Fault Location in the Smart Grids Context Based on an Evolutionary Algorithm

Abstract

Advances in communications technologies, data processing and storage benefit power distribution utilities, allowing them to enhance the use of data provided by field monitors, remote-controlled switches and smart meters. Today, utilities can gather a variety of data regarding the power grid operation, such as customers demands, alarms and measurements, taking steps toward the Smart Grids. An interoperability bus (IB) can provide those data to any other corporate system, allowing one to develop power grid operational tools executed by distribution management systems (DMS). In this context, the present paper proposes a new fault location methodology for real power distribution networks, that resorts to data provided by an IB, such as alarms from protection relays and fault indicator sensors, and measurements from power quality monitors and smart meters. The methodology can be implemented in the DMS level and is based on evolutionary strategies, which is responsible for estimating the exact location of faults in the MV level of power distribution networks. The effect of the availability of data as alarms and measurements is assessed, considering a real 319-km-long power distribution feeder. Test results obtained from 113 short-circuit cases have indicated that the locating error is inferior to 2.9%.