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An electrical power system consists of a large number of
generation, transmission, and distribution subsystems. It is a very
large and complex system; hence, its installation and management
are very difficult tasks. An electrical system is essentially a
very large network with very large data sets. Handling these data
sets can require much time to analyze and subsequently implement.
An electrical system is necessary but also potentially very
dangerous if not operated and controlled properly. The demand for
electricity is ever increasing, so maintaining load demand without
overloading the system poses challenges and difficulties. Thus,
planning, installing, operating, and controlling such a large
system requires new technology. Artificial intelligence (AI)
applications have many key features that can support a power system
and handle overall power system operations. AI-based applications
can manage the large data sets related to a power system. They can
also help design power plants, model installation layouts, optimize
load dispatch, and quickly respond to control apparatus. These
applications and their techniques have been successful in many
areas of power system engineering. Artificial Intelligence
Techniques in Power Systems Operations and Analysis focuses on the
various challenges arising in power systems and how AI techniques
help to overcome these challenges. It examines important areas of
power system analysis and the implementation of AI-driven analysis
techniques. The book helps academicians and researchers understand
how AI can be used for more efficient operation. Multiple AI
techniques and their application are explained. Also featured are
relevant data sets and case studies. Highlights include: Power
quality enhancement by PV-UPQC for non-linear load Energy
management of a nanogrid through flair of deep learning from IoT
environments Role of artificial intelligence and machine learning
in power systems with fault detection and diagnosis AC power
optimization techniques Artificial intelligence and machine
learning techniques in power systems automation
Introduces the recent applications of new computational intelligent
technologies focusing on medical diagnosis issues Reviews
multidisciplinary research in healthcare like data mining, medical
imaging, pattern recognition and so forth Explores intelligent
systems and application of learning in healthcare challenges along
with the representation and reasoning of clinical uncertainty
Addresses the problems resulting from automated data collection in
modern hospitals with possible solutions to support medical
decision-making system Discusses current and emerging intelligent
system with respect to evolutionary computation and its
applications in medical domain
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