Workshop4:Nature Inspired Algorithms in Electric Power Systems (NIA-EPS 2011)

Call for paper:
Nature Inspired Algorithms (NIA) are relatively a newer addition to class of population based stochastic search techniques. These algorithms are based on the evolutionary, self organising and collective processes in nature for example the concepts of natural evolution like selection, reproduction and mutation form the key ingredients of certain NIA whereas the socio-cooperative behaviour displayed by natural species like birds, ants, termites and bees (and also human behaviour) form basis of some other NIA. These algorithms seem promising because of their social –cooperative approach and because of their ability to adapt themselves in the continuously changing environment.

NIA techniques have been applied to several problems in smart grid technologies that will enable power system to optimize use of renewable energy sources and transmission infrastructures. Thermal unit commitment / hydrothermal coordination and economic dispatch / optimal power flow, maintenance scheduling, reactive sources allocation and expansion planning are among the most important applications.

This special session will attempt to bring together researchers and practitioners to a common platform and will create a forum to discuss the latest development in this application.  Authors are invited to submit their original and unpublished work to this Special Session.

The following are the topics of interests but not limited to:

•Differential Evolution Algorithm
•Particle Swarm Optimization
•Genetic Algorithms
•Genetic Programming
•Ant Colony Optimization
•Bacterial Foraging Algorithm
•Honey-Bee Algorithm
•Evolutionary Programming
•Evolutionary Strategies
•Tabu Search
•Simulated Annealing

Power System Applications:
•Power system operation
•Power system planning
•Power system control
•Power system protection
•Power plant control
•Network control
•Power system automation
•Electricity markets
•Distribution system application
•Distributed generation application
•Forecasting application

Dr. Thanga Raj Chelliah,
System and Control Engineering,
Faculty of Science, Technology and Communication,
University of Luxembourg,

Dr. Radha Thangaraj,
Department of Computer Science and Communication,
Faculty of Science, Technology and Communication,
University of Luxembourg,

Prof. Ajith Abraham,
Machine Intelligence Research Labs,
Scientific Network for Innovation and Research Excellence,