@InProceedings{vats2020mitigating,
author="Vats, Vibhas Kumar
and Rai, Sneha
and De, Suddhasil
and De, Mala",
editor="Nath, Vijay
and Mandal, J. K.",
title="Mitigating Effect of Communication Link Failure in Smart Meter-Based Load Forecasting",
booktitle="Nanoelectronics, Circuits and Communication Systems",
year="2020",
publisher="Springer Singapore",
address="Singapore",
pages="289--300",
abstract="With the ever-increasing number of smart meter installations, an enormous amount of power consumption data is collected by these meters in real time. Availability of this large amount of power consumption data has changed the way power system analyses were done traditionally; one such area being load forecasting. The load forecasting is now largely data-driven and hence failure to receive data from the smart meters lead to forecasting errors. The present paper targets to solve this problem by introducing a novel classification-based load forecasting methodology that enables day-ahead load predication in case of missing data due to communication link failure. In this method, the loads are classified or clustered in sub-classes based on amount of consumption and then day-ahead forecasting is done using this clustered load data. The proposed methodology is demonstrated using the data collected in a practical smart system installed at NIT Patna campus.",
isbn="978-981-15-2854-5"
}