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PEE201 AI TECHNIQUES IN ELECTRIC POWER SYSTEM AND DRIVES

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3 1 2 4.5

Prerequ!"e#!$%

Overview : Concepts of artificial intelligence (AI) and optimization, introduction of various AI

techniques, their features and advantages in comparison to conventional methods, their

applications in power and electric drive systems

&u''( L)*+ % !eview of fuzzy sets and fuzzy control systems, development of mem"ership

function, #uzzy measures, #uzzy $ayesian decision ma%ing, fuzzy system design and simulation,

fuzzy optimization, , solution of linear system under fuzzy environment, multi&input, multi&output

system, multi&o"'ective decision ma%ing

Ar",+- Neur- Ne"/)r % !eview of A and learning processes, learning algorithms,

supervised learning as an optimization method, ransforming static neural networ% intodynamic, neuronal filters, temporal "ac%&propagation algorithm, additive neurodynamical model,

application of *opfield neural networ% for constrained and unconstrained optimization, stochasticmachines, recurrent networ% architectures, time&delay feed forward neural networ%,

computational power of recurrent neural networ%, +alman filter,

E)u")-r( A*)r"!%!eview of evolutionary algorithms and various operators, mapping

unconstrained and constrained optimization pro"lems, evolutionary programming, goal

programming

Mu")6e+"e )7"'-") % Comparison with single o"'ective optimization, concept of

dominance, non&dominated shorting, multio"'ective optimization using genetic algorithm

I"e*r-"e8 S(!"e!%Introduction to integrating systems li%e fuzzification of neural neywor%,

eural fuzzy controller, -A "ased fuzzy classification, -A "ased parameter learning of neural

networ%

AI A77+-")! P)/er S(!"e!% Case studies such as .conomic load dispatch, load

forecasting, optimal power flow, transient sta"ility and power system sta"ilizers, hydro&thermal

scheduling, voltage control, protection system

AI A77+-") Ee+"r+ Dre! S(!"e! % Case studies such as Induction motor speed

control, wind generation system, /01 controller, model identification and adaptive drive

control, estimation of distorted waves

L-)r-")r(% 2nderstanding the #uzzy, neural networ% and -A concepts through programming,

2se of 1A3A$ ool "o4es, fuzzy system applications li%e cruise control, 5C motor control,

power system sta"ilizer, eural networ% models and learning, constrained optimization using

neural networ% li%e .conomic 5ispatch, Implementing "inary and real value -A

Re+)e8e8 9))!

6 !oss, 7 , #uzzy 3ogic with .ngineering Applications, 1c-raw

*ill (6889)

; *ay%in, eural etwor% : A comprehensive foundation, /earson .ducation (

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6 $ring your calculator daily

3ate entry in the class is not allowed ry to "e punctual

= hree will "e two theory quizzes as per the sylla"us announced #irst quiz will "eimmediately after mid sem test from the corresponding sylla"us ;econd quiz will

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8/13/2019 Pee201ai(t)

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8/13/2019 Pee201ai(t)

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Oere/ % Concepts of artificial intelligence (AI) and optimization,

introduction of various AI techniques, their features and advantages in

comparison to conventional methods, their applications in power and

electric drive systems

=

&u''( L)*+ % !eview of fuzzy sets and fuzzy control systems,

development of mem"ership function, #uzzy measures, #uzzy $ayesiandecision ma%ing,

=

#uzzy system design and simulation, fuzzy optimization

=

?;olution of linear system under fuzzy environment

=

9

1ulti&input, multi&output system, multi&o"'ective decision ma%ing

=

Applications of #uzzy logic to optimal power flow pro"lem, induction

motor speed control

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Ar",+- Neur- Ne"/)r %!eview of A and learning processes,

learning algorithms

;upervised learning as an optimization method

6

8

ransforming static neural networ% into dynamic

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