Recently, wireless sensor networks (WSNs) have gained great attention from the research community for various smart grid\napplications, including advanced metering infrastructure (AMI), power outage detection, distribution automation, towers and\npoles monitoring, line fault diagnostics, power fraud detection, and underground cable system monitoring. However, multipath,\nfading, environmental noise, and obstructions in harsh smart grid environments make reliable communication a challenging\ntask for wireless-sensor-network- (WSN-) based smart grid applications. To overcome varying link conditions in smart grid\nenvironments, sensor nodes must be capable of estimating link quality dynamically and reliably. In this paper, the performance of\nthe state-of-the-art link-quality estimation methods is investigated for different smart power grid environments, such as outdoor\nsubstation, underground network transformer vault, and main power control room, in terms of packet delivery ratio, average\nnumber of packet retransmissions, average number of parent changes, average number of hops, and average communication\ndelay. In addition, main smart grid characteristics and potential applications of WSNs in smart grid have been introduced along\nwith the related technical challenges. Overall, our performance evaluations show that the link-quality estimators, called Expected\nTransmission Count (ETX) and four-bit, show the best performance in harsh smart grid environments.
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