SE4SG 2013 : Towards a Constraint Based Approach for Self-Healing Smart Grids

Towards a Constraint Based
Approach for Self-Healing
Smart Grids
ICSE 2013 International Workshop on Software Engineering Challenges
for the Smart Grid
18.05.2013 Smart Grid Research Initiative / Computing Faculty / Technical University of Munich – http://smartgrid.in.tum.de/ 1
Vasileios Koutsoumpas, Technical
University of Munich
Pragya K. Gupta, Fortiss GmbH

Koutsoumpas, Gupta: Towards a Constraint Based Approach for Self-Healing Smart Grids. ICSE 2013 International Workshop on SE4SG
18.05.2013 Smart Grid Research Initiative / Computing Faculty / Technical University of Munich – http://smartgrid.in.tum.de/ Slide: 2
Overview and Backround
 Electrical Grid
Balance between consumption and production
Central power generation
Renewable energy sources and ICT
Reformation of the grid
 New Features
Handling of bidirectional energy flows
Automatic fault detection
Self-healing of the network
Demand-side management
Load adjustment
Smart sensing
Smart Market

Scenario 2
Scenario 1
Research Motivation
Power
Generator B
Power
Generator A
Switch 1
Switch 2
Switch 3
L
S
L
S
L
S
Car hits
switch 2
Connected
Region
looses
power
Customer
inform the
energy
provider
Energy
Provider
assign the
task to
technician
s
Problem
Detection
Repair-
Action
Stable
State
Car hits
switch 2
Rerouting
Switch 3
closes
Only not
reachable
Region
looses power
Energy
Provider
send
technicians
to the
isolated
region
Repair-
Action
Stable State
What just happened?
Runtime verification, Repair action
selected and executed, Self-Healing
Process
Main Questions:
How to develop self-healing systems
efficiently?
Model based/formal method
Model everything
Formalize semantics
Formal Specification
Verification

System Theory: FOCUS
C C
On
Off
press
press
Properties
 Formal System Specification
 Composition/Decomposition
 Refinement
C2 C3
C1
Toolsupport
 Autofocus3

Logical Specification with Predicate Logic
System Specification
Component 1
Input
Output
Attributes
Constraints
Formal System Specification
 Signature ∑ : A set of attributes
 Constraint Language CL(∑) : A set of
logical constraints over the signature ∑.
 Logical Specification
 Self-Healing Properties
 Runtime Verification

Physical Cells
7
Energy Bus
Data Bus
5
-4
-8 -3
14 113 200 -6
-2-18
-2 3
-5
7
Energy Bus
Data Bus
5
-4
-8 -3
14 113 200 -6
-2-18
-2 3
-5
7
Energy Bus
Data Bus
5
-4
-8 -3
14 113 200 -6
-2-18
-2 3
-5

Architecture for the Smart Grid
Physical Layer (Physical Cells)
C
C C
C
C
C C
C
C
C C
C
C
C C
C
logical Layer (Logical Cells)
Functional Layer
FRFR
FR FR
FRFR FR FR
Top-Down
Bottom-Up
 Functional Layer: Describes the usage functionality that
a system offers its environment. Functional
requirements are used to formalize this functionality
(black box view)
 Logical Layer: Describes how the functionality is realized
by a network of interacting logical cells
 Physical Layer: Describes the physical infrastructure and
the concrete realization of a functionality with all
technical details (glass box view)
 Hybrid Approach

Cellular Model for the Smart Grid
Market
Physical Cell
Logical Cell
Energy Flow
Data Flow
Energy and
Data Flow
Flexibility
Operator
 Vision of future grids
 Physical cells conform to a given policy
 Policies derive mostly from the functional
requirements
 Example: Autonomous behavior is a FR. This
can be interpreted as a policy. This policy can
be formalized.
 FR->Policies->Formalization by predicate logic
 Logical cell realizes concepts that are domain
specific.
 Example flexibility operator
 Market role
 Cellular decomposition
 Cellular composition

Diagnosis Model for Self-Healing Smart
Grids
Sytem Model
Data Space
Generalized
Data
Data Collection
Hypothesis Space Therapy-Repair-Space
General
Hypotheses
Hypotheses-
Solutions
General Plan for
Therapie-Repair
Concrete
Actions for
Healing
Data
Generalization
Therapy-Repair
System
i1
i3i2
i4
o4
o3
Formal Specification with
constraints
Selection of
Healing
Actions
Creation of
Healing Actions
Recognition of
Inconsistencies
Hypothesis
Selection
Hypothesis
Checking
Creation of
Hypothesis
Alternatives
Cell
Energy Flow
Data
Flow
Energy
and Data
Flow
CellPhysical Cell
Logical Cell
 Search Spaces
Data space: set of possible measurements
Hypothesis space: set of all possible reasons that can cause
any dysfunction to the system
Therapy-repair space: a set of all actions that can confront
some dysfunction
 Values
Possible values: valid or not
Normal values: valid values that declare the normal
operation
Observed values: from measurement devices or sensors
Predicted values
• Operations
Data gathering operations
Therapy-repair operations
Selection operations

The Gap between normal and broken
State
Normal State
Broken State
Degraded State
Detection of
System Failure
System recovery
System recovery
Detection of
System Failure

Outlook
 Focus on the fuzzy zone
 Evaluation E-Energy
 Framework and Tool
Support
 Smart City Simulation
Past, Present and Future
Sytem Model
Data Space
Generalized
Data
Data Collection
Hypothesis Space Therapy-Repair-Space
General
Hypotheses
Hypotheses-
Solutions
General Plan for
Therapie-Repair
Concrete
Actions for
Healing
Data
Generalization
Therapy-Repair
System
i1
i3i2
i4
o4
o3
Formal Specification with
constraints
Selection of
Healing
Actions
Creation of
Healing Actions
Recognition of
Inconsistencies
Hypothesis
Selection
Hypothesis
Checking
Creation of
Hypothesis
Alternatives
Cell
Energy Flow
Data
Flow
Energy
and Data
Flow
CellPhysical Cell
Logical Cell

End
Thank you for your Attention!

Discussion

Smart Grid Initiative
Georg Hackenberg, Technical
University of Munich, Goal Oriented
Modeling of Requirements
Maximilian Irlbeck, Technical
University of Munich, Reference
Architecture for Smart Grids
Vasileios Koutsoumpas, Technical
University of Munich, Self-Healing
Applications for Smart Grids
Denis Bytchkow, Fortiss GmbH, Goal
Oriented Modeling of Requirements
Pragya K. Gupta, Fortiss GmbH,
Requirements Engineering

SE4SG 2013 : Towards a Constraint Based Approach for Self-Healing Smart Grids

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SE4SG 2013 : Towards a Constraint Based Approach for Self-Healing Smart Grids