Genetic Algorithms (GAs) based method to improve the reliability and power quality of distribution systems using network reconfiguration. Two new objective functions are formulated to address power quality and reliability issues for the reconfiguration problem. Various power quality and reliability objectives such as feeder power loss, system’s node voltage deviation, system’s average interruption frequency index, system’s average interruption unavailability index and energy not supplied are transformed into a single objective function. This single objective problem is then solved using the GA-based method. The effectiveness of the proposed objective functions has been investigated on two different standard test distribution systems. Application results are promising when compared with other existing method.

Genetic Algorithms (GAs) based method to improve the reliability and power quality of distribution systems using network reconfiguration. Two new objective functions are formulated to address power quality and reliability issues for the reconfiguration problem. Various power quality and reliability objectives such as feeder power loss, system’s node voltage deviation, system’s average interruption frequency index, system’s average interruption unavailability index and energy not supplied are transformed into a single objective function. This single objective problem is then solved using the GA-based method. The effectiveness of the proposed objective functions has been investigated on two different standard test distribution systems. Application results are promising when compared with other existing method.

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