Modern Heuristic Optimization Techniques and Potential Applications to Power System Control

1
Modern Heuristic Optimization Techniques and
Potential Applications to Power System Control

• Mohamed A El-Sharkawi
• The CIA lab
• Department of Electrical Engineering
• University of Washington
• Seattle, WA 98195-2500
• elsharkawi_at_ee.washington.edu
• http//cialab.ee.washington.edu

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Heuristic Optimization Techniques

• Genetic Algorithms
• Evolutionary Programming
• Swarm Intelligence
• Particle Swarm
• DNA Computing
• Artificial Life
• Intelligent Agents

3
Biocomputation

• The use of biological processes or behavior as
  metaphor, inspiration, or enabler in developing
  new computing technologies
• The field is highly multidisciplinary, Engineers,
  computer scientists, molecular biologists,
  geneticists, mathematicians, physicists, and
  others.

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Nature is a Powerful Paradigm

• Brain ? neural networks
• Evolution theory ? genetic algorithms
• Flock of birds ? particle swarm optimization
• Insects ? swarm intelligence

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Classical Control Design
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Classical Control Operation
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PSO Control
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PSO/NN Control
Constraints
System inputs
NN Model
Objectives
Control Inputs
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Gradient Search vs MAS
MAS
Gradient Search
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Evolutionary Algorithms
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Population Pool
Byte 1
Byte 2
Byte n
individual
?1
?2
?n
...
1
1
0
0
1
1
1
1
1
1
1
0
0
0
0
0
0
1
1
1
1
0
0
0
0
...
2
0
0
1
1
1
1
1
1
1
0
0
0
0
0
0
1
1
1
1
0
0
0
0
0
...
3
1
0
0
1
1
1
1
1
1
1
0
0
0
0
0
0
1
1
1
1
0
0
1
1
...
K
0
0
1
0
0
1
1
1
1
1
1
0
0
0
0
0
0
1
1
1
0
0
0
0
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Fitness Evaluation
Ranked Individuals
Individuals
2
0
0
1
1
1
0
0
1
1
0
0
1
1
1
0
Fitness
n
2
Computations
1
0
0
1
1
1
0
0
0
1
1
1
0
0
Normalize
q
3
f(.)
1
0
0
1
1
1
0
0
0
1
1
1
0
0
p
p
0
0
1
1
1
0
0
1
0
0
1
1
1
0
q
1
1
0
0
1
1
1
0
1
0
0
1
1
1
0
3
n
1
0
0
1
1
1
0
1
0
0
1
1
1
0
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Two-point Crossover

• Two crossover points are obtained by a random
  number generator

Crossover points
2
1
2
1
p
Crossover
p
0
0
1
1
1
0
0
1
1
1
0
0
0
1
q
q
1
0
0
1
1
1
0
0
0
1
1
0
0
1
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Mutation
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Particle Swarm Optimization
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Border (Edge) Identification
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The Art of Fitness Function

• To find points anywhere on the boundary
• Metric f(x)-boundary value

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Results - Case 1
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The Art of Fitness Function

• Distribute points uniformly on the boundary
• Metric
• f(x)-boundary value -Distance to closest
  neighbor

(to penalize proximity to neighbors)
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Results - Case 2
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The Art of Fitness Function

• Distribute points uniformly on the boundary close
  to current state
• Metric
• f(x)-boundary value -Distance to closest
  neighbor Distance to current state
• (penalize proximity to neighbors, penalize
  distance from current state)

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Results - Case 3
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Cascading event
Test System WSCC 179 Bus System
Base Case 61,411 MW 12,330 MVAR
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First Event Initial Contingency
Three Phase fault on the line between John Day
(76) and Grizzly (82)
Second Event
Trip the line between John Day (76) and Hanford
(78)
Third Event
Trip the line between John Day (78) and North
500 (80)
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Swarm Intelligence
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Swarm IntelligenceCoordination without Direct
Communication
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Swarm Intelligence

• Appears in biological swarms of certain insect
  species
• Interactions is indirect (stigmergy)
• The end result is accomplishment of very complex
  forms of social behavior and fulfillment of a
  number of tasks

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Pheromone Trails
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DE 0.15 CD 0.14 BC 0.11 AB 0.23
BC 0.11 AB 0.23
B
D
AB 0.23
CD 0.14 BC 0.11 AB 0.23
A
C
E
G
F
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DE 0.15 CD 0.14 BC 0.11 AB 0.23
BC 0.11 AB 0.23
B
D
AB 0.23
CD 0.14 BC 0.11 AB 0.23
A
C
E
G
F
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