Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis

Yibin Sun, Heitor Murilo Gomes, Bernhard Pfahringer, Albert Bifet
8/29/2024
cs.LGcs.AI

No official code found. Best implementation: Anonymous-1-2-3-4/NewZealandEnergyPrices (0 stars, last commit 2024-06-24).

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.

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Code Implementations(1)

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Cite this paper

@article{sun2024realtime,
  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},
  year   = {2024},
  eprint = {2408.16187},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.16187v1}
}

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