ARTIFICIAL INTELLIGENCE APPLICATION TO POWER SYSTEM PROTECTION
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INTRODUCTION:

The microprocessor technology brings unquestionable improvements of the protection relays- criteria signals are estimated in a shorter time; input signals are filtered-out more precisely; it is easy to apply sophisticated corrections; the hardware is standardized and may communicate with other protection and control systems; relays are capable of self-monitoring. All this, however, did not make a major breakthrough in power system protection as far as security, dependability and speed of operation are considered.


PROBLEMS IN POWER SYSTEM PROTECTION:

The problems result mainly from the trade-off between the security demand (no false tripping), and the speed of operation and the dependability (no missing operations) requirements. The more secure is the relay (both the algorithm and its particular settings), the more it tends to misoperate or operate slowly. And vice versa, the faster is the relay, the more it tends to operate falsely.



ARTIFICIAL INTELLIGENCE METHODS:

AI is a subfield of computer science that investigates how the though and action of human beings can be mimicked by machines [5]. Both the numeric, non-numeric and symbolic computations are included in the area of AI. The mimicking of intelligence includes not only the ability to make rational decisions, but also to deal with missing data, adapt to existing situations and improve itself in the long time horizon based on the accumulated experience.
Three major families of AI techniques are considered to be applied in modern power system protection are.


EXPERT SYSTEMS:

The first expert systems included a few heuristic rules based on the expert’s experience. In such systems, the knowledge takes the form of so called production rules written using the If... then... syntax (knowledge base). The system includes also the facts which generally describe the domain and the state of the problem to be solved (data base). A generic inference engine uses the facts and the rules to deduce new facts which allow the firing of other rules


ARTIFICIAL NEURAL NETWORKS:
The ANNs are very different from expert systems since they do not need a knowledge base to work. Instead, they have to be trained with numerous actual cases. An ANN is a set of elementary neurons which are connected together in different architectures organized in layers what is biologically inspired .