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

Heuristic Optimization Techniques Genetic AlgorithmsGenetic Algorithms Evolutionary ProgrammingEvolutionary Programming Swarm IntelligenceSwarm Intelligence Particle SwarmParticle Swarm DNA ComputingDNA Computing Artificial LifeArtificial Life Intelligent AgentsIntelligent Agents

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.

Nature is a Powerful Paradigm Brain  neural networks Evolution theory  genetic algorithms Flock of birds  particle swarm optimization Insects  swarm intelligence ……

Classical Control: Design System inputs Control Inputs Constraints

Classical Control: Operation System inputs Control Inputs Constraints

PSO Control System inputs Control Inputs Constraints

PSO/NN Control System inputs Control Inputs Constraints

Gradient Search vs MAS Gradient Search MAS

Evolutionary Algorithms

Population Pool Byte 1Byte 2Byte n 1 individual #1 #2 #3 #K 22 nn

Fitness Evaluation #1 #2 #3 Individuals #n Fitness Computations f(.) Normalize Ranked Individuals #q #p #q # #3 #n #

Two-point Crossover Two crossover points are obtained by a random number generator #p #q Crossover #p #q Crossover points

Mutation mutation #p

Particle Swarm Optimization

Personal Best at previous step Current motion Component in the direction of personal best Component in the direction of previous motion Component in the direction of global best New Motion Global best

Border (Edge) Identification

The Art of Fitness Function To find points anywhere on the boundary Metric: |f(x)-boundary value|

Results - Case 1

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)

Results - Case 2

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)

Results - Case 3

Test System WSCC 179 Bus System Cascading event Base Case 61,411 MW 12,330 MVAR

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)

Swarm Intelligence

Swarm Intelligence Coordination without Swarm Intelligence = Coordination without Direct Communication

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

Pheromone Trails

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

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

Finis