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Abstract
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Power distribution networks (PDNs) has played a crucial role in expediting the transition towards cleaner and better distributed energy sources. Owing to the daily increase
in using electrical power, the need for a sustainable, reliable, and efficient network, which
can respond to the needs of consumers, is felt more than before. Therefore, smart network
must be used. In smart distribution networks, a special measuring equipment called micro phasor measurement unit (mPMU) must be utilized to simultaneously and accurately
measure voltage and current phases to control and monitor the distribution network. Due
to technical and economical issues, it is not possible to use mPMU on all distribution network buses. On the other hand, faults may occur in electrical networks that cause hazardous
transients, equipment failure, and power outage. A fast and accurate fault location brings
about network quick restoration and thus increases reliability and customer satisfaction. Besides, Nowadays, more and more distributed generations (DGs) are used in PDNs which
complicates the automatic fault location.
This research begins with proposing a new algorithm for optimal mPMU placement in
PDN. A new method is presented to optimize the number of mPMU in the PDN based on
the ant colony algorithm, the extracted heuristic information from the network and sudounobservable bus concept, while guaranteeing the network observability. Then, an accurate impedance-based method is presented to determine the fault location for smart PDN
in the presence of DGs. In addition, phase domain equations of distributed line parameters
are used to enhance the accuracy of fault location. Two types of networks are considered.
The first type of network is assumed to be fully observable with mPMU and in the second
type, there are only a few mPMUs with data loggers on the rest nodes. Load impedances of
all nodes are estimated using pre-fault recorded information by present mPMUs and data
loggers. The proposed algo
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