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Modeling of photovoltaic sources and their emulation by means of
power electronic converters are challenging issues. The former is
tied to the knowledge of the electrical behavior of the PV
generator; the latter consists in its realization by a suitable
power amplifier. This extensive introduction to the modeling of PV
generators and their emulation by means of power electronic
converters will aid in understanding and improving design and set
up of new PV plants. The main benefit of reading Photovoltaic
Sources is the ability to face the emulation of photovoltaic
generators obtained by the design of a suitable equipment in which
voltage and current are the same as in a real source. This is
achieved according to the following steps: the source electrical
behavior modeling, the power converter design, including its
control, for the laboratory emulator. This approach allows the
reader to cope with the creation of an indoor virtual photovoltaic
plant, in which the environmental conditions can be imposed by the
user, for testing real operation including maximum power point
tracking, partial shading, control for the grid or load
interfacing, etc. Photovoltaic Sources is intended to meet the
demands of postgraduate level students, and should prove useful to
professional engineers and researchers dealing with the problems
associated with modeling and emulation of photovoltaic sources.
Modeling of photovoltaic sources and their emulation by means of
power electronic converters are challenging issues. The former is
tied to the knowledge of the electrical behavior of the PV
generator; the latter consists in its realization by a suitable
power amplifier. This extensive introduction to the modeling of PV
generators and their emulation by means of power electronic
converters will aid in understanding and improving design and set
up of new PV plants. The main benefit of reading Photovoltaic
Sources is the ability to face the emulation of photovoltaic
generators obtained by the design of a suitable equipment in which
voltage and current are the same as in a real source. This is
achieved according to the following steps: the source electrical
behavior modeling, the power converter design, including its
control, for the laboratory emulator. This approach allows the
reader to cope with the creation of an indoor virtual photovoltaic
plant, in which the environmental conditions can be imposed by the
user, for testing real operation including maximum power point
tracking, partial shading, control for the grid or load
interfacing, etc. Photovoltaic Sources is intended to meet the
demands of postgraduate level students, and should prove useful to
professional engineers and researchers dealing with the problems
associated with modeling and emulation of photovoltaic sources.
The first book of its kind, Power Converters and AC Electrical
Drives with Linear Neural Networks systematically explores the
application of neural networks in the field of power electronics,
with particular emphasis on the sensorless control of AC drives. It
presents the classical theory based on space-vectors in
identification, discusses control of electrical drives and power
converters, and examines improvements that can be attained when
using linear neural networks. The book integrates power electronics
and electrical drives with artificial neural networks (ANN).
Organized into four parts, it first deals with voltage source
inverters and their control. It then covers AC electrical drive
control, focusing on induction and permanent magnet synchronous
motor drives. The third part examines theoretical aspects of linear
neural networks, particularly the neural EXIN family. The fourth
part highlights original applications in electrical drives and
power quality, ranging from neural-based parameter estimation and
sensorless control to distributed generation systems from renewable
sources and active power filters. Simulation and experimental
results are provided to validate the theories. Written by experts
in the field, this state-of-the-art book requires basic knowledge
of electrical machines and power electronics, as well as some
familiarity with control systems, signal processing, linear
algebra, and numerical analysis. Offering multiple paths through
the material, the text is suitable for undergraduate and
postgraduate students, theoreticians, practicing engineers, and
researchers involved in applications of ANNs.
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