Computational Intelligence in Electric Power Transmission

The continuing rapid growth in the size, load demand and complexity of the power network has led to the need for more sophisticated and intelligent techniques of controlling and optimizing the behavior of this network. Computational Intelligence (CI) is an emerging field that has grown significantly in the last decade as evidenced by the creation of the IEEE Computational Intelligence Society (CIS). This field has produced promising techniques for modeling, control and optimization of nonlinear, non-stationary, large, multi-variable complex systems. The book has five parts: Part I introduces and describes the five main paradigms of CI: neural networks, evolutionary computation, swarm intelligence, fuzzy systems and artificial immune systems that readers will need to understand Parts II to IV. Part II focuses on CI-based state estimation, modeling and control of generators, FACTS devices, wind farms and photovoltaic systems, motors, wide area monitoring and control of power systems, fault tolerant control, and estimation and mitigation control of harmonics. Part III focuses on applications of CI-based optimization techniques for controller tuning, FACTS placement, economic dispatch and reactive power optimization. Part IV describes a methodology for solving the problem of finding a secure operating point of a power system and Part V describes the development and implementation of an artificial neural network suitable for protecting transmission lines. The book is written so that the reader, with a basic background in power systems and a novice in computational intelligence, will be able to understand and apply the various CI concepts to power systems modeling, control and optimization problems.