Cutting-edge research indicates that evolutionary programming is
set to emerge as the dominant optimisation technique in the
fast-changing power industry. Combining theory and practice,
Intelligent System Applications in Power Engineering capitalises on
the potential of neural networks and evolutionary computation to
resolve real-world power engineering problems such as load
forecasting, power system operation and planning optimisation.
Unlike existing optimisation methods, these novel computational
intelligence techniques provide power utilities with innovative
solutions for improved performance. Features include:
- Introduction to evolutionary programming and neural networks
serving as a foundation for later discussion of the benefits of
hybrid systems
- Practical application of evolutionary programming to reactive
power planning and dispatch for speedy, cost-effective increases in
transmission capacity plus generator parameter estimation
- Examination of economic dispatch, power flow control in FACTS
and co-generation scheduling and fault diagnosis for HVDC systems
and transformers
- Consideration of power frequency and harmonic evaluation to
maximise supply quality
- Employment of distance protection, faulty section estimation
and calculation of fault clearing time for transient stability
assessment
Graduate students in electric power engineering will value Lais
broad coverage of the applications of evolutionary programming and
neural networks in the field. This unique reference will be a boon
to engineers, computer application specialists, consultants and
utility managers wishing to understand the benefits intelligent
systems can bring to the power industry.
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