Electricity price forecasting with confidence-interval estimation through an extended ARIMA approach

By M. Zhou, Zheng Yan, Y. Ni, Gengyin Li, Y. Nie. 2006

139 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/cefa03862cfb9a553bb8fcd56db5c93f53c1c813

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Jakub Nowotarski
2. Rafal Weron
3. Lalit Mohan Saini
4. Sanjeev Kumar Aggarwal
5. Ashwani Kumar
6. Florian Ziel
7. Bartosz Uniejewski
8. Grzegorz Marcjasz

In Management Science and Operations Research

1. Rafal Weron
2. Jakub Nowotarski
3. Lalit Mohan Saini
4. Sanjeev Kumar Aggarwal
5. Ashwani Kumar
6. Florian Ziel

Citations in the corpus

• Recent advances in electricity price forecasting: A review of probabilistic forecasting (2016, methodology): “[45] compute the PIs for SARIMA models fitted to California power market prices, but they use them only as a trigger to stop an iterative SARIMA estimation scheme and do not evaluate nor analyze the PIs.”
• Electricity price forecasting in deregulated markets: A review and evaluation (2009, background): “market 13 [13,17,19,23,28,30,31,33, 34 ,37,38,40,45]”