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Bridging an energy system model with an ensemble deep-learning approach for electricity price forecasting

https://doi.org/10.2139/ssrn.6367403
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Outgoing claims: the papers this work cites, builds on, or argues with.

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A bat optimized neural network and wavelet transform approach for short-term price forecasting
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Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms
inferredcites →https://doi.org/10.1016/j.enconman.2015.08.025openalex-snapshot
Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method
inferredcites →https://doi.org/10.1016/j.eneco.2005.09.008openalex-snapshot
Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters
inferredcites →https://doi.org/10.1016/j.eneco.2006.05.012openalex-snapshot
A structural model for electricity prices with spikes: Measurement of spike risk and optimal policies for hydropower plant operation
inferredcites →https://doi.org/10.1016/j.eneco.2008.02.004openalex-snapshot
Intra-day and regime-switching dynamics in electricity price formation
inferredcites →https://doi.org/10.1016/j.eneco.2013.02.004openalex-snapshot
The market value of variable renewables
inferredcites →https://doi.org/10.1016/j.enpol.2008.03.035openalex-snapshot
The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany
inferredcites →https://doi.org/10.1016/j.enpol.2012.06.028openalex-snapshot
Forecasting Nord Pool day-ahead prices with an autoregressive model
inferredcites →https://doi.org/10.1016/j.epsr.2018.10.034openalex-snapshot
Electricity price forecasting in the short term hybridising fundamental and econometric modelling
inferredcites →https://doi.org/10.1016/j.ijforecast.2004.12.005openalex-snapshot
Forecasting electricity prices for a day-ahead pool-based electric energy market
inferredcites →https://doi.org/10.1016/j.ijforecast.2008.09.008openalex-snapshot
Forecasting electricity prices: The impact of fundamentals and time-varying coefficients
inferredcites →https://doi.org/10.1016/j.ijforecast.2011.02.019openalex-snapshot
Forecasting spikes in electricity prices
inferredcites →https://doi.org/10.1016/j.ijforecast.2014.08.008openalex-snapshot
Electricity price forecasting: A review of the state-of-the-art with a look into the future
inferredcites →https://doi.org/10.1016/j.ijforecast.2015.06.002openalex-snapshot
Probabilistic forecasting of hourly electricity prices in the medium-term using spatial interpolation techniques
inferredcites →https://doi.org/10.1016/j.ijforecast.2015.11.008openalex-snapshot
A hybrid model for GEFCom2014 probabilistic electricity price forecasting
inferredcites →https://doi.org/10.1016/j.ijforecast.2019.11.002openalex-snapshot
Comparing the forecasting performances of linear models for electricity prices with high RES penetration
inferredcites →https://doi.org/10.1016/j.ijforecast.2022.09.004openalex-snapshot
LASSO principal component averaging: A fully automated approach for point forecast pooling
inferredcites →https://doi.org/10.1016/j.rser.2017.05.234openalex-snapshot
Recent advances in electricity price forecasting: A review of probabilistic forecasting
inferredcites →https://doi.org/10.1109/5.823996openalex-snapshot
Forecasting loads and prices in competitive power markets
inferredcites →https://doi.org/10.1109/msp.2012.2205597openalex-snapshot
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
inferredcites →https://doi.org/10.1109/tpwrs.2002.1007902openalex-snapshot
Forecasting next-day electricity prices by time series models
inferredcites →https://doi.org/10.1109/tpwrs.2011.2167689openalex-snapshot
Forecasting Power Prices Using a Hybrid Fundamental-Econometric Model
inferredcites →https://doi.org/10.1111/j.1467-6451.2006.00297.xopenalex-snapshot
QUANTIFYING MARKET POWER IN THE GERMAN WHOLESALE ELECTRICITY MARKET USING A DYNAMIC MULTI‐REGIONAL DISPATCH MODEL *
inferredcites →https://doi.org/10.1111/j.2517-6161.1996.tb02080.xopenalex-snapshot
Regression Shrinkage and Selection Via the Lasso
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
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A Fast Learning Algorithm for Deep Belief Nets
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Measuring Market Inefficiencies in California's Restructured Wholesale Electricity Market

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inferred← citeshttps://doi.org/10.3390/en19133171openalex-snapshot
Determinants of Energy Prices in the European Union for the Period 2017–2025—An Econometric Analysis
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