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TECHNICAL SHORTFALLS FOR PAN-EUROPEAN POWER SYSTEM
WITH HIGH LEVELS OF RENEWABLE GENERATION
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 773505.
1
TASK 2.4
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Why?
What?
How?
Outcomes
So what?
INTRODUCTION
METHODOLOGY
CONCLUSIONS
AGENDA
RESULTS
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INTRODUCTION
3
8 Minutes
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“Perform detailed technical analysis to assess the potential existence of the technical scarcities in a 2030 power system
with high levels of renewables.”
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System congestion System restoration
Dynamic voltage control Rotor angle stability
Frequency stability & control Steady state voltage control
Ireland & Northern Ireland Power System
Continental European System
Nordic Power System
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METHODOLOGY
7
4 Minutes
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Scenarios (Future system configuration)
Snapshots for analysis
Models
Analysis
Stimuli
Conclusions Evaluation on
indices
Lim
itatio
ns
Every nth hour Specific conditions Every hour
SYSTEM
CONSIDERED CORE SCENARIOS NETWORK SENSITIVITIES
Nordic system Energy
Transition
Renewable
Ambition
High
Solar -
Poland and
neighbours
Energy
Transition
Renewable
Ambition
Going
Green
Distributed
Renewables
Ireland and
Northern
Ireland
- Steady
Evolution
Low Carbon
Living
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RESULTS
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Nordic System Ireland &
Northern Ireland Continental
Europe 10
Frequency stability & control EDF VTT
Steady state voltage control PSEi EirGrid & SONI
Dynamic voltage control PSEi EirGrid & SONI
Rotor angle stability PSEi EirGrid & SONI
System congestion NCNR EirGrid & SONI
System restoration EirGrid & SONI
Steady state voltage control PSEi
Dynamic voltage control PSEi
Rotor angle stability PSEi
System congestion NCNR
System restoration
EirGrid & SONI
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Frequency Stability & Control
Continental Europe
Frequency stability & control EDF
EDF
5 Minutes
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Scenarios Stimuli & analysis method Study type
1. Energy Transition (ET) 2. Renewable Ambition (RA)
Time domain simulation • Interconnected incidents:
loss of 2 GW of generation in each zone
• 3 system split configurations
Every hour across the year
aFRR sizing Every hour across the year
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Interconnected incidents: loss of 2 GW of generation in each zone*
Zone
Energy Transition Renewable Ambition
NADIR < 49 Hz
ROCOF > 1 Hz /s
NADIR < 49 Hz
ROCOF > 1 Hz /s
PL + CZ + SK + HU 0% 0% 0% 0%
ES + PT 0% < 1% 0% ~ 9%
IT 0% 0% 0% 0%
FR 0% 0% 0% 0%
DE + neighbours 0% 0% 0% 0%
ROCOF analysis:
- Maximal ROCOF values in the Iberian Peninsula: 1.3 Hz/s.
- ROCOF values are highly correlated with very high share of VRES (up to 90%
of the instantaneous Iberian generation).
*The loss of 3 GW of generation was also simulated in
France, with similar results.
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3 system split configurations Iberian peninsula Italy Europe in 3
Splitting event
Energy Transition Renewable Ambition
NADIR < 47.5 Hz
ZENITH > 51.5 Hz
ROCOF > 1 Hz /s
NADIR < 47.5 Hz
ZENITH > 51.5 Hz
ROCOF > 1 Hz /s
Iberian Peninsula 0% 0% ~ 38% < 1% ~ 15% ~ 85 %
Italy < 1% < 1% ~ 58% < 1% ~ 2% ~ 49%
Europe in 3 0% 0% ~ 1% 0% 0% ~ 26%
Hypothesis: the power imbalances after the split are equal to the border power flows before the split (including HVDC links)
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3 system split configurations
Zoom on the Iberian peninsula split
Imbalances up to +/- 40% of load for the worst hours
ROCOF > 2 Hz/s in most cases
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3 system split configurations
Zoom on the Iberian peninsula split
Many nadir values < 49 Hz load shedding is activated Several nadir values < 47,5 Hz risk of blackout
Zenith values up to 53 Hz LFSM-O is not sufficient
More details in 2020 CIGRE paper C4-658, ”Assessment of the dynamic frequency stability of the future Continental Europe power system – Interconnected incidents and system splits”
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aFRR sizing
For a given level of risk taken by the TSO, the average and extreme aFRR needs will increase with the penetration of VRES.
aFRR duration curves, Renewable Ambition scenario, risk level = 1%
More details in 2019 Wind Integration Workshop paper, ”Probabilistic estimation of the aFRR requirement in the future European power system with high RES penetration”
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Key outcomes
Interconnected incidents
• For all zones of the Continental system, frequency nadir values for interconnected incidents seem to be manageable, as they stay above the first load-shedding threshold
• ROCOF values are more problematic, as they can reach 1,3 Hz/s and very few systems can currently run with such high levels of ROCOF
System splits
• Classical frequency control mechanisms are not sufficient for dealing with such events
• Even load shedding and LFSM-O, as modelled in the study, are not always sufficient to avoid black out situations
aFRR requirements
• The transition to higher penetrations of variable renewables results in a higher requirement for aFRR, and the annual variability requirement also increases
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Frequency Stability & Control
Ireland & Northern Ireland
Continental Europe
Frequency stability & control EDF EirGrid & SONI
EirGrid & SONI
4 Minutes
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Scenarios Stimuli & analysis method Study type
1. Low carbon living (LCL) 2. Steady evolution (SE)
• Economic dispatch analysis Every hour across the year
• Time domain simulation - Loss of infeed - Loss of outfeed/export
Every 7th hour across the year
• Inertia scarcity index: Evaluated through least cost dispatching, RoCoF used as index
• Reserve adequacy index: For both speed and magnitude of reserve provision, evaluation through time domain simulations, frequency nadirs and zeniths as index
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0
1
2
3
4
5
6
0 1000 2000 3000 4000 5000 6000 7000 8000
Ro
Co
F (
Hz/s
)
2030 LCL MARUN 2030 LCL EOC
21
• Multiple models for each scenario: Market run (MARUN), enhanced operation (EOC) • Inertia scarcity demonstrated: Excessive RoCoF indicates lack of inertia
• RoCoF constrained dispatches used: The scarcity is mitigated beforehand to enable time domain simulations
With RoCoF Constraint
Without RoCoF Constraint
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• For LCL scenario: No significant scarcity – only 0.6% cases below 49 Hz, Mean = 49.52 Hz • Improvement in nadirs: Generally higher SNSP , improving frequency nadirs
• Underlying factors: 1) Increasing renewable reduces LSI, 2) Fast dynamic reserve
• Important assumptions: Current FFR product modelled, significant quantity of fast dynamic reserve
• SE scenarios: Lower RES, less interconnection and smaller fast reserve magnitudes • For SE scenario: Worse – 4% cases below 49 Hz, Mean = 49.42 Hz
• Underlying factors: Smaller fast reserve levels
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• Inertia scarcity found and mitigated before time domain simulations
• Higher renewable scenario characterised by higher interconnection and higher fast dynamic reserves shows better under-frequency performance
• Fast dynamic reserves are critical for system stability, a fast reserve product helps enormously – current FFR product included in simulations
• Abundant fast reserve resources can mask the gaps in scheduling practices occurring due to changing reserve portfolio and system conditions
• Need for revision of scheduling practices, catering for changes in reserve portfolio identified.
Key outcomes
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Nordic System Ireland &
Northern Ireland Continental
Europe
Frequency stability & control EDF EirGrid & SONI VTT
Frequency Stability & Control
VTT 4 Minutes
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Scenarios Stimuli & analysis method Study type
1. Energy Transition (Sysflex core scenario)
2. High solar (Nordic sensitivity)
3. Renewable Ambition (Sysflex core scenario)
Time domain simulation • Interconnected incidents: loss
of generation equal to the dimensioning incident
Every hour across the year
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Nordic analysis: Introduction
26
Power system
model
(Simulink)
Frequency
nadir
Frequency
rate of
change
Dimensioning
incident
Dispatch model
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Frequency nadir
27
Energy Transition High Solar Renewable Ambition
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Rate of change of frequency
28
Energy Transition High Solar Renewable Ambition
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Effect of fast frequency reserve
• Addition of 200 MW FFR produces a small increase in frequency nadir
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Nordic System Ireland &
Northern Ireland Continental
Europe 30
Frequency stability & control EDF EirGrid & SONI VTT
Steady state voltage control PSEi EirGrid & SONI
Dynamic voltage control PSEi EirGrid & SONI
Rotor angle stability PSEi EirGrid & SONI
System congestion NCNR EirGrid & SONI
System restoration EirGrid & SONI
Steady state voltage control PSEi
Dynamic voltage control PSEi
Rotor angle stability PSEi
System congestion NCNR
System restoration
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Steady State Voltage Control
Continental Europe
Steady State Voltage Control PSEi
PSEi
6 Minutes
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Scenarios Stimuli & analysis method
Study type
1. Energy Transition (ET)
2. Going Green (GG)
3. Distributed Renewables (DR)
• Load flow analysis - intact system - N-1 conditions
Selected snapshots
• Short circuit analysis - intact system - n-1 conditions
Selected snapshots
• P-V Analysis - intact system - n-1 conditions
Selected snapshots
• Q-V Analysis - intact system - n-1 conditions
Selected snapshots
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Capacity scenarios for CE (Going Green)
+ more
RES in PL
=
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Capacity scenarios for CE (Distributed Renewables)
+ some RES in
PL are moved to the radial
DS
=
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Operation snapshots for CE
+ = Maximum load snapped (/4)
Maximum load snapped (/3) Maximum load snapped (/2)
Maximum load snapped (/1)
Capacity scenario
Worst cases under study: • Maximum Load
• Minimum Inertia • Minimum Reactive
power margins for the Synchronous Generation
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Contingencies and disturbances
Very detailed model representing EHV and 110 kV power
grid Simplified model representing EHV power grid
Equivalent models
Contingencies and disturbances
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Steady-state voltage deviation analysis
• All network contingencies have been assumed in Polish power system owing to the detailed representation of power grid used for Poland.
• Analysis has been focused on 110 kV network in Poland, especially the nodes to which passive and active radial distribution systems are connected.
• Problems of low voltage levels occur particularly in the Maximum Load operational snapshots (with relatively low SNSP).
• The highest number of 110 kV nodes for which the voltage is below 0.9 p.u. are observed for the Going Green capacity scenario.
• The impact of reduced voltage regulation due to higher RES generation becomes apparent at high load conditions.
0
10
20
30
40
50
60
70
0
20
40
6080
100
120
140
160
ET/M
ax_L
oad/
1
ET/M
ax_L
oad/
2/3/
4
ET/M
in_I
ner
tia/
1
ET
/Min
_In
ert
ia/2
/3
ET/M
in_I
ner
tia/
4
ET/M
in_R
eact
ive/
1/2
ET/M
in_R
eact
ive/
3/4
GG
/Ma
x_Lo
ad
/1
GG
/Ma
x_Lo
ad
/2/3
/4
GG
/Min
_In
ert
ia/1
GG
/Min
_Ine
rtia
/2/3
GG
/Min
_In
ert
ia/4
GG
/Min
_R
eac
tiv
e/1
/2
GG
/Min
_R
eac
tiv
e/3
/4
DR
/Max
_Loa
d/1
DR
/Max
_Loa
d/2
/3/4
DR
/Min
_In
ert
ia/1
DR
/Min
_Ine
rtia
/2/3
DR
/Min
_In
ert
ia/4
DR
/Min
_Rea
ctiv
e/1/
2
DR
/Min
_Rea
ctiv
e/3/
4
SN
SP
(%)
Num
ber
of 1
10 k
V n
odes
Number of 110 kV nodes for which V < 0,90 (N-1) SNSP
0
10
20
30
40
50
60
70
0,75
0,8
0,85
0,9
0,95
1
ET/M
ax_L
oad/
1
ET/M
ax_L
oad/
2/3/
4
ET/M
in_I
nert
ia/1
ET
/Min
_In
ert
ia/2
/3
ET/M
in_I
ner
tia/
4
ET/M
in_R
eact
ive/
1/2
ET/M
in_R
eact
ive/
3/4
GG
/Ma
x_Lo
ad
/1
GG
/Ma
x_Lo
ad
/2/3
/4
GG
/Min
_In
ert
ia/1
GG
/Min
_Ine
rtia
/2/3
GG
/Min
_In
ert
ia/4
GG
/Min
_R
eac
tiv
e/1
/2
GG
/Min
_R
eac
tiv
e/3
/4
DR
/Max
_Loa
d/1
DR
/Max
_Loa
d/2/
3/4
DR
/Min
_In
ert
ia/1
DR
/Min
_Ine
rtia
/2/3
DR
/Min
_In
ert
ia/4
DR
/Min
_Rea
ctiv
e/1
/2
DR
/Min
_Rea
ctiv
e/3/
4
SNSP
(%)
Vo
lta
ge
(p
.u.)
Min. voltage [p.u] of 110 kV node (N-1) SNSP
FIGURE : SNSP AND NUMBER OF 110 KV NODES FOR WHICH V < 0.90 P.U. (N-1)
FIGURE: SNSP AND MIN. VOLTAGE [P.U.] OF 110 KV NODES (N-1)
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Steady-state voltage deviation analysis
• Minimum Inertia and Minimum Reactive snapshots show increased over-voltage deviations, although this issue is observed across all snapshots and scenarios.
• The highest numbers of nodes with over-voltage issues correspond to the Going Green scenario.
• The highest values of over-voltage at 110 kV nodes are observed in the Distributed Renewables scenario.
• The key factor affecting steady-state voltage issues is the power demand.
• Due to the fact that Minimum Inertia and Minimum Reactive snapshots are much closer to the minimum load time, more over-voltage problems can be observed.
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ctiv
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/3
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/Min
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ert
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/Min
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ctiv
e/1/
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/Min
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ctiv
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/Ma
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/1
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SN
SP
(%)
Num
ber
of 1
10 k
V n
odes
Number of 110 kV nodes for which V > 1,1 (N-1) SNSP
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1,11,111,121,131,141,151,161,171,181,19
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ctiv
e/3
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SN
SP
(%)
Vo
lta
ge
(p
.u.)
Max. voltage [p.u] of 110 kV node (N-1) SNSP
FIGURE: SNSP AND NUMBER OF 110 KV NODES FOR WHICH V > 1.1 P.U. (N-1)
FIGURE: SNSP AND MAX. VOLTAGE [P.U.] OF 110 KV NODES (N-1).
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39
Steady-state voltage deviation analysis
• Higher RES level causes not only changes in the number and magnitude of voltage deviations but also shifts the problem from one location to another.
• When RES generation increases, the voltage problems are shifted from Central and South-West to the North-East and the North-West parts of the Polish power system in the Going Green and Distributed Renewables scenarios, respectively.
• It has been also observed that increasing RES impacts upon the magnitude of voltage values without causing significant changes in spatial distribution for the Distributed Renewables capacity scenario.
higher 𝑆𝑁𝑆𝑃
higher 𝑆𝑁𝑆𝑃
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40
Voltage Stability analysis
• The Voltage stability margins in Polish part of CE power system have been assessed with the use of the Power-Voltage (P-V) Curve method.
• The voltage is a function of active power in this area from operational point up to the loss of load flow convergence.
• Voltage stability margins within Polish Power System have been calculated for all investigated scenarios and operational cases, including (N-0) and (N-1) states.
• Relatively high correlations between voltage stability margin and the load level occur in the Energy Transition and Going Green scenarios.
• A secondary factor having impact to increasing the voltage stability margin is the renewables generation which change the load in power network elements.
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SNSP
(%)
Vol
tage
sta
bilit
y m
argi
n (%
)
Stab. margin (N-0) Stab. margin (N-1) SNSP
FIGURE: SNSP AND VOLTAGE STABILITY MARGINS CALCULATED FOR POLISH POWER SYSTEM
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41
Voltage Stability analysis
• In order to obtain the P-V Curves, the load was increasing in particular ODMs individually.
• For (N-1) states there are two cases in which divergence of the load flow has been obtained.
• Districts having remote generation (both conventional and renewable) are characterised by lower voltage stability margins.
FIGURE: APPROXIMATE LOCATION OF DISTRICTS OF POLISH REGIONAL TSO’S CONTROL CENTRES.
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101520253035404550
SN
SP
(%)
VO
LTA
GE
STA
BIL
ITY
MA
RG
IN (%
)
Stab. margin (ODM 1) Stab. margin (ODM 2) Stab. margin (ODM 3)
Stab. margin (ODM 4) Stab. margin (ODM 5) SNSP
FIGURE: SNSP AND VOLTAGE STABILITY MARGINS CALCULATED FOR DISTRICTS OF POLISH REGIONAL TSO’S CONTROL CENTRES (N-1).
ODM 1
ODM 2ODM 3
ODM 4
ODM 5
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42
Voltage Stability analysis
• Q-V curves present the relationship between the reactive power injected into a power network node and the nodal voltage level.
• For all scenarios and operational cases, the weakest 110 kV nodes have been identified within all the critical zones and selected for the Q-V curve analysis.
• (N-1) contingency states for various snapshots have been analysed for the purpose of Q-V curve calculation.
• In general, the scenarios characterized by high RES capacity entail a higher risk of nodal voltage in-stability. FIGURE: Q-V CURVES FOR ONE OF THE ANALYSED 110 KV NODES.
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43
Steady-state voltage control– Key outcomes
• EHV system in Poland remains relatively un-effected by increasing RES levels across the Continental European System.
• However, the 110 kV Polish system exhibits a lack of steady state reactive power capacity, as demonstrated by deteriorating steady state voltage regulation.
• The reactive power scarcity becomes most apparent at high load and minimum inertia conditions.
• P-V analysis across various zones of the Polish system demonstrates that within the subnetworks of the Polish system, regions with higher magnitude of installed renewable capacity, shows a trend towards diminishing stability margins.
• Q-V analysis on the Polish system demonstrates that the scenarios characterised by high RES capacity exhibit a higher risk of potential nodal voltage instability.
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44
Steady State Voltage Control
Ireland & Northern Ireland
Continental Europe
Steady State Voltage Control PSEi EirGrid & SONI
EirGrid & SONI
6 Minutes
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45
Scenarios Stimuli & analysis method Study type
1. Low carbon living (LCL)
2. Steady evolution (SE)
• Load flow analysis - intact system - n-1 conditions
Every hour across the year
• Short circuit analysis - intact system - n-1 conditions
Every hour across the year
• QV Analysis - intact system - n-1 conditions
Every hour across the year
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46
Steady State Voltage Control Steady state voltage deviations
• Evaluation index: Steady state voltage deviations for steady state reactive power scarcity
• Increase in renewable generation causing higher deviations • Trend observed due to reduction in reactive capacity due to displaced conventional gen.
• Higher renewables scenario, amplifies the deficiency in steady state reactive power
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47
Steady State Voltage Control QV analysis
• Evaluation index: MVARs required to attain a pre-define voltage
• Trend: MVAR requirement increases with SNSP – general lack of MVARs
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48
Steady State Voltage Control Short circuit analysis
• Evaluation index: Short circuit power or MVA level is used as index • Results presented for a strong & a week bus
Week bus trend: Initial increase in fault level, followed by sharp decline Strong bus trend: Not as clear due to frequent generation dispatch
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49
• The results of voltage deviation analysis are supported by QV analysis
• Clear trend of increasing renewables causing reduced steady state reactive capacity – scarcity has been identified
• System short circuit levels are significantly reduced at high renewable generation levels, implications for protection & stability
• Weaker & renewable energy dominant parts of the network need consideration, this can be done in a number of ways, possibly using a reactive power product
Key outcomes
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50
Nordic System Ireland &
Northern Ireland Continental
Europe 50
Frequency stability & control EDF EirGrid & SONI VTT
Steady state voltage control PSEi EirGrid & SONI
Dynamic voltage control PSEi EirGrid & SONI
Rotor angle stability PSEi EirGrid & SONI
System congestion NCNR EirGrid & SONI
System restoration EirGrid & SONI
Steady state voltage control PSEi
Dynamic voltage control PSEi
Rotor angle stability PSEi
System congestion NCNR
System restoration
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51
Dynamic Voltage Control
Continental Europe
Dynamic Voltage Control PSEi
PSEi
5 Minutes
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52
Scenarios Stimuli & analysis method
Study type
1. Energy Transition (ET)
2. Going Green (GG)
3. Distributed Renewables (DR)
• Time domain simulations - Short circuit faults
Selected snapshots
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53
Fault Ride-Through (FRT) analysis
• The obtained voltage waveforms have been compared with the Low Voltage Fault Ride-Through (LVRT) profiles required by the RfG network code.
• For the purposes of analysis following sets of disturbances have been assumed:
• 150 ms self-clearing close 3-phase short circuit in transmission lines leading out of a power plant station, as regards SGMs.
• 150 ms self-clearing 3 phase short circuit at the point of common connection (PCC), as regards PPMs.
• A set of the largest PPMs within the whole Polish power system and selected two critical zones regarding steady-state voltage stability, have been selected for the test simulations.
FIGURE: FRT RESPONSES FOR SGMS (SELECTED EHV BUSBAR OF KOZIENICE POWER PLANT STATION, 150 MS SELF-CLEARING 3 PHASE SHORT CIRCUIT).
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54
Fault Ride-Through (FRT) analysis
• In order to assess how outages may influence the LVRT capability of non-synchronous generators, critical contingencies identified in the voltage control analyses, also have been applied to the pre-fault power system operation state.
• All the analysed D-type wind farms and active distribution systems (B and C-type PPM generation included) have the FRT capability implemented in their control systems.
• For PPMs there have been no significant impact observed of different operational cases (resulting in different SNSP) to FRT responses.
FIGURE: FRT RESPONSES FOR PPM (SELECTED PCC OF D-TYPE PPM, GOING GREEN SCENARIO).
FIGURE: FRT RESPONSES FOR PPM (SELECTED PCC OF C-TYPE PPM, DISTRIBUTED RENEWABLES SCENARIO).
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55
Dynamic Voltage Control– Key outcomes
Fault Ride Through analysis:
• As a result of the analysis, no LVRT requirement violations have been observed in the transient simulations.
• The FRT response curves for SGMs and PPMs within Maximum Load operational snapshots tend to have less oscillation than for Minimum Inertia and Minimum Reactive ones.
• Following differences between FRT plots representing Maximum Load and other operational snapshots can be explained by greater power system stiffness, related to lower 𝑆𝑁𝑆𝑃 level values.
• A clear indication of a lack of dynamic reactive injection capacity in the Polish system as a subset of the Continental European system is not apparent.
• An absence of dynamic reactive power scarcity for Continental European system at higher renewable energy levels cannot be concluded.
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56
Dynamic Voltage Control
Ireland & Northern Ireland
Continental Europe
Dynamic Voltage Control PSEi EirGrid & SONI
EirGrid & SONI 5 Minutes
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Scenarios Stimuli & analysis method Study type
1. Low carbon living (LCL)
2. Steady evolution (SE)
• Time domain simulations - Short circuit faults,
cleared by line tripping
Selected snapshots
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Case Selection
58
Which of the 8760 hours from each scenario to focus upon?
Split 8760 based on: • SNSP • Inertia • Large gen.
near load centres
TYPE 1
TYPE 2
Each of the 8 types is high or low in terms of these three measures
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How does the scarcity manifest?
59
Larger voltage drops that propagate further after any contingency on the system (e.g. line faults)
None
Localised
Global
Can be localised in terms of: • contingencies, or • conditions
Can be specific or systematic
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Illustrative voltage traces for a fault
Measuring the scarcity…
60
Bus 1:
1 unique violation
No delayed recovery
Bus 3:
1 unique violation
Delayed recovery
1. Unique Violations
2. Early Recovery
How far did the fault ‘spread’
Understand VAr s provided during fault
0.5 p.u. threshold applied
Bus 2:
1 unique violation
Delayed recovery
Bus 4:
No unique violation
No delayed recovery
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Unique Violations – LCL
61 Network model has ~1300 buses
SNSP < 10%
SNSP >80%
SNSP from 20% t0 80%
Global scarcity Localised scarcity
Minimal Scarcity
Box plot of unique violations for 306 contingencies for each snapshot
SNSP doesn’t tell the whole story
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Early Recovery – LCL
62
Box plot of early recovery (% )for 306 contingencies for each snapshot
More early recovery as SNSP increases
SNSP < 10%
SNSP >80%
SNSP from 20% t0 80%
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What this looks like…
Same contingency for a Type 1 and Type 2 Hour 63
A more volatile voltage profile
Exhibiting fast recovery from a wide ranging initial dip
Would system really survive these swings?
How long a delay can be tolerated?
Type 2 recovers to similar voltage as
Type 1 on-fault
Type 1 Type 2
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What this means…
64
Conclusions are valid, but large voltage swings call into question the security of the system
Are modelling limitations masking mass converter trips?
What is the winder system impact of delayed recovery?
How long a delay can be tolerated?
A global scarcity of dynamic voltage control is emerging
Widespread localised issues for contingencies and hours of operation
Scarcity is driven by the location of synchronous machines
Is a detailed issue and while low SNSP leads to more areas with no synch. Gen., attempts to analyse/manage through lens of SNSP may fail
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Nordic System Ireland &
Northern Ireland Continental
Europe 65
Frequency stability & control EDF EirGrid & SONI VTT
Steady state voltage control PSEi EirGrid & SONI
Dynamic voltage control PSEi EirGrid & SONI
Rotor angle stability PSEi EirGrid & SONI
System congestion NCNR EirGrid & SONI
System restoration EirGrid & SONI
Steady state voltage control PSEi
Dynamic voltage control PSEi
Rotor angle stability PSEi
System congestion NCNR
System restoration
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66
Rotor Angle Stability
Continental Europe
Rotor Angle Stability PSEi
PSEi 5 Minutes
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67
Scenarios Stimuli & analysis method
Study type
1. Energy Transition (ET)
2. Going Green (GG)
3. Distributed Renewables (DR)
• Time domain simulations
- Short circuit faults Selected snapshots
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68
Critical Clearing Time analysis
FIGURE: C|K3|1C CLOSE 3 PHASE SHORT CIRCUIT ELIMINATED BY LINE
TRIPPING AT NORMAL CLEARING TIME 𝒕𝐈 = 𝟏𝟎𝟎 𝐦𝐬.
FIGURE: C|K3|2C CLOSE 3-PHASE SHORT-CIRCUIT IN A DOUBLE-CIRCUIT LINE
ELIMINATED BY LINE TRIPPING AT NORMAL CLEARING TIME 𝒕𝐈 = 𝟏𝟎𝟎 𝐦𝐬
FIGURE: F|K3|1C FAR 3 PHASE SHORT CIRCUIT ELIMINATED BY LINE TRIPPING AT
IMPEDANCE RELAY II ZONE (85% LINE LENGTH) CLEARING TIME 𝒕𝐈+ = 𝟏𝟐𝟎 𝐦𝐬 FROM
THE POWER STATION SIDE OF LINE AND NORMAL CLEARING TIME 𝒕𝐈 = 𝟏𝟎𝟎 𝐦𝐬 FROM
THE OTHER END OF LINE SIDE.
FIGURE: C|K3|B PHASE SHORT-CIRCUIT IN A BUSBAR SYSTEM ELIMINATED AT
NORMAL CLEARING TIME 𝒕𝐈 = 𝟏𝟎𝟎 𝐦𝐬.
𝑘t =𝑡cr − 𝑡I
𝑡I⋅ 100%
𝑘t =𝑡cr − 𝑡I
𝑡I⋅ 100%
𝑘t =𝑡cr − 𝑡I
𝑡I⋅ 100%
𝑘t =𝑡cr − 𝑡I+
𝑡I+⋅ 100%
• Critical clearing times 𝑡cr, described as the longest clearing times for which a power system will remain in synchronism, have been calculated using a binary search method:
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69
Critical Clearing Time analysis
• The selected disturbances have been applied on the transmission lines and busbars in the EHV substations transferring power from the biggest conventional Polish power plants.
• Transient stability analysis covers 9 operation snapshots for each of the 163 considered fault event contingencies.
• For each of the analyzed scenarios, median values for the CCTs tend to be the highest for the Maximum Load operational snapshots.
• The larger the active power demand is, the larger the number of synchronous generators operating, which leads to the increase of the inertia level in the power system.
FIGURE: C|K3|1C CRITICAL CLEARING TIME RESULTS – BOX PLOTS.
FIGURE: C|K3|2C CRITICAL CLEARING TIME RESULTS – BOX PLOTS.
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70
Critical Clearing Time analysis
• Generally, Minimum Reactive and Minimum Inertia operational cases simulation results tend to be comparable, but lower than corresponding values for the Maximum Load.
• The lower the reactive power generation is, the lower the voltages of generators are, which causes the decrease of transient stability margin.
• The overall power systems’ inertia is being reduced for the Minimum Inertia, and Minimum Reactive operational cases, due to the higher renewables penetration.
FIGURE: F|K3|1C CRITICAL CLEARING TIME RESULTS – BOX PLOTS.
FIGURE: C|K3|B CRITICAL CLEARING TIME RESULTS – BOX PLOTS.
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71
Oscillation damping analysis
• For the purposes of oscillatory stability analysis, settling and halving times have been calculated in order to assess the damping of inter-area and inter-plant oscillations.
• Settling and halving times have been calculated for close 3-phase short circuit disturbances in which clearing times are assumed to be 100 ms.
• High penetration of renewables and decrease of the synchronous generation cause significant issues with an oscillation damping.
• For each of the analysed capacity scenarios, both halving and settling time median values tend to be lowest for the Maximum Loads operational snapshots, due to low SNSP level.
FIGURE: HALVING AND SETTLING TIMES DEFINITION.
FIGURE: HALVING TIMES– BOX PLOTS.
FIGURE: SETTLING TIMES– BOX PLOTS.
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72
Oscillation damping analysis
• The overall power systems’ inertia is being reduced for the Minimum Inertia and Minimum Reactive scenarios, due to the higher renewables penetration, instead of synchronous generation.
• The lower the reactive power generation is, the lower the voltage of generators connected at the power plant are, which causes reduced oscillation damping.
• In the first two seconds of the simulation inter-plant oscillation components are more noticeable (approximately 1,42 Hz), then the nature of the oscillations turns to inter-area values (from 0,63 Hz for Maximum Load to 0,76 Hz for Minimum Inertia and Minimum Reactive).
• High penetration of synchronous generation due to the higher active power demand helps to better damp power systems oscillations.
FIGURE OSCILLATIONS DAMPING – ROTOR ANGLE PLOTS FOR VARIOUS OPERATION SNAPSHOTS.
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73
Rotor Angle Stability – Key outcomes
Critical Clearing Times analysis:
• The analysis of critical clearing time shows no emergence of a localised scarcity in stability margin when assessed in terms of the expected primary protection operation times. All the obtained critical clearing times met the grid requirements.
• There is also no evident trend in transient stability margins in the function of capacity scenario.
• Performed analysis has shown that the local conditions of synchronous generation (generator operation point, the nearest network topology and configuration, other synchronous units committed in the vicinity) determine the synchronous torque.
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74
Rotor Angle Stability – Key outcomes
Oscillation damping analysis:
• Oscillation damping presents a global scarcity with poor settling and halving times for all cases and scenarios.
• Time-domain simulations have identified the poor oscillation damping during severe system disturbances, such as three-phase short-circuit events, with only the Maximum Load cases having any significant number of acceptable settling and halving times.
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Rotor Angle Stability
Ireland & Northern Ireland
Continental Europe
Rotor Angle Stability PSEi EirGrid & SONI
EirGrid & SONI 5 Minutes
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76
Scenarios Stimuli & analysis method Study type
1. Low carbon living (LCL)
2. Steady evolution (SE)
• Time domain simulations - Sort circuit faults
Selected snapshots
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Case Selection
77
Which of the 8760 hours from each scenario to focus upon?
Split 8760 based on: • SNSP • Inertia • Large gen.
near load centres
TYPE 1
TYPE 2
Each of the 8 types is high or low in terms of these three measures
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How does the scarcity manifest?
78
Reduced synchronising and damping torque Loss of synchronism and larger oscillations
One generator or a small group oscillate or separate
Large groups oscillate or separate
None
Localised
Global
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Angle Margin
79
How often does angular instability occur?
Localised instability
SNSP < 10%
SNSP >80%
SNSP from 20% t0 80%
Measure spread of machine angles : η= ((360- δmax) / (360+δmax)) ×100
Stable when AM > 0
Unstable unit
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Critical Clearing Time
80
Do we clear faults fast enough?
The longest fault clearance time for which the system remains stable
Absolute worst case clear time is 25 cycles
Localised issue for backup protection
76% cases have CCT above 70 cycles
SNSP < 10%
SNSP >80%
SNSP from 20% t0 80%
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Decay Time Constant
81
Time required for oscillation magnitude to decay to 36.8% of initial value
Acceptable if < 7 seconds
Localised issue emerging
Issue volatile with SNSP…
SNSP < 10%
SNSP >80%
SNSP from 20% t0 80%
Do we have enough damping?
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What this means…
82
Further study required to
• Would protection pick up?
• Are generator models detailed enough to capture stresses placed upon then with only 4 units online?
• How to define a synchronising torque requirement
• Will certain units risk becoming undispatchable without support?
A localised scarcity of rotor angle stability is emerging
Systematic shortfall of synchronising and damping torque for certain units
Scarcity is driven by the location of synchronous machines
Certain machines or small groups to become isolated in weak parts of the network. More severe in steady evolution.
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83
Nordic System Ireland &
Northern Ireland Continental
Europe 83
Frequency stability & control EDF EirGrid & SONI VTT
Steady state voltage control PSEi EirGrid & SONI
Dynamic voltage control PSEi EirGrid & SONI
Rotor angle stability PSEi EirGrid & SONI
System congestion NCNR EirGrid & SONI
System restoration EirGrid & SONI
Steady state voltage control PSEi
Dynamic voltage control PSEi
Rotor angle stability PSEi
System congestion NCNR
System restoration
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System Congestion
Continental Europe
System Congestion NCNR
NCNR 5 Minutes
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85
Scenarios Stimuli & analysis method Study type
Distributed Renewables (DR) Energy transition (ET) Going Green (GG)
Load flow analysis (N-0) Decomposition of Load Flow (Power Flow Coloring)
21 timestamps (7 per a scenario) differenciated by load level, inertia and reactance
Background – Cross-border congestion management • Market allocated flows and real flows differ significantly
• This difference can increase due to higher integration of the renewables (uncertainty).
• The difference is called unscheduled flow
Do we need coordination of XB remedial actions for the future power system?
Coordinated remedial actions are the most efficient
Remedial actions (inter-TSO) are needed
Unscheduled flows can create congestions
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86
Import/Export Transit
Loop flow Scheduled Flow
UNSCHEDULED FLOW
Allocated Flows
UAF
(prepared by EDF)
Unscheduled Flow – interpretation and results
4
6 5
Unscheduled flow
Results (cross-border CEE)
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• The results show that the magnitude of unscheduled flows is scenario-dependant and can vary from 500 MW to 4000 MW
• For some borders, correlation of UF is visible. General direction of UF in the region is North to South.
• Power Flow Coloring is used for identification of unscheduled flows. The method is compliant with the ENTSO-E flow type definitions.
Unscheduled Flows – interpretation and results
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System Congestion
Ireland & Northern Ireland
Continental Europe
System Congestion NCNR EirGrid & SONI
EirGrid & SONI 3 Minutes
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Scenarios Stimuli & analysis method Study type
1. Low carbon living (LCL)
2. Steady evolution (SE)
• Load flow analysis - intact system - n-1 conditions
Every hour across the year
• Congestion context: The context of congestion is different to Continental system
• Congestion index: Thermal overloading metric
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I. Overloading increment with SNSP: Density as well as magnitude II. Summer vs Winter: Load decreases in summer, but so does the thermal rating III. Nominal congestion for above 220 kV network: Renewable location impact IV. Overload mechanism: Renewables feeding far away load centres, lack of local absorption V. Higher renewable scenario: Amplifies all the effects
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• Clear trend of increasing renewables causing increased congestion – global scarcity identified
• Congestion driven by a lack of transmission paths from renewables to load centres and an absence of local absorption
• Wind farm collector networks (110 kV here) need to be managed, this can be done in a number of ways, network upgrades and/or a congestion product among the options
Key outcomes
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CONCLUSIONS
96
7 Minutes
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97
RoCoF (dimensioning incident)
Localised concern Inertia Scarcity No Scarcity
RoCoF (System split)
Frequency containment (dimensioning incident)
Frequency containment (System split)
Steady State voltage Regulation
Fault level
Continental Europe Ireland & Northern
Ireland Nordic System
Global concern Not applicable
Evolving Characteristic Evolving Characteristic Evolving Characteristic
Global concern Not applicable
S.S reactive power Scarcity
S.S reactive power Scarcity
No Scarcity Dynamic reactive injection scarcity
Not analysed
Not analysed
Scarcity Concern Evolving Characteristic
• Various aspects of system stability in view of increasing renewable generation levels are analysed.
• Due to varying nature of systems under consideration, the inter-system comparison in terms of just the presence or absence of a scarcity does not tell the complete story.
• Therefore, the results for system stability aspects can be categorised into:
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Rotor angle margin Localised concern
System congestion
System restoration
Transmission Capacity Scarcity
Global concern
Evolving Characteristic Not analysed
Not analysed
Dynamic voltage regulation
Critical clearing times
Oscillation damping
No Scarcity Dynamic reactive injection scarcity
Evolving Characteristic Evolving Characteristic
Damping Scarcity Damping Scarcity
Not analysed
Continental Europe Ireland & Northern
Ireland Nordic System
• Ireland & Northern Ireland system is witnessing the renewable generation impacts, while the continental system generally appears to be evolving towards them
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• Multiple scarcities identified clearly for Ireland & Northern Ireland system
• For continental system, some scarcities and areas of concern have been identified. An evolution of system needs is apparent
• Lack of a clearly evident system scarcity, does not imply the absence of a scarcity altogether
• The manifestation of scarcities depends on the choice of focus area, snapshot selection, renewable energy levels and stimuli used
• Where identified the system scarcities can potentially be mitigated through system services, underpinned by a well considered regulatory and economic framework
• The studies relied on RMS models, the analysis was therefore limited to electromechanical transients & synchronous frequency ranges.
Conclusions
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100
Task
2.4
S
carc
ity
iden
tifi
cati
on
& a
nal
ysis
Work Package 3 Task 2.1 What scarcities to look for?
Task 2.2 Scenarios & sensitivities
Task 2.3 Models & analysis to be run
Work Package 10
Task 2.6
Inputs
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This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 773505.
Thank You!
Questions?
101