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Artificial Intelligence in Power Systems
Presented By,
Ms. Sandhya Kumbhar
Contents
• Introduction
• Need for AI in Power system
• Artificial Intelligence Techniques
• Advantages
• Disadvantages
• Applications
• Conclusion
• References
2
Power Systems and Artificial Intelligence
• An electric power system is a network of electrical
components used to supply, transmit and use electric power.
Power system engineering deals with the generation,
transmission, distribution and utilization of electric power and
other electrical devices.
• Artificial Intelligence is known to be the intelligence exhibited
by machines and software, for example, robots and computer
programs.
• The term is generally used to the developing systems equipped
with the intellectual processes and characteristics of humans,
like ability to think, reason, find the meaning, etc.
3
Need for AI in Power Systems
Power system analysis by conventional techniques becomes
more difficult because of:
(a) Complex, versatile and large amount of information which
is used in calculation, diagnosis and learning.
(b) Increase in the computational time period and accuracy due
to extensive and vast system data handling.
4
Artificial Intelligence Techniques
Three major families of AI techniques are considered to be
applied in modern power system protection
• Expert System Techniques (XPSs),
• Artificial Neural Networks (ANNs),
• Fuzzy logic systems (FL).
5
Expert Systems
• An expert system obtains the
knowledge of a human expert in
a narrow specified domain into
a machine implementable form.
• Expert systems are computer
programs which have proficieny
and competence in a particular
field.
• They are also called knowledge
based or rule based systems.
6
Artificial Neural Netwoks
Artificial neural network 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 input.
7
Fuzzy Logic
Fuzzy logic is the way in
which human brain works, and
we can use this technology in
machines so that they can
perform somewhat like
humans.
It provides expressive power
and higher capability to model
complex problems.
8
Applications
• AI techniques can be used to improve the performance of
transmission line.
• Control of power system like voltage control, stability control,
power flow control, load frequency control is possible.
• Load forecasting.
• Fault diagnosis.
• Stability analysis and enhancement.
• Reactive power planning and its control.
9
Advantages
• AI techniques are permanent and consistent.
• Processing speed is good.
• Easy to document and reproduce.
• They are fast and robust.
• They are fault tolerant.
10
Disadvantages
• AI techniques are unable to learn or adapt for new problems or
situations.
• They have large dimensionality.
• They are not scalable.
11
Application In Power System
Operation Control
1. Discrete control
 Cut load :
Artificial neural networks has the approximation of function mapping functions and
parallel processing capabilities, it has a good adaptability to deal with load control and
real-time, select an appropriate character input describing function mapping of key
issues.
 Power system relay protection :
Fuzzy identification theory contains a large area in the design of relay protection.
Due to the adaptive ability of traditional protection, reaction ability of detection ability is
limited, real-time tracking using the computer, the calculation characteristics of the
running mode of protection device, making fuzzy in artificial intelligent control theory
for the improvement of the computer provides an important method and way to realize
the relay protection device.
12
Contd….
 Continuous control :
Excitation control is an important part of controlling the voltage and reactive
power of the generator. It can maintain the stability of the power system in the
disturbance environment. It is an important real time continuous control system
against disturbance.
13
Conclusion
• The main feature of power system design and planning is
reliability. Conventional techniques don't ful fill the
probabilistic essence of power system. This leads to increase
in operating and maintenance cost. Plenty of research is
performed to utilize the current interest on Artificial
Intelligence for power system applications.
• 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 and particularly
power systems which use renewable energy resources for
operation.
14
References
• Warwick k, Ekwue A. and Aggarwal R.(ed).Artificial
intelligence techniques in power systems.The institution of
Electrical Engineers, London, 1997.
• International Journal of Engineering Intelligent Systems,The
special issue on AI applications to power system protection,
edited by M.M.Saha and B.Kasztenny, vol.5,No.4,December
1997, pp.185-93.
• Artificial Intelligence in Power systems by R.Pasupathi Nath,
V.Nishanth Balaji IOSR Journal of Computer Enginering
(IOSR-JCE) E-ISSN:2278-0661, p-ISSN: 2278-8727.
15
THANK YOU

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Artificial Intelligence in Power System overview

  • 1. Artificial Intelligence in Power Systems Presented By, Ms. Sandhya Kumbhar
  • 2. Contents • Introduction • Need for AI in Power system • Artificial Intelligence Techniques • Advantages • Disadvantages • Applications • Conclusion • References 2
  • 3. Power Systems and Artificial Intelligence • An electric power system is a network of electrical components used to supply, transmit and use electric power. Power system engineering deals with the generation, transmission, distribution and utilization of electric power and other electrical devices. • Artificial Intelligence is known to be the intelligence exhibited by machines and software, for example, robots and computer programs. • The term is generally used to the developing systems equipped with the intellectual processes and characteristics of humans, like ability to think, reason, find the meaning, etc. 3
  • 4. Need for AI in Power Systems Power system analysis by conventional techniques becomes more difficult because of: (a) Complex, versatile and large amount of information which is used in calculation, diagnosis and learning. (b) Increase in the computational time period and accuracy due to extensive and vast system data handling. 4
  • 5. Artificial Intelligence Techniques Three major families of AI techniques are considered to be applied in modern power system protection • Expert System Techniques (XPSs), • Artificial Neural Networks (ANNs), • Fuzzy logic systems (FL). 5
  • 6. Expert Systems • An expert system obtains the knowledge of a human expert in a narrow specified domain into a machine implementable form. • Expert systems are computer programs which have proficieny and competence in a particular field. • They are also called knowledge based or rule based systems. 6
  • 7. Artificial Neural Netwoks Artificial neural network 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 input. 7
  • 8. Fuzzy Logic Fuzzy logic is the way in which human brain works, and we can use this technology in machines so that they can perform somewhat like humans. It provides expressive power and higher capability to model complex problems. 8
  • 9. Applications • AI techniques can be used to improve the performance of transmission line. • Control of power system like voltage control, stability control, power flow control, load frequency control is possible. • Load forecasting. • Fault diagnosis. • Stability analysis and enhancement. • Reactive power planning and its control. 9
  • 10. Advantages • AI techniques are permanent and consistent. • Processing speed is good. • Easy to document and reproduce. • They are fast and robust. • They are fault tolerant. 10
  • 11. Disadvantages • AI techniques are unable to learn or adapt for new problems or situations. • They have large dimensionality. • They are not scalable. 11
  • 12. Application In Power System Operation Control 1. Discrete control  Cut load : Artificial neural networks has the approximation of function mapping functions and parallel processing capabilities, it has a good adaptability to deal with load control and real-time, select an appropriate character input describing function mapping of key issues.  Power system relay protection : Fuzzy identification theory contains a large area in the design of relay protection. Due to the adaptive ability of traditional protection, reaction ability of detection ability is limited, real-time tracking using the computer, the calculation characteristics of the running mode of protection device, making fuzzy in artificial intelligent control theory for the improvement of the computer provides an important method and way to realize the relay protection device. 12
  • 13. Contd….  Continuous control : Excitation control is an important part of controlling the voltage and reactive power of the generator. It can maintain the stability of the power system in the disturbance environment. It is an important real time continuous control system against disturbance. 13
  • 14. Conclusion • The main feature of power system design and planning is reliability. Conventional techniques don't ful fill the probabilistic essence of power system. This leads to increase in operating and maintenance cost. Plenty of research is performed to utilize the current interest on Artificial Intelligence for power system applications. • 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 and particularly power systems which use renewable energy resources for operation. 14
  • 15. References • Warwick k, Ekwue A. and Aggarwal R.(ed).Artificial intelligence techniques in power systems.The institution of Electrical Engineers, London, 1997. • International Journal of Engineering Intelligent Systems,The special issue on AI applications to power system protection, edited by M.M.Saha and B.Kasztenny, vol.5,No.4,December 1997, pp.185-93. • Artificial Intelligence in Power systems by R.Pasupathi Nath, V.Nishanth Balaji IOSR Journal of Computer Enginering (IOSR-JCE) E-ISSN:2278-0661, p-ISSN: 2278-8727. 15