Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

[1]  Yoshua Bengio,et al.  Algorithms for Hyper-Parameter Optimization , 2011, NIPS.

[2]  Florian Ziel,et al.  Probabilistic mid- and long-term electricity price forecasting , 2017, Renewable and Sustainable Energy Reviews.

[3]  Florian Ziel,et al.  Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories , 2020, Applied Energy.

[4]  Syed Yousaf Raza Shah,et al.  Electricity Price Forecasting in Smart Grid: A Novel E-CNN Model , 2019, AINA Workshops.

[5]  Hiroyuki Mori,et al.  An Electricity Price Forecasting Model with Fuzzy Clustering Preconditioned ANN , 2018 .

[6]  Nadeem Javaid,et al.  ESAENARX and DE-RELM: Novel schemes for big data predictive analytics of electricity load and price , 2019, Sustainable Cities and Society.

[7]  Amir F. Atiya,et al.  Why does forecast combination work so well? , 2020, International Journal of Forecasting.

[8]  Florian Ziel,et al.  Forecasting Electricity Spot Prices Using Lasso: On Capturing the Autoregressive Intraday Structure , 2015, IEEE Transactions on Power Systems.

[9]  Nitin Singh,et al.  A PSO-Based ANN Model for Short-Term Electricity Price Forecasting , 2018 .

[10]  Francesco Lisi,et al.  Component estimation for electricity market data: Deterministic or stochastic? , 2015, 2015 Modern Electric Power Systems (MEPS).

[11]  P. Narayan,et al.  Are Indian stock returns predictable , 2015 .

[12]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[13]  Sara Atef,et al.  A Comparative Study Using Deep Learning and Support Vector Regression for Electricity Price Forecasting in Smart Grids , 2019, 2019 IEEE 6th International Conference on Industrial Engineering and Applications (ICIEA).

[14]  Grzegorz Marcjasz,et al.  A Note on Averaging Day-Ahead Electricity Price Forecasts Across Calibration Windows , 2019, IEEE Transactions on Sustainable Energy.

[15]  Wei Gao,et al.  Combination of fuzzy based on a meta-heuristic algorithm to predict electricity price in an electricity markets , 2017 .

[16]  M. Ghofrani,et al.  A new day-ahead hourly electricity price forecasting framework , 2017, 2017 North American Power Symposium (NAPS).

[17]  R. Weron Electricity price forecasting: A review of the state-of-the-art with a look into the future , 2014 .

[18]  Rosa Espínola,et al.  The effect of wind generation and weekday on Spanish electricity spot price forecasting , 2011 .

[19]  Wenbo Chen,et al.  Electricity price prediction based on hybrid model of adam optimized LSTM neural network and wavelet transform , 2019, Energy.

[20]  Florian Ziel,et al.  Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices , 2018, International Journal of Forecasting.

[21]  Hiroyuki Mori,et al.  A Fuzzy-Preconditioned GRBFN Model for Electricity Price Forecasting , 2017 .

[22]  F. Ravazzolo,et al.  CENTRE FOR APPLIED MACRO – AND PETROLEUM ECONOMICS ( CAMP ) CAMP Working Paper Series No 2 / 2018 Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration , 2018 .

[23]  Anamika,et al.  Market-Clearing Price Forecasting for Indian Electricity Markets , 2017 .

[24]  Bart De Schutter,et al.  Forecasting day-ahead electricity prices in Europe: the importance of considering market integration , 2017, ArXiv.

[25]  Florian Ziel,et al.  Variance Stabilizing Transformations for Electricity Spot Price Forecasting , 2018, IEEE Transactions on Power Systems.

[26]  Jakub Nowotarski,et al.  LTSC_EXAMPLE: MATLAB example script and data for "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices" , 2013 .

[27]  J. S,et al.  Two-Stage Machine Learning Framework for Simultaneous Forecasting of Price-Load in the Smart Grid , 2018 .

[28]  Dimitrije Kotur,et al.  Neural network models for electricity prices and loads short and long-term prediction , 2016, 2016 4th International Symposium on Environmental Friendly Energies and Applications (EFEA).

[29]  Manoj Tripathy,et al.  Short-term load/price forecasting in deregulated electric environment using ELMAN neural network , 2015, 2015 International Conference on Energy Economics and Environment (ICEEE).

[30]  Derek W. Bunn,et al.  Short-Term Electricity Price Forecasting with Recurrent Regimes and Structural Breaks , 2019, Energies.

[31]  Ranjeeta Bisoi,et al.  Short-term electricity price forecasting and classification in smart grids using optimized multikernel extreme learning machine , 2018, Neural Computing and Applications.

[32]  I. J. Ramírez-Rosado,et al.  Explanatory information analysis for day-ahead price forecasting in the Iberian electricity market , 2015 .

[33]  R. Weron,et al.  Energy Forecasting: A Review and Outlook , 2020, IEEE Open Access Journal of Power and Energy.

[34]  N. Javaid,et al.  Deep Long Short-Term Memory: A New Price and Load Forecasting Scheme for Big Data in Smart Cities , 2019, Sustainability.

[35]  T. Pinto,et al.  Day-ahead electricity market price forecasting using artificial neural network with spearman data correlation , 2019, 2019 IEEE Milan PowerTech.

[36]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[37]  Qun Jin,et al.  BRIM: An Accurate Electricity Spot Price Prediction Scheme-Based Bidirectional Recurrent Neural Network and Integrated Market , 2019, Energies.

[38]  Ji Zhu,et al.  L1-Norm Quantile Regression , 2008 .

[39]  Noradin Ghadimi,et al.  The price prediction for the energy market based on a new method , 2018 .

[40]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[41]  Bart De Schutter,et al.  Forecasting spot electricity prices Deep learning approaches and empirical comparison of traditional algorithms , 2018 .

[42]  S. Schneider Power Spot Price Models with negative Prices , 2011 .

[43]  Estefania Planas,et al.  A Note on the Normalization of Spanish Electricity Spot Prices , 2016, IEEE Transactions on Power Systems.

[44]  Zheng Wang,et al.  Seasonal classification and RBF adaptive weight based parallel combined method for day-ahead electricity price forecasting , 2018, 2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT).

[45]  Akbar Maleki,et al.  Electricity price forecasting using neural networks with an improved iterative training algorithm , 2018 .

[46]  Ying-Yi Hong,et al.  Short-term LMP forecasting using an artificial neural network incorporating empirical mode decomposition , 2015 .

[47]  Rajesh Kumar,et al.  A hybrid approach to price forecasting incorporating exogenous variables for a day ahead electricity Market , 2016, 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES).

[48]  Halbert White,et al.  Tests of Conditional Predictive Ability , 2003 .

[49]  Rafał Weron,et al.  Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO , 2018, International Journal of Forecasting.

[50]  Derek W. Bunn,et al.  Fundamental and Behavioural Drivers of Electricity Price Volatility , 2010 .

[51]  Sílvio Mariano,et al.  A bat optimized neural network and wavelet transform approach for short-term price forecasting , 2018 .

[52]  K. Maciejowska,et al.  PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices , 2020, Energies.

[53]  Jakub Nowotarski,et al.  Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting , 2016 .

[54]  Mohsen Mohammadi,et al.  Day-ahead price forecasting based on hybrid prediction model , 2016, Complex..

[55]  Zhongfu Tan,et al.  Forecasting day-ahead electricity prices using a new integrated model , 2019, International Journal of Electrical Power & Energy Systems.

[56]  Tomasz Serafin,et al.  Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) Method , 2021, ICCS.

[57]  George Athanasopoulos,et al.  Forecasting: principles and practice , 2013 .

[58]  Gul Muhammad Khan,et al.  Efficient Prediction of Dynamic Tariff in Smart Grid Using CGP Evolved Artificial Neural Networks , 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

[59]  D. N. Sidorov,et al.  Forecasting nonstationary time series based on Hilbert-Huang transform and machine learning , 2014, Autom. Remote. Control..

[60]  Amin Kargarian,et al.  Multi-agent microgrid energy management based on deep learning forecaster , 2019, Energy.

[61]  Bartosz Uniejewski,et al.  Regularized quantile regression averaging for probabilistic electricity price forecasting , 2021 .

[62]  Joakim Westerlund,et al.  Testing for Predictability in Conditionally Heteroskedastic Stock Returns , 2015 .

[63]  Jing Ma,et al.  Research and application of a hybrid wavelet neural network model with the improved cuckoo search algorithm for electrical power system forecasting , 2017 .

[64]  Ilkay Oksuz,et al.  The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company , 2018, Energies.

[65]  T. Aruldoss Albert Victoire,et al.  Two-Stage Machine Learning Framework for Simultaneous Forecasting of Price-Load in the Smart Grid , 2018, ICMLA.

[66]  I. Jacob Raglend,et al.  Sequential wavelet-ANN with embedded ANN-PSO hybrid electricity price forecasting model for Indian energy exchange , 2015, Neural Computing and Applications.

[67]  Zijun Zhang,et al.  Short-Term Electricity Price Forecasting With Stacked Denoising Autoencoders , 2017, IEEE Transactions on Power Systems.

[68]  Arun Sukumaran Nair,et al.  Deep Neural Networks (DNN) for Day-Ahead Electricity Price Markets , 2018, 2018 IEEE Electrical Power and Energy Conference (EPEC).

[69]  Katarzyna Maciejowska,et al.  Assessing the impact of renewable energy sources on the electricity price level and variability – A quantile regression approach , 2020, Energy Economics.

[70]  Zhang Yang,et al.  Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernel-based extreme learning machine methods , 2017 .

[71]  Wei Gao,et al.  Different states of multi-block based forecast engine for price and load prediction , 2019, International Journal of Electrical Power & Energy Systems.

[72]  Rob J Hyndman,et al.  Another look at measures of forecast accuracy , 2006 .

[73]  Jakub Nowotarski,et al.  An empirical comparison of alternate schemes for combining electricity spot price forecasts , 2013 .

[74]  Qing Guo,et al.  A Lower Extremity Exoskeleton: Human-Machine Coupled Modeling, Robust Control Design, Simulation, and Overload-Carrying Experiment , 2015 .

[75]  Ping Jiang,et al.  A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting , 2015 .

[76]  Salim Lahmiri,et al.  Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices , 2017, IEEE Systems Journal.

[77]  Nadeem Javaid,et al.  Electricity Price and Load Forecasting using Enhanced Convolutional Neural Network and Enhanced Support Vector Regression in Smart Grids , 2019, Electronics.

[78]  Yang Zhang,et al.  Effective Adam-Optimized LSTM Neural Network for Electricity Price Forecasting , 2018, 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS).

[79]  Johannes Krokeide Kolberg,et al.  Artificial Intelligence and Nord Pool’s intraday electricity market Elbas : a demonstration and pragmatic evaluation of employing deep learning for price prediction : using extensive market data and spatio-temporal weather forecasts , 2018 .

[80]  Angelica Gianfreda,et al.  Market Design for Long-Distance Trade in Renewable Electricity , 2016 .

[81]  R. Weron,et al.  Recent advances in electricity price forecasting: A review of probabilistic forecasting , 2016 .

[82]  Andreas Wagner,et al.  Electricity Price Forecasting with Neural Networks on EPEX Order Books , 2019, Applied Mathematical Finance.

[83]  Eva Onaindia,et al.  On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market , 2019, Energies.

[84]  . Anamika,et al.  Electricity Price Forecasting and Classification Through Wavelet–Dynamic Weighted PSO–FFNN Approach , 2018, IEEE Systems Journal.

[85]  Bijaya K. Panigrahi,et al.  Electricity price classification using extreme learning machines , 2013, Neural Computing and Applications.

[86]  R. Tibshirani,et al.  REJOINDER TO "LEAST ANGLE REGRESSION" BY EFRON ET AL. , 2004, math/0406474.

[87]  Rafał Weron,et al.  Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting , 2018, Energies.

[88]  Rob J Hyndman,et al.  Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond , 2016 .

[89]  Zhiwei Wang,et al.  Power Market Price Forecasting via Deep Learning , 2018, IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society.

[90]  Nadeem Javaid,et al.  Short-Term Electric Load and Price Forecasting Using Enhanced Extreme Learning Machine Optimization in Smart Grids , 2019, Energies.

[91]  Mohammad Shahidehpour,et al.  Electricity Price Forecasting , 2002 .

[92]  Rafał Weron,et al.  Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks , 2018, 1805.06649.

[93]  Z. H. Bohari,et al.  Electricity Price Forecasting Using Neural Network with Parameter Selection , 2019 .

[94]  C. Li,et al.  A Novel Hybrid Forecasting Method Using GRNN Combined With Wavelet Transform and a GARCH Model , 2015 .

[95]  Nadeem Javaid,et al.  Big Data Analytics for Price and Load Forecasting in Smart Grids , 2018, BWCCA.

[96]  Rafał Weron,et al.  On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks , 2019, International Journal of Forecasting.

[97]  Olivier Grunder,et al.  Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by firefly algorithm , 2017 .

[98]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[99]  Mun-Kyeom Kim,et al.  Short-term price forecasting of Nordic power market by combination Levenberg–Marquardt and Cuckoo search algorithms , 2015 .

[100]  Joao P. S. Catalao,et al.  Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method , 2015 .

[101]  M. Hashem Pesaran,et al.  Selection of estimation window in the presence of breaks , 2007 .

[102]  Mohammad Hossein Javidi,et al.  Electricity price forecasting using a new data fusion algorithm , 2015 .

[103]  Ioannis P. Panapakidis,et al.  Day-ahead electricity price forecasting via the application of artificial neural network based models , 2016 .

[104]  Jakub Nowotarski,et al.  On the importance of the long-term seasonal component in day-ahead electricity price forecasting , 2016, Energy Economics.

[105]  Joao P. S. Catalao,et al.  Hybrid model using three-stage algorithm for simultaneous load and price forecasting , 2018, Electric Power Systems Research.

[106]  Joao P. S. Catalao,et al.  Price Forecasting of Electricity Markets in the Presence of a High Penetration of Wind Power Generators , 2017 .

[107]  Nitin Singh,et al.  Short term electricity price forecast based on environmentally adapted generalized neuron , 2017 .

[108]  Ross Baldick,et al.  Day-Ahead Price Forecasting in ERCOT Market Using Neural Network Approaches , 2019, e-Energy.

[109]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[110]  Francesco Lisi,et al.  Combining day-ahead forecasts for British electricity prices , 2013 .

[111]  Jesus Lago,et al.  Neural networks in day-ahead electricity price forecasting: Single vs. multiple outputs , 2020, ArXiv.

[112]  R. Weron,et al.  Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models , 2016 .

[113]  Ali Ahmadian,et al.  A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks , 2020, IEEE Transactions on Industrial Informatics.

[114]  Stefan Trück,et al.  Electricity markets around the world , 2018 .

[115]  S. Surender Reddy,et al.  Day-ahead electricity price forecasting using back propagation neural networks and weighted least square technique , 2016, Frontiers in Energy.

[116]  Rafał Weron,et al.  Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models , 2018, Energies.

[117]  Hazlee Azil Illias,et al.  Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach , 2019, IEEE Access.

[118]  Francis X. Diebold,et al.  Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold–Mariano Tests , 2012 .

[119]  Guoqiang Hu,et al.  Day-Ahead Price Forecasting for Electricity Market using Long-Short Term Memory Recurrent Neural Network , 2018, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV).

[120]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[121]  Dipti Srinivasan,et al.  Forecasting of Electricity Prices Using Deep Learning Networks , 2018, 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).

[122]  Abhinav Aggarwal,et al.  A novel hybrid approach using wavelet transform, time series time delay neural network, and error predicting algorithm for day-ahead electricity price forecasting , 2017, 2017 6th International Conference on Computer Applications In Electrical Engineering-Recent Advances (CERA).

[123]  Ping-Huan Kuo,et al.  An Electricity Price Forecasting Model by Hybrid Structured Deep Neural Networks , 2018 .

[124]  Tomasz Serafin,et al.  Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting , 2019, Energies.

[125]  Ilkay Oksuz,et al.  Electricity Price Forecasting Using Recurrent Neural Networks , 2018 .

[126]  Shuman Luo,et al.  A two-stage supervised learning approach for electricity price forecasting by leveraging different data sources , 2019, Applied Energy.

[127]  Ignacio J. Ramirez-Rosado,et al.  Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market , 2016 .

[128]  Bri-Mathias Hodge,et al.  The impact of wind power on electricity prices , 2016 .

[129]  Wei Xu,et al.  The Day-Ahead Electricity Price Forecasting Based on Stacked CNN and LSTM , 2018, IScIDE.

[130]  Florian Ziel,et al.  Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets , 2015, 1501.00818.

[131]  Y. Yao,et al.  On Early Stopping in Gradient Descent Learning , 2007 .

[132]  Stephan Schneider,et al.  ANN-Based Electricity Price Forecasting Under Special Consideration of Time Series Properties , 2018, ICTERI.

[133]  P. Alam ‘A’ , 2021, Composites Engineering: An A–Z Guide.

[134]  Florian Ziel,et al.  Efficient modeling and forecasting of electricity spot prices , 2014, 1402.7027.

[135]  Heng-Ming Tai,et al.  An Optimized Heterogeneous Structure LSTM Network for Electricity Price Forecasting , 2019, IEEE Access.

[136]  Luigi Grossi,et al.  Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources , 2019, Technological Forecasting and Social Change.

[137]  Mohammad Bagher Menhaj,et al.  A combination approach based on a novel data clustering method and Bayesian recurrent neural network for day-ahead price forecasting of electricity markets , 2019, Electric Power Systems Research.

[138]  Barbara Rossi,et al.  Forecasting in macroeconomics , 2013 .