Artificial with ideas rather than events. 7. Randomness and

Artificial
Intelligence is the study of how to make computer do the things which at
present human can do better. Artificial
intelligence is a branch of computer science that aims to create intelligent
machines. It has become an essential part of the technology industry.

According to the father of Artificial
Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially
intelligent computer programs”.

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AI is accomplished by studying how human
brain thinks, and how humans learn, decide, and work while trying to solve a
problem, and then using the outcomes of this study as a basis of developing
intelligent software and systems.

A branch of Computer Science named Artificial
Intelligence pursues creating the computers or machines as intelligent as
human beings.

The philosophy of
artificial intelligence attempts to answer such questions as follows: Can a
machine act intelligently? Can it solve any problem that a person would solve
by thinking? Are human intelligence and machine intelligence the same?

Thus, the development of AI started with
the intention of creating similar intelligence in machines that we find and
regard high in humans.

A)   
Goals of AI

·       
To Create Expert Systems ? The systems which exhibit
intelligent behavior, learn, demonstrate, explain, and advice its users.

·       
To Implement Human Intelligence in Machines ? Creating systems that understand,
think, learn, and behave like humans.

B) The Original 7 Aspects of A.I.:

 

1.
Simulating higher functions of the human brain

2.
Programming a computer to use general language.

3.
Arranging hypothetical neurons in a manner so that they can form concepts.

4.
A way to determine and measure problem complexity.

5.
Self-Improvement.

6.
Abstraction: Defined as the quality of dealing with ideas rather than events.

7.
Randomness and creativity.

Strong A.I. can do anything as well/better than a
human.

Weak A.I. achieves only the result of a human.  Example: playing chess.

C) What is AI Technique?

In the real world, the knowledge has some
unwelcomed properties ?

Its volume is huge,
next to unimaginable.It is not
well-organized or well-formatted.It keeps changing
constantly.

AI Technique is a manner to organize and
use the knowledge efficiently in such a way that ?

It should be
perceivable by the people who provide it.It should be easily
modifiable to correct errors.It should be useful in
many situations though it is incomplete or inaccurate.

AI techniques elevate the speed of
execution of the complex program it is equipped with.

 

II. AREAS OF ARTIFICIAL
INTELLIGENCE

AI has been dominant in various fields
such as ?

·       
Gaming ? AI plays crucial role in strategic
games such as chess, poker, tic-tac-toe, etc., where machine can think of large
number of possible positions based on heuristic knowledge.

·       
Natural
Language Processing ?
It is possible to interact with the computer that understands natural language
spoken by humans.

·       
Expert
Systems ? There are
some applications which integrate machine, software, and special information to
impart reasoning and advising. They provide explanation and advice to the
users.

·       
Vision
Systems ?  These systems understand, interpret, and
comprehend visual input on the computer. For example,

o   A spying airplane takes photographs, which
are used to figure out spatial information or map of the areas.

o   Doctors use clinical expert system to
diagnose the patient.

o   Police use computer software that can
recognize the face of criminal with the stored portrait made by forensic artist.

·       
Speech
Recognition ? Some
intelligent systems are capable of hearing and comprehending the language in
terms of sentences and their meanings while a human talks to it. It can handle
different accents, slang words, noise in the background, change in human’s
noise due to cold, etc.

·       
Handwriting
Recognition ? The
handwriting recognition software reads the text written on paper by a pen or on
screen by a stylus. It can recognize the shapes of the letters and convert it
into editable text.

·       
Intelligent
Robots ? Robots are
able to perform the tasks given by a human. They have sensors to detect
physical data from the real world such as light, heat, temperature, movement,
sound, bump, and pressure. They have efficient processors, multiple sensors and
huge memory, to exhibit intelligence. In addition, they are capable of learning
from their mistakes and they can adapt to the new environment.

III. Application Of Artificial Intelligence
Techniques in Power Station

Artificial intelligence is that the science of automating intelligent
behaviors presently accomplishable by humans. Power system has full-grown
hugely over many decades. Because the size and complexness of the facility
system consisting of generators, control transformers, transmission lines,
distribution transformers etc. will increase the likelihood of tantalizing
faults. The acquisition of knowledge, the process of this information to be
used by the operator, and management of remote devices are the essential
building blocks of all fashionable utility management systems.

I. INTRODUCTION

There are three kinds
of nation plants acknowledged for the huge electricity generation:

i)                   
Nuclear power
plants

ii)                 
 ii) Thermal power plants

iii)               
 iii)Hydal power plants

 

 One may expect that the mobile sensing will
play an increasingly important role in the monitoring of power system. An
expert system obtains the knowledge of a human expert in a narrow specified
domain into a machine implementable form. Skilled systems also are referred to
as information based mostly systems or rule based systems. Expert systems are
computer programs which have ability and competence in a particular field.

 

Artificial neural
networks are biologically inspired systems which convert a set of inputs into a
set of outputs by a network of neurons, where each neuron produces one output
as a function of inputs. A fundamental neuron can be considered as a processor
which makes a simple non linear operation of it’s input producing a single
output.

 

They are classified by
their architecture: number of layers and topology: connectivity pattern, feed
forward or recurrent.

 

II. METHODS USED IN IMPLEMENTATION

 

There are mainly three
techniques:

i)Expert system techniques,

 

Expert system is a
kind of intelligent computer software system which is built by human experts.
It contains a large amount of professional knowledge and rich experience in the
power system. Its use has penetrated into all fields. Especially in the field
of artificial intelligence technology and even exceed the level of human
expert. In medical diagnosis, geological exploration, culture and education has
been equipped with the corresponding knowledge and procedures of the system and
the problem of solving and processing has been close to the level of experts.

Expert systems are
computer programs which have proficiency and competence in a particular field.

 

They are also called
as knowledge based systems or rule based systems.

 

Expert systems use the
interface mechanism and knowledge to solve problems which cannot be or
difficult to be solved by human skill and intellect.

 

Advantages:

Permanent and
consistent.Easily
documented.Easily
transferred or reproduced

 

Disadvantages:

They are unable
to learn or adapt to new problems or situations.

 

Since expert systems
are basically computer programs, the process of writing codes for these
programs is simpler than  actually
calculating and estimating the value of parameters used in generation,
transmission and distribution.

Any modifications even
after design can be easily done because they are computer programs.

 

An expert system
obtains the knowledge of a human expert in a narrow specified domain into a
machine implementable form.

Virtually, estimation
of these values can be done and further research for increasing the efficiency
of the process can be also performed.

 

 

 ii) Artificial
neural networks,

 

Artificial Neural
Networks are biologically inspired systems which convert a set of inputs into a
set of outputs by a network of neurons, where each neuron produces one output
as a function of inputs. A fundamental neuron can be considered as a processor
which makes a simple non linear operation of its inputs producing a single
output.

 

The understanding of
the working of neurons and the pattern of their interconnection can be used to
construct computers for solving real world problems of classification of
patterns and pattern recognition. They are classified by their architecture:
number of layers and topology: connectivity pattern, feedforward  or recurrent.

 

Advantages:

 

Speed of
processing.They do not need
any appropriate knowledge of the system model.They have the
ability to handle situations of incomplete data and information, corrupt
data.They are fault
tolerant.Fast and robust.

 

Disadvantages:

 

Large
dimensionality.

 

Results are
always generated even if the input data are unreasonable.

 

They are not
scalable ie.  once an ANN is trained
to do a certain task ,it is difficult to extend for other tasks without
retraining the neural network.

 

 iii)Fuzzy logic
systems.

Fuzzy logic or fuzzy
systems are logical systems for standardization and formalization of
approximate reasoning. It is similar to human decision making with an ability
to produce exact and accurate solutions from certain or even approximate
information and data.

Fuzzy logic is the way
like which human brain works, and we can use this technology in machines so
that they can perform somewhat like humans. Fuzzification
provides superior expressive power, higher generality and an improved
capability to model complex problems at low or moderate solution cost.

Applications:

Stability analysis and enhancement.Power system controlFault diagnosisSecurity assessmentLoad forecastingReactive power planning and its controlState estimation

Fuzzy logic can be used for designing the physical
components of power systems. They can be used in anything from small circuits
to large mainframes. They can be used to increase the efficiency of the
components used in power systems. As most of the data used in power system
analysis are approximate values and assumptions, fuzzy logic can be of great
use to derive a stable, exact and ambiguity-free output

·        
Replacement
human staff for dangerous and extremely specialized operations, like live
maintenance of high voltage transmission lines, has been a protracted standing
result within the power community.

·        
Operation
in hazardous environments, such as radioactive locations in nuclear plants,
access to tight spaces, such as cable viaducts and cooling pipes, and precise
positioning of measurement equipment.

·        
Knowledgeable
systems use the interface mechanism and information to resolve problems that
cannot be or difficult to be resolved by human talent and intellect.

·        
Results
are permanent and consistent.

·        
Can
be easily documented.

·        
Results
can be easily transferred and reproduced.

·        
Computers
for solving real world problems of classification of patterns and pattern
recognition.

·        
Fuzzification
provides superior expressive power, higher generality and an improved capability
to model.

·        
Complex
problems at low or moderate solution cost.

·        
Stability
analysis and enhancement.

·        
Power
system control.

·        
Fault
diagnosis.

·        
Load
forecasting.

·        
Reactive
power planning and its control.

·        
Operation
of power system like unit commitment, hydro-thermal coordination, economic
dispatch,

·        
Congestion
management, maintenance scheduling, state estimation, load and power flow.

·        
Planning
of power system like generation expansion planning, power system reliability,
transmission expansion planning, reactive power planning.

·        
Control
of power system like voltage control, stability control, power flow control,
load frequency control.

·        
Control
of power plants like fuel cells power plant control, thermal power plant
control.

·        
Automation
of power grid like restoration, management, fault designation, network
security.

·        
Can
be used in anything from small circuits to large mainframes.

·        
Can
be used to increase the efficiency of the components used in power systems.

·        
As
most of the data used in power system analysis are approximate values and
assumptions, fuzzy logic can be of great use to derive a stable, exact and
ambiguity free output.

 

IV. CONCLUSION

Electricity is one of the prime factors for the growth
and determines the value of the society. So, implementation of artificial
intelligence is very important in power system. The main feature of power
systems design and planning is reliability. Conventional techniques don’t
fulfill the probabilistic essence of power systems. This leads to increase in
operating and maintenance costs. A lot of research is
yet to be performed to perceive full advantages of this upcoming technology for
improving the efficiency of electricity market investment, distributed control
and monitoring, efficient system analysis, particularly power systems which use
renewable energy resources for operation

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