TSO Reliability Management: a probabilistic approach for better balance between reliability & costs

Generally Accepted Reliability Principle with Uncertainty
modelling and through probabilistic Risk assessment

GARPUR/ISGAN ACADEMY
Webinar 1
2
23 May 2017
Introduction:
Webinar outline,
GARPUR project and philosophy
Oddbjørn Gjerde
Coordinator
SINTEF Energi AS
1 2 3 54

3
1. Introduction to GARPUR project &
philosophy
2. GARPUR methodology for Reliability
Management Approach & Criteria
(RMAC)
3. Application of RMAC to real time
operation: case study at Landsnet
4. Conclusions
5. Questions
Outline of the webinar
Oddbjørn Gjerde
SINTEF Energi AS
Louis Wehenkel
Université de Liège
Samuel Perkin
LANDSNET
Louis Wehenkel
Université de Liège
1 2 3 54

Introduction
4
Network Code on Operational Security:
(N-1)-Criterion means the rule according to which elements remaining in
operation [ ] after a Contingency [ ] must be capable of accommodating the new
operational situation without violating Operational Security Limits
Present practice: N-1
 N-1 has been the cornerstone of TSO reliability
management
 with N-1 there is no need to quantify the
consequences since they are not accepted
 N-1 will stay one of the cornerstones of TSO
reliability management
But…
1 2 3 54

Introduction
5
N-1 limitations
 Does not consider probability of outages
 Does not distinguish situations that are
– Not N-1 secure (N-0, N-½ …) or,
– N-1 secure (but still many options)
 Difficult/impossible to handle the comprehensive uncertainties in a
large interconnected system
 Complexity of the pan-European system, increasing probability of
multiple outages
 Volatility caused by RES increasingly necessitates probabilistic
approaches
 Hard to handle new devices that enable fast corrective actions
1 2 3 54

Introduction
6
Purpose of GARPUR
Balancing reliability and costs:
Reducing socio economic costs and still maintaining reliability of supply.
Therefore GARPUR aims to:
 Design, develop, and assess new probabilistic reliability criteria
 Evaluate their practical use with more focus on social welfare effects
GARPUR covers the three time horizons:
1 2 3 54
Power system
operation
Asset
management
System
development

Introduction
7
GARPUR in a nutshell
1 2 3 54

Introduction
8
GARPUR ambitions
 Consistent, continuous and comprehensive framework &
tools to balance reliability and economics
 From system planning to operation
 Resulting in:
– More optimal
socio-economic impact
1 2 3 54

Introduction
9
More information
1 2 3 54
http://www.garpur-project.eu/

Webinar 1
10
23 May 2017
GARPUR Methodology
for probabilistic Reliability Management
Louis Wehenkel
GARPUR Scientific Advisor
University of Liège
1 2 3 54

11
 Weaknesses of the N-1 criterion
 GARPUR proposal in a nutshell
 Implementation in practice
GARPUR methodology for Probabilistic Reliability Management1 2 3 54
Outline

12
Outline

13
(e.g. in Real-Time operation)
 Contingencies explicitly covered:
– all N-1 events (+ possibly some common mode N-k events)
 Acceptable contingency response:
– simulated response within steady-state (and stability) limits, for
each and every contingency in the list.
 Economic objective:
– Minimize operating costs: sum of TSOs preventive & corrective
control costs and congestion costs
The N-1 criterion

14
Overall socio-economic impact: a cost function summing
up two terms (to be minimized):
 The Total Risk (for end-users) = the expected socio-
economic costs of service interruptions, as implied by
all possible N-k contingencies and all possible failure
modes that could occur
 The Operating Costs = all direct costs of TSO decisions
minus the induced electricity market surpluses
Socio-economic analysis of alternative reliability criteria

15
Socio-economic impact of covering more or less
contingencies in real-time operation
N-0 N-2N-1N-1/2 …
€
CC
Operating
Cost
Total Risk
Overall socio-economic impact
CC = set of contingencies covered in real-time operation, by minimizing OC under the constraint of
acceptable response to each one of these contingencies

Facing a sudden drop in RES output:
 N-1 clearly too pessimistic !
N-0 N-2N-1N-1/2 …
€
CC
Operating
Cost
Total Risk
Overall SEI

Facing harsh weather conditions:
N-0 N-2N-1N-1/2 …
€
CC
Operating
Cost
Total Risk
Overall SEI
 N-1 too optimistic!

Summary
 N-1 most often not optimal !!!
N-1.5?N-1?N-1/2?
€
CC

19
Outline

GARPUR proposal in a nutshell
In order to decide which subset of contingencies should be
covered, we dynamically adapt to information about
 Socio-economic costs of service interruptions...
 Corrective control failure modes…
 Probabilities… of contingencies and failure modes
To formalize this, we formulate a stochastic
optimization problem called the GARPUR RMAC

The 4 ingredients of the GARPUR RMAC
 A reliability target
 A socio-economic objective function
 A discarding principle
 A relaxation principle
+ Probabilities of threats, and sets of candidate preventive and
corrective control actions used for reliability management

22
Outline

Implementation in practice
Grid development / Asset management / System operation

Declination from Real-Time to Long-Term
 We specify for each context
− The types of candidate decisions available
− The socio-economic objective function
− The reliability target
− The discarding/relaxation principles
 We ensure coherency among different contexts
− Longer-term decisions are chosen to enable the
reachability of shorter-term reliability targets

Webinar 1
25
23 May 2017
Application of RMAC to real time operation:
case study at Landsnet
Samuel Perkin
Landsnet
1 2 3 54

26
Outline
 Moving from N-1 to Probabilistic Reliability Assessment
on the Icelandic system (10 minutes)
 Pilot test overview (2 minutes)
 Initial pilot test results (3 minutes)
Application of RMAC to real time operation1 2 3 54

27
Lost
Load
Energy Not
Served
Interruption
Costs
Risk
Reliability
Indicators
Moving from physical to probabilistic indicators...
From N-1 to GARPUR

28
Lost
Load
Energy Not
Served
Interruption
Costs
Risk
Reliability
Indicators
Requires a number of models...
System
Response
Model
System
Restoration
Model
Socio-
Economic
Model
Probabilistic
Model
System-Wide
Reliability
Model
Moving from physical to probabilistic indicators...
From N-1 to GARPUR

29
Pilot Test Grid Model
Buses: 85
Branches: 107
Generators: 71
The Icelandic System

30
0 20 40 60 80 100 120 140 160
Contingency Number
LostLoad
MaxVm
MinVm
BranchLimsST
BranchLimsLT
Post-Contingency Operational Limit Compliance
Case: heavy system load &
common system topologyFrom N-1 to GARPUR

31
0 20 40 60 80 100 120 140 160
Contingency Number
LostLoad
MaxVm
MinVm
BranchLimsST
BranchLimsLT
Post-Contingency Operational Limit Compliance
0 20 40 60 80 100 120 140 160
Contingency Number
LostLoad
MaxVm
MinVm
BranchLimsST
BranchLimsLT
Post-Control Operational Limit Compliance
Case: heavy system load &
common system topology
Apply Corrective Control Actions
From N-1 to GARPUR
Corrective control resolves many short-term voltage issues...

Compare severity of contingencies based on relative lost load
=> 32 single component contingencies result in some loss of load
32
0 20 40 60 80 100 120 140 160
Contingency Number
0%
1%
2%
3%
4%
5%
6%
Lost Load per Contingency (% of system)
From N-1 to GARPUR
Lost
Load

33
From N-1 to GARPUR
Lost
Load
ENSTo convert lost load to Energy Not Served (ENS) we need a System
Restoration Model that predicts the outage duration per contingency

To convert lost load to Energy Not Served (ENS) we need a System
Restoration Model that predicts the outage duration per contingency
34
Lack of data for large contingencies, so must use heuristic model
From N-1 to GARPUR
Lost
Load
ENS

Can now compare contingencies based on ENS.
The heuristic model doesn‘t change the relative order of contingencies.
0 20 40 60 80 100 120 140 160
Contingency Number
0
20
40
60
80
100
120
ENS per Contingency (MWh)
35
From N-1 to GARPUR
Lost
Load
ENS

36
10 20 30 40 50 60 70
Demand Node
100%
80%
60%
40%
20%
0%
Demand nodes divided by consumer types
PublicServices
Commerce
Residential
OtherIndustry
AlSmelting
Agriculture
Other
AlFactory
FeSiSmelting
Utilities
From N-1 to GARPUR
Lost
Load
ENS
Int.
Cost
To convert ENS into interruption costs, need to know affected
consumer groups and their Value of Lost Load over time

37
0 1 2 3 4 5 6 7 8
Outage Duration (hours)
0
2000
4000
6000
8000
10000
12000
14000
Value of Lost Load per Consumer Type (ISK/kWh)
PublicServices
Commerce
Residential
OtherIndustry
AlSmelting
Agriculture
Other
AlFactory
FeSiSmelting
Utilities
From N-1 to GARPUR
Lost
Load
ENS
Int.
Cost

38
From N-1 to GARPUR
0 20 40 60 80 100 120 140 160
Contingency Number
0
10
20
30
40
Interruption Cost per Contingency (Million ISK)
Lost
Load
ENS
Int.
Cost

39
𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹 = 𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 × 𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷 𝑷𝑷
From N-1 to GARPUR
Lost
Load
ENS
Int.
Cost
Risk
Conversion from Interruption Costs to Risk requires the following
fundamental equation:

40
Conversion from Interruption Costs to Risk requires the following
fundamental equation:
𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹 = 𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 × 𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷 𝑷𝑷
From N-1 to GARPUR
0 20 40 60 80 100 120 140 160
Contingency Number
0%
0.01%
0.02%
0.03%
0.04%
Hourly contingency probability (% per hour)
Lost
Load
ENS
Int.
Cost
Risk

Comparing contingencies by Risk results in different priorities than if
sorting by Interruption Costs or ENS/Lost Load
41
0 20 40 60 80 100 120 140 160
Contingency Number
0
500
1000
1500
2000
Risk per Contingency (expected ISK/hour)
From N-1 to GARPUR
Lost
Load
ENS
Int.
Cost
Risk

42
The three main aggregate indicators in the GARPUR method are:
 Assessed Risk
 Residual Risk
 Probability of an acceptable system state
From N-1 to GARPUR
Lost
Load
ENS
Int.
Cost
Risk
Rel.
Indic.

43
From N-1 to GARPUR
Assessed Risk is simply the sum of each assessed contingency‘s risk
𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨 𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹 = 9422 𝐼𝐼𝐼𝐼 𝐼𝐼
 Assessed Risk
 Residual Risk
Lost
Load
ENS
Int.
Cost
Risk
Rel.
Indic.

44
From N-1 to GARPUR
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 9422 𝐼𝐼𝐼𝐼 𝐼𝐼
𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹 = 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 × 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
 Assessed Risk
 Residual Risk
Lost
Load
ENS
Int.
Cost
Risk
Rel.
Indic.
Discarded probability is the probability of an unassessed event
occurring (i.e. N-2 or worse)
Residual Risk is the product of discarded probability and the worst
case consequences (equivalent to the total loss of the system)

45
From N-1 to GARPUR
𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹𝑹𝑹𝑹𝑹 𝑹𝑹 = 0.0013% × 5223 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝐼𝐼𝐼𝐼 𝐼𝐼 = 68 000 𝐼𝐼𝐼𝐼 𝐼𝐼
 Assessed Risk
 Residual Risk
Lost
Load
ENS
Int.
Cost
Risk
Rel.
Indic.
Residual Risk is the product of discarded probability and the worst
case consequences (equivalent to the total loss of the system)
Discarded probability is the probability of an unassessed event
occurring (i.e. N-2 or worse)

0 20 40 60 80 100 120 140 160
Contingency Number
LostLoad
MaxVm
MinVm
BranchLimsST
BranchLimsLT
46
From N-1 to GARPUR
 Assessed Risk
 Residual Risk
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 68 000 𝐼𝐼𝐼𝐼 𝐼𝐼
First we define an acceptable system state as one that complies with
operational limits (referred to in GARPUR as acceptability constraints)
Lost
Load
ENS
Int.
Cost
Risk
Rel.
Indic.

Lost
Load
ENS
Int.
Cost
Risk
From N-1 to GARPUR
P(Acceptable state) = P(No Fault) + P(Acceptable Contingencies)
0 20 40 60 80 100 120 140 160
Contingency Number
LostLoad
MaxVm
MinVm
BranchLimsST
BranchLimsLT
Rel.
Indic.
𝑷𝑷 𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺 = 99.48% + 0.075%
𝑷𝑷 𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺 = 99.555%
 Assessed Risk
 Residual Risk
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 68 000 𝐼𝐼𝐼𝐼 𝐼𝐼

48
From N-1 to GARPUR
1) Variable failure rates (dependent on weather and other threats)
2) Variable contingency lists (dependent upon the above)
3) Use real-time system state data
4) Assessment across multiple scenarios (of load and generation)
5) Assessment using full socio-economic impact assessment (SEIA)
6) Finding actions that optimise SEIA while maintaining some probability
of an acceptable system state.
So far we have achieved a probabilistic N-1 reliability assessment.
What is missing in order to acheive the GARPUR approach?

49
LANDSNET PILOT TEST
1) Variable failure rates (dependent on weather and other threats)
2) Variable contingency lists (dependent upon the above)
3) Use real-time system state data
4) Assessment across multiple scenarios (of load and generation)
5) Assessment using full socio-economic impact assessment (SEIA)
6) Finding actions that optimise SEIA while maintaining some probability
of an acceptable system state.
At present we have achieved the green items and are yet to implement
those in red
So far we have achieved a probabilistic N-1 reliability assessment.
What is missing in order to acheive the GARPUR approach?

50
LANDSNET PILOT TEST
Basic inputs:
 System state updates every
minute
 Weather data updates every
20 minutes
 Residual risk target equal to
68 000 ISK (N-1 equivalent)
 Contingency list limited to
5000 or fewer to keep
runtime below 2 minutes

51
LANDSNET PILOT TEST
Web UI (internal)

52
LANDSNET PILOT TEST
Live outputs
Risk and acceptability are clearly sensitive to weather
Step in risk between 20:00 and 06:00 caused by variation in economic model

53
LANDSNET PILOT TEST
Live outputs
Contingency set is most often smaller than the N-1 set, but increases
considerably during periods of bad weather

54
LANDSNET PILOT TEST
Live outputs
0: Anomaly
1: Noteworthy
Disturbance
2: Extensive
Incidents
3: Widespread or
Major Incident
For reference: ENTSOe (2012) Incidents Classification Scale Guidelines
Class Definitions:

55
LANDSNET PILOT TEST
Live outputs
Displaying live weather data (used by the model) on dashboard to improve
understanding of the pilot test outputs

56
LANDSNET PILOT TEST
Live outputs
Initial attempts to ‚dig‘ into the outputs provided only minor insights, and
were difficult to read at a glance

57
LANDSNET PILOT TEST
Risk Map:
 Same information as on
previous slide
 Captures temporal aspect
(paths showing prior changes)
 Simple to compare
contingencies
 Consistent & unique colours
allows for quick interpretation

58
Closing remarks
 Showed the path from N-1 to probabilistic risk assessment
 Landsnet pilot test shows that the approach is feasible with
presently available data
 Future work required to upgrade the models to capture
dynamic stability, system restoration, and to move from
assessment to control.

Webinar 1
59
23 May 2017
Conclusion:
Benefits of the GARPUR Methodology
for probabilistic Reliability Management
Louis Wehenkel
GARPUR Scientific Advisor
University of Liège
1 2 3 54

60
 Dynamic contingency selection
 Coherent decision making among timeframes
 New approaches for reliability assessment and
control
Conclusion: benefits of GARPUR methodology1 2 3 54
Main benefits

61
 A theoretically founded principle for choosing the
subset of N-k contingencies that have to the covered by
preventive and corrective control actions
 Its implementation will support operators to adjust
their perception of the risk and determine a strategy to
manage reliability
 Overall, the principle will help to optimize the socio-
economic impact of the reliability management
decisions taken by TSOs
Dynamic contingency selection

62
 We show how to take into account the short-term
reliability management approach when carrying out
longer-term studies
Coherent decision-making from planning to operation

63
 Reliability assessment, from long-term to real-time
 Reliability control for real-time and mid-term
 A simulation framework to study off-line the impact of
moving from N-1 to the probabilistic RMAC
New tools and methods

64
 Simulates the operation of the power system submitted to
a given set of external event, by allowing one to plug in the
RMAC the operator would use
 Allows to compare the outcome of operating the system
while using different RMACs
 Is used to compare the N-1 RMAC with the GARPUR RMAC
 Comparison is based on socio-economic impact, and its
decomposition in several ‘cost’ terms
Teaser 1 for next Webinar, Fall 2017
GARPUR Quanification Platform

65
 Testing the use of the GQP in realistic conditions
 Studying the outcomes of the probabilistic
RMAC when used in long-term grid development
studies
Teaser 2 for next Webinar, Fall 2017
The other pilots tests

66
Q & A session1 2 3 54
http://www.garpur-project.eu/

TSO Reliability Management: a probabilistic approach for better balance between reliability & costs

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