Electricity Consumption Prediction via WaveNet+t

Document Type

Conference Proceeding

Publication Date

1-1-2023

Abstract

Electricity consumption prediction is essential for load management to prevent shortage and excess supply. Different methods ranging from statistical methods, machine learning, and deep learning models were developed to predict electricity consumption. In this study, a probabilistic model -WaveNet+t was developed to provide the confidence interval rather than the deterministic estimate. WaveNet+t model integrates dilated causal convolutional neural networks with residual networks to extract the temporal, long/short term patterns from the time series data. The testing results based on a real dataset from 370 clients showed that WaveNet+t model has a lower CRPSsum value than the benchmark models.

Publication Source (Journal or Book title)

Proceedings - 2023 IEEE Conference on Artificial Intelligence, CAI 2023

First Page

59

Last Page

60

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