Applied Natural Computing in Power Systems

Call for Chapters

Nadia Nedjah, Leandro dos Santos Coelho, Viviana Cocco Mariani, Luiza de Macedo Mourelle (Eds.)

The soft computing, quantum computing and chaos theory approaches differ from the respective conventional computing techniques in that they are tolerant of imprecision, uncertainty, partial truth, and approximation. The soft computing techniques comprises of fuzzy systems, artificial neural networks, swarm intelligence, probabilistic reasoning and meta-heuristic techniques such as evolutionary algorithms (genetic algorithms, evolutionary programming, differential evolution, evolution strategies, genetic programming), tabu search, among others.

On the other hand, quantum computing is a research field that includes concepts like quantum-mechanical computers and quantum algorithms. So far, many efforts on quantum computers have progressed actively due to its superiority to classical computers on various specialized problems. There are some well-known quantum algorithms, such as Grover's database search algorithm and Shor's quantum factoring algorithm. In this context, recently, quantum-inspired evolutionary algorithms (QEAs) have attracted much attention and wide applications. QEAs can be useful to treat the balance between exploration and exploitation more easily compared to conventional evolutionary algorithms.

Other emergent approach in design of intelligent systems is the chaos theory. Chaos is a kind of characteristic of nonlinear systems, which is a bounded unstable dynamic behavior that exhibits sensitive dependence on initial conditions and includes infinite unstable periodic motions. Recently, the combination of optimization methods, intelligent systems, quantum approaches and concepts of chaotic systems are modern issues in nonlinear science and has attracted interests from various fields.

For this book, we seek original contributions on any aspect related to optimization, modeling, nonlinear identification, control, automation, among others using soft computing, quantum computing and chaos theory approaches. Applications of mentioned design and optimization methodologies in power systems to real-world system are welcome. The topics of interest include, but not limited to:

Intelligent systems and bio-inspired approaches in tuning of stabilizers parameters and automatic voltage regulators Quantum-inspired evolutionary algorithms in power systems Soft computing, quantum computing and chaos theory approaches in load frequency controller designs in power systems Power transformers diagnosis using emergent bio-inspired approaches Computational intelligence for fault diagnosis of power plant, optimal reactive power flow, economic power dispatch, alarm processing, short term scheduling, and environmental/economic power dispatch Multiobjective algorithms using global optimization methodologies based on quantum computing, chaotic systems, and intelligent systems Intelligent systems applied to reliability engineering approaches in electrical power systems Bio-inspired approaches in design of distribution, transmission and generation systems Optimal capacitor placement in distribution systems using soft computing, quantum computing and chaos theory approaches Applications of intelligent systems, quantum computing, and chaotic approaches in short-term electric load forecasting.

The time schedule for this publication is as follows:

1. Manuscript submission: May 28, 2010
2. Authors Notification: August 30, 2010
3. Camera-ready submission: September 25, 2010