In the deregulated power markets, the electricity market price forecasting is very important for the market participants, managers GenCo, DisCo, retailers, etc. Although, most of researches has achieved good results on the electricity market price forecasting, however, these techniques mostly focus on normal price forecasting and not considering price spikes in the electricity market. In this study, we propose a price interval identification model using neural network, which can generate forecasted price interval, level of spike and associated forecast confidence. The model is tested with the Queensland electricity market data of Australia and promising results are been obtained.
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