Fault identification based on artificial immunological systems

The growing tendency in the number of distributed generation units, directly connected at the distribution level, inevitably brings a number of new challenges. One of the effects is that this new topology may influence the performance of analysis methods and techniques that were based on traditional systems. Fault location methods in distribution systems are examples of how inserting of new generation sources can change the efficiency of these tools. Considering that fault location is a fundamental step to help distribution companies to maintain reliability indices within acceptable margins, this work presents a method applicable to both traditional systems and systems with the presence of distributed generators. In order to achieve this goal, a methodology was developed based on artificial immunological systems technique, which is generally used to complex problems-solving. The methodology evaluated considering several scenarios in the test system and presented a satisfactory performance, being able to estimate characteristics such as location, fault type and fault resistance in an efficient way.