Energy Price Forecasting in the Ontario Competitive Power System Market
- 19 February 2004
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Power Systems
- Vol. 19 (1) , 366-374
- https://doi.org/10.1109/tpwrs.2003.821470
Abstract
This paper introduces a method for forecasting energy prices using artificial intelligence methods, such as neural networks and fuzzy logic, and a combination of the two. The new approach is compared with some of the exiting methods. Various factors affecting the market clearing price are investigated. Results for the Ontario electricity market are presented.Keywords
This publication has 15 references indexed in Scilit:
- An integrated neural network method for market clearing price prediction and confidence interval estimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Prediction of system marginal price in the UK Power Pool using neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Forecasting next-day electricity prices by time series modelsIEEE Transactions on Power Systems, 2002
- Market Operations in Electric Power SystemsPublished by Wiley ,2002
- Locational marginal price forecasting in deregulated electricity markets using artificial intelligenceIEE Proceedings - Generation, Transmission and Distribution, 2002
- Power System Restructuring and DeregulationPublished by Wiley ,2001
- Gaming and price spikes in electric power marketsIEEE Transactions on Power Systems, 2001
- Forecasting energy prices in a competitive marketIEEE Computer Applications in Power, 1999
- Electricity price short-term forecasting using artificial neural networksIEEE Transactions on Power Systems, 1999
- Spot Pricing of ElectricityPublished by Springer Nature ,1988