensitivity cases can be easily considered • • • •
Cost of coal Cost of RE Cost of energy storage (battery will expand the duration of Solar availability in a day) Transmission development delays
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Study Updates: What if scenarios: Example from a recent study by MHI
• •
Hydro generation in dry season is improved with the increased capacity of reservoir type hydro plants Hydro generation in wet season is reduced due to the power import restrictions 12
Engineering studies to further validate the development plan •
PSSE based steady state load flow studies (at initial planning stage) o N-1 o N-2
•
PSSE based dynamic stability studies (at initial planning stage) o Data accuracy and availability (can be easily addressed with good engineering practice)
•
Detailed electromagnetic transient studies (PSCAD based) o May perform very preliminary studies if plans involve very high RE penetration o Generally performed closer to project implementations
System Stability Studies - Example
- The event occurred during a time when the system load was unusually low (800 MW) - A coal Generation unit delivering approximately 280 MW (33%) and absorbing 28 MVAr tripped due to a protection malfunction. - The major load centre is around the capital city.
System Stability Studies Voltage comparisions:220 kV Biyagama220
VOLT 2570 [BIYAG-2 220.00]
NewChilaw 220
VOLT 2815 [NCHILAW-2 220.00]
•System Voltage: Recorded (Blue) and Simulation (Green).
1.250 1.200 V (pu)
1.150 1.100 1.050 1.000 0.950 1.250 1.200
V(pu)
1.150
•The simulation model does not capture the event accurately.
1.100 1.050 1.000 0.950 1.250
Lakvijaya220
VOLT 2810 [PUTTALAM-PS 220.00]
Kothmale220
VOLT 2220 [KOTMA-2 220.00]
1.200
V (pu)
1.150 1.100
•Model predicts excellent voltage control:
1.050 1.000 0.950 1.250 1.200
-
V (pu)
1.150 1.100 1.050 1.000 0.950 Kelanitissa220
VOLT 2300 [KELAN-2 220.00]
-
1.250 1.200 V (pu)
1.150 1.100 1.050 1.000 0.950 Time(s)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
... ... ...
Are tap changer actions adequately modeled ? Are the remaining generators providing the expected voltage support?
System Stability Studies
Voltage comparisions:220 kV Biyagama220
VOLT 2570 [BIYAG-2 220.00]
New Chilaw220
VOLT 2815 [NCHILAW-2 220.00]
•Model adjustments:
1.250 1.200
V (pu)
1.150 1.100 1.050 1.000
-
0.950 1.250 1.200
V(pu)
1.150 1.100
-
1.050 1.000 0.950 1.250
Lakvijaya220
VOLT 2810 [PUTTALAM-PS 220.00]
Kothmale220
VOLT 2220 [KOTMA-2 220.00]
Kelanitissa220
VOLT 2300 [KELAN-2 220.00]
1.200
V (pu)
1.150 1.100 1.050 1.000 0.950 1.250 1.200
V (pu)
1.150 1.100 1.050 1.000 0.950 1.250 1.200
V (pu)
1.150 1.100 1.050 1.000 0.950 Time(s)
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
... ... ...
Include Tap changer actions adequately in the system model Some of the key generators were not on ‘voltage control’ mode at the time of event.
Detailed PSCAD (emt) Studies – not generally required at planning stages
1.4
V MA GF_G
• •
1.2 1.0 0.8 0.6 0.4 0.2 2.0
ID_G
IQ_G
1.5 1.0 0.5
•
0.0 -0.5 -1.0 -1.5 4.0
PMW F_G
QMV ArF_G
3.0
•
2.0 1.0 0.0 -1.0 -2.0 -3.0 sec
14.90
15.00
15.10
15.20
15.30
15.40
15.50
•
Fault is applied at 15s for 120ms First 10ms duration fault: large rotation in Vd and Vq frame leads to high Iq injection and Low Id injection Next 50ms, inverter bring down Id and Iq to allow the PLL to relock to the phase. Last 60ms during the fault: inject Iq to support the system After fault release, PLL goes unstable and causes large voltage fluctuation