Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis
Machine Learning
2024-08-30 v1 Artificial Intelligence
Abstract
This paper introduces a group of novel datasets representing real-time time-series and streaming data of energy prices in New Zealand, sourced from the Electricity Market Information (EMI) website maintained by the New Zealand government. The datasets are intended to address the scarcity of proper datasets for streaming regression learning tasks. We conduct extensive analyses and experiments on these datasets, covering preprocessing techniques, regression tasks, prediction intervals, concept drift detection, and anomaly detection. Our experiments demonstrate the datasets' utility and highlight the challenges and opportunities for future research in energy price forecasting.
Cite
@article{arxiv.2408.16187,
title = {Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis},
author = {Yibin Sun and Heitor Murilo Gomes and Bernhard Pfahringer and Albert Bifet},
journal= {arXiv preprint arXiv:2408.16187},
year = {2024}
}
Comments
12 Pages, 8 figures, short version accepted by PRICAI