ARTIFICIAL INTELLIGENCE SUBSTATION CONTROLLER

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Controlling a substation by a fuzzy controller speeds up response time diminishes up the possibility of risks normally related to human operations. The automation of electric substation is an area under constant development Our research has focused on, the Selection of the magnitude to be controlled, Definition and implementation of the soft techniques, Elaboration of a programming tool to execute the control operations. it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status. The status of the circuit breakers can be control by using a knowledge base that relates some of the operation magnitudes, mixing status variables with time variables and fuzzy sets .The number of necessary magnitudes to a supervise and to control a substation can be very high in the present research work, many magnitudes were not included .To avoid the extensive number of required rules nevertheless , controlling a substation by a fuzzy controller has the advantage that it can speed up the response time and diminish the possibility of risks normally related to human operations.

AI AUTOMATES SUBSTATION CONTROL

Introduction

Electric substations are facilities in charge of the voltage transformation to provide safe and effective energy to the consumers. This energy supply has to be carried out with sufficient quality and should guarantee the equipment security. The associated cost to ensure quality and security during the supply in substations is high. Automatic mechanisms are generally used in greater or lesser scale, although they mostly operate according to an individual control and protection logic related with the equipment itself and not with the topology of the whole substation in a given moment.

The automation of electric substation is an area under constant development. Nevertheless, the control of a substation is a very complex task due to the great number of related problems and, therefore, the decision variables that can influence the substation performance. Under such circumstances, the use of learning control systems can be very useful.

Many papers on applications of artificial intelligence (AI) techniques to power system have been published in the last year. The difficulties associated with the application of this technique include:

1. Selection of the magnitude to be controlled

2. Definition and implementation of the soft techniques

3. Elaboration of a programming tool to execute the control operations

4. Selection, acquisition and installation of the measurement and control equipment

5. Interface with this equipment and

6. Applications of the controlling technique in existent substations.

Our research has focused on the first three points, and the interest of the present work is to expose the obtained result and to present them for discussion. The objective is to show that it is possible to control the status of circuit breakers (CB) in a substation making use of a knowledge, mixing status variables with time variables and fuzzy sets.

Even when all the magnitudes to be controlled cannot be included in the analysis (mostly due to the great number of measurements and status variables of the substation and, therefore, to the rules that would be required by the controller), it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status.

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