Locational marginal price forecasting in deregulated electricity markets using artificial intelligence

By Y.-y. Hong, C. Hsiao. 2002

161 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

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Citations in the corpus

Appliance Commitment for Household Load Scheduling (2011, background): “In our example, the forecasted price signal, , is obtained by adding a white noise, , (which follows a normal distribution) to the actual price signal, as in (13) (13) A daily mean error of 10% is assumed in this paper, which is consistent with the forecasting accuracy reported by Contreras et al. [”
Application of Public-Domain Market Information to Forecast Ontario's Wholesale Electricity Prices (2006, methodology): “Among those, artificial intelligence based methods [1], [2] , [3], [4], [5], input/output hidden Markov models [6], wavel et”
An Adaptive Wavelet Neural Network-Based Energy Price Forecasting in Electricity Markets (2008, methodology): “In [16], recurrent neural network (RNN) has been applied for LMP forecasting.”
Short-term electricity prices forecasting in a competitive market: A neural network approach (2007, methodology): “In particular, neural networks approaches, that have been widely used for load forecasting with successful performance [16,17], are now used to predict electricity prices [18–24], using Fourier and Hartley transforms as filters to the price data [25], using extended Kalman filter [26] or combined wi”
A Novel Approach to Forecast Electricity Price for PJM Using Neural Network and Similar Days Method (2007, methodology): “…the largest competitive wholesale electricity market in the world is coordinated by an independent system operator (ISO) who ensure a secured, economical and efﬁcient operation as well as determining all locational marginal price (LMP) according to voluntary bids and bilateral transactions [10].”
Electricity price forecasting in deregulated markets: A review and evaluation (2009, methodology): “In [60], a Fuzzy-c-means (FCM) and RNN based method has been used.”