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Electricity price forecasting: A review of the state-of-the-art with a look into the future
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Cited by:
- Maryniak, Paweł & Trück, Stefan & Weron, Rafał, 2019. "Carbon pricing and electricity markets — The case of the Australian Clean Energy Bill," Energy Economics, Elsevier, vol. 79(C), pages 45-58.
- Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
- Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
- Loutfi, Ahmad Amine & Sun, Mengtao & Loutfi, Ijlal & Solibakke, Per Bjarte, 2022. "Empirical study of day-ahead electricity spot-price forecasting: Insights into a novel loss function for training neural networks," Applied Energy, Elsevier, vol. 319(C).
- Smyl, Slawek, 2020. "A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting," International Journal of Forecasting, Elsevier, vol. 36(1), pages 75-85.
- Mendes, Carla & Staffell, Iain & Green, Richard, 2024. "EuroMod: Modelling European power markets with improved price granularity," Energy Economics, Elsevier, vol. 131(C).
- Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
- Đukan, Mak & Kitzing, Lena, 2023. "A bigger bang for the buck: The impact of risk reduction on renewable energy support payments in Europe," Energy Policy, Elsevier, vol. 173(C).
- repec:dui:wpaper:1502 is not listed on IDEAS
- Sajjad Khan & Shahzad Aslam & Iqra Mustafa & Sheraz Aslam, 2021. "Short-Term Electricity Price Forecasting by Employing Ensemble Empirical Mode Decomposition and Extreme Learning Machine," Forecasting, MDPI, vol. 3(3), pages 1-18, June.
- Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
- Tim Janke & Florian Steinke, 2019. "Forecasting the Price Distribution of Continuous Intraday Electricity Trading," Energies, MDPI, vol. 12(22), pages 1-14, November.
- Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2016. "Day-ahead electricity price forecasting via the application of artificial neural network based models," Applied Energy, Elsevier, vol. 172(C), pages 132-151.
- Clements, A.E. & Hurn, A.S. & Li, Z., 2016. "Strategic bidding and rebidding in electricity markets," Energy Economics, Elsevier, vol. 59(C), pages 24-36.
- Woo, C.K. & Liu, Y. & Zarnikau, J. & Shiu, A. & Luo, X. & Kahrl, F., 2018. "Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016," Applied Energy, Elsevier, vol. 222(C), pages 460-474.
- Xiaoming Xie & Meiping Li & Du Zhang, 2021. "A Multiscale Electricity Price Forecasting Model Based on Tensor Fusion and Deep Learning," Energies, MDPI, vol. 14(21), pages 1-14, November.
- Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
- Mukherjee, Paramita & Coondoo, Dipankor & Lahiri, Poulomi, 2019. "Forecasting Hourly Prices in Indian Spot Electricity Market," MPRA Paper 103161, University Library of Munich, Germany.
- Nowotarski, Jakub & Weron, Rafał, 2018.
"Recent advances in electricity price forecasting: A review of probabilistic forecasting,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
- Jakub Nowotarski & Rafal Weron, 2016. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports HSC/16/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Figueiredo, Nuno Carvalho & Silva, Patrícia Pereira da & Bunn, Derek, 2016. "Weather and market specificities in the regional transmission of renewable energy price effects," Energy, Elsevier, vol. 114(C), pages 188-200.
- de Hoog, Julian & Abdulla, Khalid, 2019. "Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1451-1459.
- Lago, Jesus & De Ridder, Fjo & Vrancx, Peter & De Schutter, Bart, 2018. "Forecasting day-ahead electricity prices in Europe: The importance of considering market integration," Applied Energy, Elsevier, vol. 211(C), pages 890-903.
- Fanelli, Viviana & Maddalena, Lucia & Musti, Silvana, 2016. "Modelling electricity futures prices using seasonal path-dependent volatility," Applied Energy, Elsevier, vol. 173(C), pages 92-102.
- Arne Vogler & Florian Ziel, "undated". "On The Evaluation Of Binary Event Probability Predictions In Electricity Price Forecasting," EWL Working Papers 1911, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
- Jannik Schütz Roungkvist & Peter Enevoldsen & George Xydis, 2020. "High-Resolution Electricity Spot Price Forecast for the Danish Power Market," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
- Bennedsen, Mikkel, 2017. "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, vol. 63(C), pages 301-313.
- Balagula, Yuri, 2020. "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 89-101.
- Monika Zielińska-Sitkiewicz & Mariola Chrzanowska & Konrad Furmańczyk & Kacper Paczutkowski, 2021. "Analysis of Electricity Consumption in Poland Using Prediction Models and Neural Networks," Energies, MDPI, vol. 14(20), pages 1-21, October.
- Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
- Katarzyna Maciejowska, 2022. "A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets," Papers 2205.00975, arXiv.org.
- Liyang Tang, 2020. "Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment," Papers 2005.08735, arXiv.org.
- Michał Narajewski, 2022. "Probabilistic Forecasting of German Electricity Imbalance Prices," Energies, MDPI, vol. 15(14), pages 1-17, July.
- Zhang, Hanyu & Assereto, Martina & Byrne, Julie, 2023. "Deferring real options with solar renewable energy certificates," Global Finance Journal, Elsevier, vol. 55(C).
- Alasseur, C. & Féron, O., 2018. "Structural price model for coupled electricity markets," Energy Economics, Elsevier, vol. 75(C), pages 104-119.
- Ekaterina Abramova & Derek Bunn, 2021. "Optimal Daily Trading of Battery Operations Using Arbitrage Spreads," Energies, MDPI, vol. 14(16), pages 1-23, August.
- Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021.
"Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark,"
Applied Energy, Elsevier, vol. 293(C).
- Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
- Carlo Fezzi & Valeria Fanghella, 2020. "Real-time estimation of the short-run impact of COVID-19 on economic activity using electricity market data," Papers 2007.03477, arXiv.org.
- Miguel Ángel Rodríguez López & Diego Rodríguez Rodríguez, 2024. "La aplicación de datos masivos en economía de la energía: una revisión," Working Papers 2024-08, FEDEA.
- Jesus Lago & Fjo De Ridder & Peter Vrancx & Bart De Schutter, 2017. "Forecasting day-ahead electricity prices in Europe: the importance of considering market integration," Papers 1708.07061, arXiv.org, revised Dec 2017.
- Kempitiya, Thimal & Sierla, Seppo & De Silva, Daswin & Yli-Ojanperä, Matti & Alahakoon, Damminda & Vyatkin, Valeriy, 2020. "An Artificial Intelligence framework for bidding optimization with uncertainty in multiple frequency reserve markets," Applied Energy, Elsevier, vol. 280(C).
- Franki, Vladimir & Višković, Alfredo, 2015. "Energy security, policy and technology in South East Europe: Presenting and applying an energy security index to Croatia," Energy, Elsevier, vol. 90(P1), pages 494-507.
- Dudek, Grzegorz, 2016. "Multilayer perceptron for GEFCom2014 probabilistic electricity price forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1057-1060.
- Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023.
"Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
- Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
- F. Cordoni, 2020. "A comparison of modern deep neural network architectures for energy spot price forecasting," Digital Finance, Springer, vol. 2(3), pages 189-210, December.
- Boonstra, Boris C. & Oosterlee, Cornelis W., 2021.
"Valuation of electricity storage contracts using the COS method,"
Applied Mathematics and Computation, Elsevier, vol. 410(C).
- Boris C. Boonstra & Cornelis W. Oosterlee, 2021. "Valuation of electricity storage contracts using the COS method," Papers 2101.02917, arXiv.org.
- Д.О. Афанасьев1 & * & Е.А. Федорова2 & **, 2019. "Краткосрочное Прогнозирование Цены Электроэнергии На Российском Рынке С Использованием Класса Моделей Scarx," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(1), pages 68-84, январь.
- Eduardo Caro & Jesús Juan, 2020. "Short-Term Load Forecasting for Spanish Insular Electric Systems," Energies, MDPI, vol. 13(14), pages 1-26, July.
- Saez, Yago & Mochon, Asuncion & Corona, Luis & Isasi, Pedro, 2019. "Integration in the European electricity market: A machine learning-based convergence analysis for the Central Western Europe region," Energy Policy, Elsevier, vol. 132(C), pages 549-566.
- Hajar Nasrazadani & Maria Pilar Mu oz Gracia, 2017. "Comparing Iranian and Spanish Electricity Markets with Nonlinear Time Series," International Journal of Energy Economics and Policy, Econjournals, vol. 7(2), pages 262-286.
- Gianfreda, Angelica & Scandolo, Giacomo, 2023. "A worldwide analysis of the energy regulatory tasks and activities through the lenses of entropy and unsupervised statistical learning," Energy, Elsevier, vol. 271(C).
- Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
- Andr s Oviedo-G mez & Sandra Milena Londo o-Hern ndez & Diego Fernando Manotas-Duque, 2021. "Electricity Price Fundamentals in Hydrothermal Power Generation Markets Using Machine Learning and Quantile Regression Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 66-77.
- Javier Pórtoles & Camino González & Javier M. Moguerza, 2018. "Electricity Price Forecasting with Dynamic Trees: A Benchmark Against the Random Forest Approach," Energies, MDPI, vol. 11(6), pages 1-21, June.
- Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023.
"Forecasting electricity prices with expert, linear, and nonlinear models,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
- Anna Gloria Billé & Angelica Gianfreda & Filippo Del Grosso & Francesco Ravazzolo, 2021. "Forecasting Electricity Prices with Expert, Linear and Non-Linear Models," Working Paper series 21-20, Rimini Centre for Economic Analysis.
- Micha{l} Narajewski & Florian Ziel, 2021. "Optimal bidding in hourly and quarter-hourly electricity price auctions: trading large volumes of power with market impact and transaction costs," Papers 2104.14204, arXiv.org, revised Feb 2022.
- João Pedro Pereira & Vasco Pesquita & Paulo M. M. Rodrigues & António Rua, 2019.
"Market integration and the persistence of electricity prices,"
Empirical Economics, Springer, vol. 57(5), pages 1495-1514, November.
- António Rua & Paulo M.M. Rodrigues & João Pedro Pereira, 2016. "Market integration and the persistence of electricity prices," Working Papers w201609, Banco de Portugal, Economics and Research Department.
- Wei Wei & Asger Lunde, 2023. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1647-1679.
- Uniejewski, Bartosz & Maciejowska, Katarzyna, 2023.
"LASSO principal component averaging: A fully automated approach for point forecast pooling,"
International Journal of Forecasting, Elsevier, vol. 39(4), pages 1839-1852.
- Bartosz Uniejewski & Katarzyna Maciejowska, 2022. "LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling," Papers 2207.04794, arXiv.org.
- Agustín A. Sánchez de la Nieta & Virginia González & Javier Contreras, 2016. "Portfolio Decision of Short-Term Electricity Forecasted Prices through Stochastic Programming," Energies, MDPI, vol. 9(12), pages 1-19, December.
- repec:hum:wpaper:sfb649dp2016-035 is not listed on IDEAS
- Jujie Wang & Yanfeng Wang & Yaning Li, 2018. "A Novel Hybrid Strategy Using Three-Phase Feature Extraction and a Weighted Regularized Extreme Learning Machine for Multi-Step Ahead Wind Speed Prediction," Energies, MDPI, vol. 11(2), pages 1-33, February.
- Facchini, Angelo & Rubino, Alessandro & Caldarelli, Guido & Di Liddo, Giuseppe, 2019. "Changes to Gate Closure and its impact on wholesale electricity prices: The case of the UK," Energy Policy, Elsevier, vol. 125(C), pages 110-121.
- Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
- Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015.
"Forecasting day-ahead electricity prices: Utilizing hourly prices,"
Energy Economics, Elsevier, vol. 50(C), pages 227-239.
- Eran Raviv & Kees E. Bouwman & Dick van Dijk, 2013. "Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices," Tinbergen Institute Discussion Papers 13-068/III, Tinbergen Institute.
- Helder Sebastião & Pedro Godinho & Sjur Westgaard, 2020.
"Using Machine Learning to Profit on the Risk Premium of the Nordic Electricity Futures,"
Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 67(4), pages 1-17, December.
- Helder Sebastião & Pedro Godinho & Sjur Westgaard, 2020. "Using Machine Learning to Profit on the Risk Premium of the Nordic Electricity Futures," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 67(si), pages 1-17, December.
- Gerardo J. Osório & Jorge N. D. L. Gonçalves & Juan M. Lujano-Rojas & João P. S. Catalão, 2016. "Enhanced Forecasting Approach for Electricity Market Prices and Wind Power Data Series in the Short-Term," Energies, MDPI, vol. 9(9), pages 1-19, August.
- Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
- Yan, Guan & Trück, Stefan, 2020. "A dynamic network analysis of spot electricity prices in the Australian national electricity market," Energy Economics, Elsevier, vol. 92(C).
- Scheben, Heike & Hufendiek, Kai, 2023. "Modelling power prices in markets with high shares of renewable energies and storages—The Norwegian example," Energy, Elsevier, vol. 267(C).
- Kamal Chapagain & Somsak Kittipiyakul, 2018. "Performance Analysis of Short-Term Electricity Demand with Atmospheric Variables," Energies, MDPI, vol. 11(4), pages 1-34, April.
- Heydari, Azim & Majidi Nezhad, Meysam & Pirshayan, Elmira & Astiaso Garcia, Davide & Keynia, Farshid & De Santoli, Livio, 2020. "Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm," Applied Energy, Elsevier, vol. 277(C).
- Georg Wolff & Stefan Feuerriegel, 2019. "Emissions Trading System of the European Union: Emission Allowances and EPEX Electricity Prices in Phase III," Energies, MDPI, vol. 12(15), pages 1-15, July.
- Radhakrishnan Angamuthu Chinnathambi & Anupam Mukherjee & Mitch Campion & Hossein Salehfar & Timothy M. Hansen & Jeremy Lin & Prakash Ranganathan, 2018. "A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets," Forecasting, MDPI, vol. 1(1), pages 1-21, July.
- Marwan, Marwan, 2020. "The impact of probability of electricity price spike and outside temperature to define total expected cost for air conditioning," Energy, Elsevier, vol. 195(C).
- Agrawal, Rahul Kumar & Muchahary, Frankle & Tripathi, Madan Mohan, 2019. "Ensemble of relevance vector machines and boosted trees for electricity price forecasting," Applied Energy, Elsevier, vol. 250(C), pages 540-548.
- Knaut, Andreas & Paschmann, Martin, 2017. "Price Volatility in Commodity Markets with Restricted Participation," EWI Working Papers 2017-2, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
- Daniel Manfre Jaimes & Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2023. "A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes," Forecasting, MDPI, vol. 5(3), pages 1-23, July.
- Pawel Maryniak & Rafal Weron, 2014. "Forecasting the occurrence of electricity price spikes in the UK power market," HSC Research Reports HSC/14/11, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
- Seong, Byeongchan & Lee, Kiseop, 2021. "Intervention analysis based on exponential smoothing methods: Applications to 9/11 and COVID-19 effects," Economic Modelling, Elsevier, vol. 98(C), pages 290-301.
- Yajing Gao & Xiaojie Zhou & Jiafeng Ren & Zheng Zhao & Fushen Xue, 2018. "Electricity Purchase Optimization Decision Based on Data Mining and Bayesian Game," Energies, MDPI, vol. 11(5), pages 1-19, April.
- Alina M. Grebenkina, 2023. "Monetary Authorities’ Experience in Considering Climate Risks [Опыт Монетарных Властей По Учету Климатических Рисков]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 11, pages 26-31, November.
- Mikkel Bennedsen, 2015. "Rough electricity: a new fractal multi-factor model of electricity spot prices," CREATES Research Papers 2015-42, Department of Economics and Business Economics, Aarhus University.
- Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
- Mustafa Gülerce & Gazanfer Ünal, 2018. "Electricity price forecasting using multiple wavelet coherence method: Comparison of ARMA versus VARMA," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-20, March.
- Jasiński, Tomasz, 2019. "Modeling electricity consumption using nighttime light images and artificial neural networks," Energy, Elsevier, vol. 179(C), pages 831-842.
- Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020.
"Comparing the forecasting performances of linear models for electricity prices with high RES penetration,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Papers 1801.01093, arXiv.org, revised Nov 2019.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
- Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
- Lintao Yang & Honggeng Yang & Haitao Liu, 2018. "GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting," Sustainability, MDPI, vol. 10(1), pages 1-16, January.
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
- Maciejowska, Katarzyna & Nowotarski, Jakub, 2016.
"A hybrid model for GEFCom2014 probabilistic electricity price forecasting,"
International Journal of Forecasting, Elsevier, vol. 32(3), pages 1051-1056.
- Katarzyna Maciejowska & Jakub Nowotarski, 2015. "A hybrid model for GEFCom2014 probabilistic electricity price forecasting," HSC Research Reports HSC/15/06, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Tschora, Léonard & Pierre, Erwan & Plantevit, Marc & Robardet, Céline, 2022. "Electricity price forecasting on the day-ahead market using machine learning," Applied Energy, Elsevier, vol. 313(C).
- Simon Pezzutto & Gianluca Grilli & Stefano Zambotti & Stefan Dunjic, 2018. "Forecasting Electricity Market Price for End Users in EU28 until 2020—Main Factors of Influence," Energies, MDPI, vol. 11(6), pages 1-18, June.
- repec:dui:wpaper:1504 is not listed on IDEAS
- Zhang, Hong & Nguyen, Hoang & Bui, Xuan-Nam & Pradhan, Biswajeet & Mai, Ngoc-Luan & Vu, Diep-Anh, 2021. "Proposing two novel hybrid intelligence models for forecasting copper price based on extreme learning machine and meta-heuristic algorithms," Resources Policy, Elsevier, vol. 73(C).
- Felten, Björn, 2020. "An integrated model of coupled heat and power sectors for large-scale energy system analyses," Applied Energy, Elsevier, vol. 266(C).
- Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
- Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
- Barbara Glensk & Reinhard Madlener, 2019.
"Energiewende @ Risk: On the Continuation of Renewable Power Generation at the End of Public Policy Support,"
Energies, MDPI, vol. 12(19), pages 1-25, September.
- Glensk, Barbara & Madlener, Reinhard, 2019. "Energiewende @ Risk: On the Continuation of Renewable Power Generation at the End of Public Policy Support," FCN Working Papers 5/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised 01 Nov 2019.
- Ehsani, Behdad & Pineau, Pierre-Olivier & Charlin, Laurent, 2024. "Price forecasting in the Ontario electricity market via TriConvGRU hybrid model: Univariate vs. multivariate frameworks," Applied Energy, Elsevier, vol. 359(C).
- Bartosz Uniejewski & Jakub Nowotarski & Rafał Weron, 2016.
"Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting,"
Energies, MDPI, vol. 9(8), pages 1-22, August.
- Bartosz Uniejewski & Jakub Nowotarski & Rafal Weron, 2016. "Automated variable selection and shrinkage for day-ahead electricity price forecasting," HSC Research Reports HSC/16/06, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
- Kristjanpoller, Werner & Minutolo, Marcel C., 2021. "Asymmetric multi-fractal cross-correlations of the price of electricity in the US with crude oil and the natural gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
- Zorana Božić & Dušan Dobromirov & Jovana Arsić & Mladen Radišić & Beata Ślusarczyk, 2020. "Power Exchange Prices: Comparison of Volatility in European Markets," Energies, MDPI, vol. 13(21), pages 1-15, October.
- Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018.
"Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting,"
Energies, MDPI, vol. 11(9), pages 1-20, September.
- Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2018. "Selection of calibration windows for day-ahead electricity price forecasting," HSC Research Reports HSC/18/06, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Ismael Ahrazem Dfuf & José Manuel Mira McWilliams & María Camino González Fernández, 2019. "Multi-Output Conditional Inference Trees Applied to the Electricity Market: Variable Importance Analysis," Energies, MDPI, vol. 12(6), pages 1-24, March.
- Keles, Dogan & Dehler-Holland, Joris & Densing, Martin & Panos, Evangelos & Hack, Felix, 2020. "Cross-border effects in interconnected electricity markets - an analysis of the Swiss electricity prices," Energy Economics, Elsevier, vol. 90(C).
- Hortay, Olivér & Víg, Attila A., 2020. "Potential effects of market power in Hungarian solar boom," Energy, Elsevier, vol. 213(C).
- Yiyuan Chen & Yufeng Wang & Jianhua Ma & Qun Jin, 2019. "BRIM: An Accurate Electricity Spot Price Prediction Scheme-Based Bidirectional Recurrent Neural Network and Integrated Market," Energies, MDPI, vol. 12(12), pages 1-18, June.
- Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
- Niels Haldrup & Oskar Knapik & Tommaso Proietti, 2016. "A generalized exponential time series regression model for electricity prices," CREATES Research Papers 2016-08, Department of Economics and Business Economics, Aarhus University.
- Yanbing Lin & Hongyuan Luo & Deyun Wang & Haixiang Guo & Kejun Zhu, 2017. "An Ensemble Model Based on Machine Learning Methods and Data Preprocessing for Short-Term Electric Load Forecasting," Energies, MDPI, vol. 10(8), pages 1-16, August.
- Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
- Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2021.
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Energies, MDPI, vol. 14(11), pages 1-26, June.
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