Big data analytics of smart meter data using Adaptive Neuro Fuzzy Inference System (ANFIS)

The ever increasing human population and the associated demand for electricity have challenged the power sector to modernize its equipment and operations. This renovation activity has made the existing grid to incorporate Information and Communication Technologies (ICT). Installation of Smart Meter is one of the significant changes due to developments in the power sector that establishes two-way communication between the Utility and the consumers. The Smart meters collect data at high velocity leading to tremendously huge volume of data and have been classified as Big Data. Uncovering useful information from these Smart Meter data is a Big Data challenge. In this paper, Smart Meter data is used to forecast the average electricity load for every hour on daily basis. The proposed method uses Adaptive Neuro Fuzzy Inference System (ANFIS) to predict the load ahead of 24 hours from present day meter readings. The experimental results are promising with the overall prediction accuracy of 84.02%.

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