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

arXiv: https://arxiv.org/abs/2408.16187 · HTML: https://mlsanity.com/paper/2408.16187/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 21 references that are in the map.
- First posted on arXiv 29 Aug 2024.

## Builds on (most cited first, 1 of 1)

- [River: machine learning for streaming data in Python](https://mlsanity.com/paper/2012.04740/) (2020)

## Built on by (most cited first, 1 of 1)

- [On Imbalanced Regression with Hoeffding Trees](https://mlsanity.com/paper/2602.22101/) (2026)

## Abstract (arXiv)

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.