Electricity price forecasting: A review of the state-of-the-art with a look into the future

Generalized autoregressive conditional heteroskedasticity

Bollerslev, T. (1986) · Journal of Econometrics · doi:10.1016/0304-4076(86)90063-1 · Cited by 22,346

Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation

Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795

A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle

Hamilton, J. D. (1989) · Econometrica · doi:10.2307/1912559 · Cited by 9,696

A Theory of the Term Structure of Interest Rates

Cox, J. C., Ingersoll, J. E., & Ross, S. A. (1985) · Econometrica · doi:10.2307/1911242 · Cited by 8,591

An equilibrium characterization of the term structure

Vasicek, O. A. (1977) · Journal of Financial Economics · doi:10.1016/0304-405x(77)90016-2 · Cited by 6,109

Strictly Proper Scoring Rules, Prediction, and Estimation

Gneiting, T., & Raftery, A. E. (2007) · Journal of the American Statistical Association · doi:10.1198/016214506000001437 · Cited by 5,793

Another look at measures of forecast accuracy

Hyndman, R. J., & Koehler, A. B. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.03.001 · Cited by 5,757

Comparing Predictive Accuracy

Diebold, F. X., & Mariano, R. S. (1995) · Journal of Business and Economic Statistics · doi:10.1080/07350015.1995.10524599 · Cited by 5,240

Artificial neural networks: a tutorial

Jain, A. K., Mao, J., & Mohiuddin, K. M. (1996) · Computer · doi:10.1109/2.485891 · Cited by 5,095

Forecasting principles and practice

Hyndman, R. J., & Athanasopoulos, G. (2018) · Cited by 4,405

Statistical Regression Model for Annual Hourly Price Estimation in the Spanish Electricity Market

Naval, N., Tipán-Salazar, L., & Yusta, J. M. (2025) · Renewable Energy and Power Quality Journal · doi:10.52152/4568 · Cited by 6

The impact of probability of electricity price spike and outside temperature to define total expected cost for air conditioning

Marwan, M. (2020) · Energy · doi:10.1016/j.energy.2020.116994 · Cited by 6

A Monte Carlo evaluation of non-parametric estimators of expected shortfall

Mehlitz, J. S., & Auer, B. R. (2020) · The Journal of Risk Finance · doi:10.1108/jrf-07-2019-0122 · Cited by 6

Optimizing the Daily Energy Consumption of an Enterprise

Maryasin, O. Y., & Lukashov, A. I. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-3-030-94202-1_35 · Cited by 6

Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices

Golia, S., Grossi, L., & Pelagatti, M. M. (2022) · Forecasting · doi:10.3390/forecast5010003 · Cited by 7

The impact of transparency policies on local flexibility markets in electric distribution networks

Heilmann, E. (2023) · Utilities Policy · doi:10.1016/j.jup.2023.101592 · Cited by 6

Easing Predictors Selection in Electricity Price Forecasting with Deep Learning Techniques

Silva, A. R., Fidalgo, J. N., & Andrade, J. (2023) · International Conference on the European Energy Market (EEM) · doi:10.1109/eem58374.2023.10161909 · Cited by 6

Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach

Li, J., Wang, C., & Wang, H. (2023) · IEEE Power Engineering Society General Meeting · doi:10.1109/pesgm52003.2023.10253181 · Cited by 6

Role of Renewables in Energy Storage Economic Viability in the Western Balkans

Topalović, Z., & Haas, R. (2024) · Energies · doi:10.3390/en17040955 · Cited by 6

A black-box adversarial attack on demand side management

Cramer, E., & Gao, J. Q. (2024) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2024.108681 · Cited by 6

Decoding renewable PPA prices in California's energy market

Peña, J. I., Rodriguez, R. M., & Mayoral, S. (2026) · Renewable Energy · doi:10.1016/j.renene.2025.125168 · Cited by 6

Use Cases and Introductory Analysis of the Dataset Collected Within the Large Network of Public Charging Stations

Straka, M., & Buzna, Ľ. (2019) · Lecture notes in networks and systems · doi:10.1007/978-3-030-12450-2_19 · Cited by 6

A fractional Brownian–Hawkes model for the Italian electricity spot market: estimation and forecasting

Giordano, L., & Morale, D. (2021) · The Journal of Energy Markets · doi:10.21314/jem.2021.001 · Cited by 6

Half-Empty or Half-Full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime

Walk, J., Hirt, R., Kühl, N., & Hersløv, E. R. (2020) · Lecture notes in business information processing · doi:10.1007/978-3-030-38724-2_8 · Cited by 6

Forecasting Available Demand-Side Flexibility

Ahmadiahangar, R., Rosin, A., Palu, I., & Azizi, A. (2020) · SpringerBriefs in applied sciences and technology · doi:10.1007/978-981-15-4627-3_4 · Cited by 6

Optimal Daily Trading of Battery Operations Using Arbitrage Spreads

Abramova, E., & Bunn, D. W. (2021) · Energies · doi:10.3390/en14164931 · Cited by 6

Electrical consumption forecasting: a framework for high frequency data

Michell, K., Kristjanpoller, W., & Minutolo, M. C. (2022) · Neural Computing and Applications · doi:10.1007/s00521-021-06735-8 · Cited by 7

Modeling Price Spikes in Electricity Markets—The Impact of Load, Weather, and Capacity

Handika, R., Truong, C. H., Trück, S., & Weron, R. (2014) · Palgrave Macmillan US eBooks · doi:10.1007/978-1-137-37027-3_7 · Cited by 6

Electricity Market Price Forecasting for a High Renewable Penetrated Power System via Random Forest

Xu, K., Sun, B., Wang, P., Zhu, Z., & Tang, H. (2022) · IEEE/IAS Industrial and Commercial Power Systems Technical Conference · doi:10.1109/icps54075.2022.9773839 · Cited by 6

Machine Learning and Bagging to Predict Midterm Electricity Consumption in Saudi Arabia

Musleh, D. A., & Metrik, M. A. A. (2023) · Applied System Innovation · doi:10.3390/asi6040065 · Cited by 6

ANN-Based Electricity Price Forecasting Under Special Consideration of Time Series Properties

Meier, J.-H., Schneider, S., Schmidt, I., Schüller, P., Schönfeldt, T., & Wanke, B. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-13929-2_13 · Cited by 7

PRICING OPTIONS ON FORWARDS IN ENERGY MARKETS: THE ROLE OF MEAN REVERSION'S SPEED

Schmeck, M. D. (2016) · International Journal of Theoretical and Applied Finance · doi:10.1142/s0219024916500539 · Cited by 6

Forecasting Electricity Prices: Autoregressive Hybrid Nearest Neighbors (ARHNN) Method

Nitka, W., Serafin, T., & Sotiros, D. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77970-2_24 · Cited by 6

Optimal Day-Ahead Orders Using Stochastic Programming and Noise-Driven Recurrent Neural Networks

Biel, M. (2021) · IEEE PowerTech Conference · doi:10.1109/powertech46648.2021.9494929 · Cited by 6

Integrated scheduling and bidding of power and reserve of energy resource aggregators with storage plants

Kuttner, L. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.119285 · Cited by 6

Classification of load forecasting studies by forecasting problem to select load forecasting techniques and methodologiesPreprint

Dumas, J., & Cornélusse, B. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.05052 · Cited by 7

A Stochastic Latent Moment Model for Electricity Price FormationPreprint

Gianfreda, A., & Bunn, D. W. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3038357 · Cited by 6

Price signal forecasting for day-ahead offering strategy of price-maker renewable energy producers considering different risk preferences

Huo, W., Zhang, Y., Zhao, H., Lin, F., & Wang, J. (2025) · Applied Energy · doi:10.1016/j.apenergy.2025.126819 · Cited by 5

A data-driven method for predicting short-term electricity demand using technical indicators

Gammanpila, W., Gammanpila, A. C., Kularathna, A. H. T. S., & Jayasooriya, N. K. (2026) · Energy Informatics · doi:10.1186/s42162-026-00645-6 · Cited by 5

Transformer-based deep learning for multi-horizon global power generation forecasting

Gawusu, S., & Zhang, X. (2026) · Energy Conversion and Management · doi:10.1016/j.enconman.2026.121284 · Cited by 5

Carbon-aware scheduling and distributionally robust optimization for cloud systems: forecasting, battery storage, and adaptive ambiguity refinement

Ruparel, H. (2026) · Journal of Cloud Computing Advances Systems and Applications · doi:10.1186/s13677-026-00904-7 · Cited by 5

Optimizing Energy Storage Profits: A New Metric for Evaluating Price Forecasting Models

Sbaraglia, S., Maccioni, A. F., & Zedda, S. (2024) · Journal of risk and financial management · doi:10.3390/jrfm17120538 · Cited by 5

Probabilistic Energy Forecasting Based on Self-organizing Inductive Modeling

Lemke, F. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-01069-0_29 · Cited by 5

Big Data and Energy Security: Impacts on Private Companies, National Economies and Societies

Hassani, H., Komendantova, N., Kroos, D., Unger, S., & Yeganegi, M. R. (2021) · IoT · doi:10.3390/iot3010002 · Cited by 5

JEPX spot prices forecasting system using GIS

Nakayama, S., Shiota, A., Mitani, Y., & Watanabe, M. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.10.419 · Cited by 5

Energy Storage Arbitrage in Day-Ahead Electricity Market Using Deep Reinforcement Learning

Zonjee, T., & Torbaghan, S. S. (2023) · IEEE PowerTech Conference · doi:10.1109/powertech55446.2023.10202674 · Cited by 5

Green Energy Cloud -Taxonomy, Infrastructure, Platform, and Services

Gao, J. Z., Wu, J., Liu, J. P., & Aremanda, V. V. (2023) · IEEE International Symposium on Service-Oriented System Engineering (SOSE) · doi:10.1109/sose58276.2023.00029 · Cited by 5

Changing Electricity Tariff—An Empirical Analysis Based on Commercial Customers’ Data from Poland

Ząbkowski, T., Gajowniczek, K., Matejko, G., Brożyna, J., Mentel, G., Charytanowicz, M., Jarnicka, J., Olwert, A., & Radziszewska, W. (2023) · Energies · doi:10.3390/en16196853 · Cited by 5

Evaluation of forecasting models for improved passenger market management and rolling stock planning on Indian railways

Bhatia, V., & Kalaivani, K. (2024) · foresight · doi:10.1108/fs-09-2022-0105 · Cited by 5

Multifractal Analysis of the Impact of Fuel Cell Introduction in the Korean Electricity Market

Ock, S. E., Lee, M., & Song, J. W. (2024) · Fractal and Fractional · doi:10.3390/fractalfract8100573 · Cited by 5

Fractal-Based Robotic Trading Strategies Using Detrended Fluctuation Analysis and Fractional Derivatives: A Case Study in the Energy Market

Popovska, E., & Georgieva-Tsaneva, G. N. (2024) · Fractal and Fractional · doi:10.3390/fractalfract9010005 · Cited by 5

Flexibility Service for Balance Responsible Parties’ Industrial Customers: A Day-Ahead Cost Optimization Approach Using Price Forecasting

Caprara, A., Barja-Martínez, S., Aragüés‐Peñalba, M., & Bullich‐Massagué, E. (2025) · IEEE Access · doi:10.1109/access.2025.3567879 · Cited by 5

The rationale for projected prices of demand on electricity for industry in Russia up to 2020

Kossov, V. V. (2016) · Studies on Russian Economic Development · doi:10.1134/s1075700716010081 · Cited by 5

Time Series Data Mining for Energy Prices Forecasting: An Application to Real Data

Silva, E. C. E., Borges, A., Teodoro, M. F., Andrade, M. A. P., & Covas, R. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-53480-0_64 · Cited by 5

Hybrid ARIMA and Support Vector Regression in Short-term Electricity Price Forecasting

Pokora, J. (2017) · Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis · doi:10.11118/actaun201765020699 · Cited by 5

The strategy and architecture of a winner broker in a renowned agent-based smart grid competition

Ozdemir, S., & Unland, R. (2017) · Web Intelligence · doi:10.3233/web-170358 · Cited by 5

The Projection Model As an Early Warning of Food Price Commodity Fluctuation

Pujiati, A., Oktavilia, S., & Damayanti, N. A. (2018) · KnE Social Sciences · doi:10.18502/kss.v3i10.3178 · Cited by 5

Using symbolic networks to analyse dynamical properties of disease outbreaks

Herrera, J. L., Buldú, J. M., Chávez, M., & Martínez, J. H. (2020) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.2019.0777 · Cited by 5

Feature Engineering for Short-Term Forecast of Energy Consumption

Spichakova, M., Belikov, J., Nou, K., & Petlenkov, E. (2019) · IEEE PES Innovative Smart Grid Technologies Europe · doi:10.1109/isgteurope.2019.8905698 · Cited by 5

Study on Electricity Market Price Forecasting with Large-Scale wind Power Based on LSTM

Liu, S., Zhang, L., & Zou, B. (2020) · International Conference on Dependable Systems and Their Applications (DSA) · doi:10.1109/dsa.2019.00045 · Cited by 5

Artificial Intelligence Models Used for Prediction in the Energy Internet

Heghedus, C., & Rong, C. (2020) · Springer eBooks · doi:10.1007/978-3-030-45453-1_11 · Cited by 5

Reliability versus renewables: Modeling costs and revenue in CAISO and PJM

Wachs, L., & Engel, B. A. (2020) · The Electricity Journal · doi:10.1016/j.tej.2020.106860 · Cited by 5

Supervised electricity tariff prediction using random forest validated through user comfort and constraint for a home energy management scheme

Chellamani, G. K., Khan, M. F. A., & Chandramani, P. V. (2020) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-200722 · Cited by 5

Developing a Digital Model of an Electricity Consumer using Deep Learning

Maryasin, O. Y., & Lukashov, A. I. (2020) · International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) · doi:10.1109/summa50634.2020.9280610 · Cited by 5

Predicting Power Deviation in the Turkish Power Market Based on Adaptive Factor Impacts

Güven, D., Özözen, A., Kayakutlu, G., & Kayalica, M. Ö. (2021) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-80847-1_14 · Cited by 5

Locational marginal price forecasting using Transformer-based deep learning network

Liao, S., Wang, Z., Luo, Y., & Liang, H. (2021) · Chinese Control Conference (CCC) · doi:10.23919/ccc52363.2021.9549619 · Cited by 5

Recent Development in Electricity Price Forecasting Based on Computational Intelligence Techniques in Deregulated Power Market

Pourdaryaei, A., Mohammadi, M., Karimi, M., Mokhlis, H., Illias, H. A., Kaboli, S. H. A., & Ahmad, S. (2021) · Energies · doi:10.3390/en14196104 · Cited by 5

A Study on Improving Economy Efficiency of Pumping Stations Based on Tariff Changes

Napierała, M. (2022) · Energies · doi:10.3390/en15030799 · Cited by 5

A techno-economic model for avoiding conflicts of interest between owners of offshore wind farms and maintenance suppliers

Marugán, A. P., Márquez, F. P. G., & Pinar-Pérez, J. M. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112753 · Cited by 5

Predicting the Gap in the Day-Ahead and Real-Time Market Prices Leveraging Exogenous Weather Data

Nizharadze, N., Soofi, A. F., & Manshadi, S. D. (2023) · Algorithms · doi:10.3390/a16110508 · Cited by 5

Dynamic pricing mechanism for multi-agent based system of well scheduling

Dewan, M. A. A., Lin, F. O., & Kinshuk, K. (2016) · International Conference on Informatics, Electronics & Vision (ICIEV) · doi:10.1109/iciev.2016.7760170 · Cited by 5

Electricity price forecasting using multiple wavelet coherence method: Comparison of ARMA versus VARMA

Gülerce, M., & Ünal, G. (2018) · International Journal of Financial Engineering · doi:10.1142/s2424786318500044 · Cited by 5

Adaptive Regularized ELM and Improved VMD Method for Multi-step ahead Electricity Price Forecasting

Nachimuthu, D. S., Gobu, B., Jaikumar, S., Arulmozhi, N., Kanimozhi, P., & Victoire, T. A. A. (2018) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2018.00204 · Cited by 5

Optimal Control of a Dispatchable Energy Source for Wind Energy Management

D’Amico, G., Petroni, F., & Sobolewski, R. A. (2019) · Stochastics and Quality Control · doi:10.1515/eqc-2019-0001 · Cited by 5

Explanatory and Causal Analysis of the MIBEL Electricity Market Spot Price

Gonçalves, C., Ribeiro, M. A., Viana, J., Fernandes, R., Villar, J., Bessa, R. J., Correia, G., Sousa, J. C., Mendes, V., & Nunes, A. C. (2019) · doi:10.1109/ptc.2019.8810763 · Cited by 5

Day ahead electricity price forecast by NARX model with LASSO based features selection

Brusaferri, A., Fagiano, L., Matteucci, M., & Vitali, A. (2019) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin41052.2019.8972263 · Cited by 5

Economic Sustainability of Small-Scale Hydroelectric Plants on a National Scale—The Italian Case Study

Raimondi, A., Bettoni, F., Bianchi, A., & Becciu, G. (2021) · Water · doi:10.3390/w13091170 · Cited by 5

Market Makers and Liquidity Premium in Electricity Futures Markets

Peña, J. I., & Rodriguez, R. M. (2021) · The Energy Journal · doi:10.5547/01956574.43.2.jpen · Cited by 6

A Methodological Review of Time Series Forecasting with Deep Learning Model: A Case Study on Electricity Load and Price Prediction

Sinha, A., Singh, T., Vyas, R., Kumar, M., & Vyas, O. P. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-5868-7_34 · Cited by 5

Publisher’s Note

None (2020) · Solar Energy · doi:10.1016/j.solener.2020.06.083 · Cited by 5

Forecasting and optimization of ancillary services provision by renewable energy sources

Camal, S. (2020) · theses.fr (ABES) · doi:10.70675/f7e2523ez3717z42f6z9017z1dbb00430b26 · Cited by 5

The economics of smart EV charging at home: a review and research agenda

de Brauwer, C. P.-S., & Loock, M. (2026) · npj Sustainable Mobility and Transport · doi:10.1038/s44333-026-00105-4 · Cited by 4

Short-term forecasting of electricity prices using generative neural networks

Kaukin, A., Pavlov, P. N., & Kosarev, V. (2023) · Бизнес-информатика · doi:10.17323/2587-814x.2023.3.7.23 · Cited by 7

Forecasting Electricity Price During Extreme Events Using a Hybrid Model of LSTM and ARIMA Architecture

Borges, J., Maia, R., & Guerreiro, S. L. P. D. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-64748-2_15 · Cited by 4

A Comprehensive Analysis of Dropout Assisted Regularized Deep Learning Architectures for Dynamic Electricity Price Forecasting

Joshi, P., Størdal, S., Lien, G., Mishra, D., & Haugom, E. (2024) · IEEE Access · doi:10.1109/access.2024.3501773 · Cited by 4

A Robust Approach to Extend Deterministic Models for the Quantification of Uncertainty and Comprehensive Evaluation of the Probabilistic Forecasting

Upadhaya, A., Telle, J.-S., Schlüters, S., Saber, M., & von Maydell, K. (2025) · International Journal of Energy Research · doi:10.1155/er/4460462 · Cited by 4

ABMF-Net: An Attentive Bayesian Multi-Stage Deep Learning Model for Robust Forecasting of Electricity Price and Demand

Mir, M. N. H., Biswas, A. K., Bhuiyan, M. S. A., Abir, M. G. R., Mridha, M. F., & Hossen, M. J. (2025) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2025.3579522 · Cited by 4

Short-term electricity price forecasting via CPO-enhanced dual decomposition and NRBO-optimized deep learning

Mengfei, L. I., & Wang, X. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105520 · Cited by 4

Intelligent forecasting of electricity consumption for hospital outpatient buildings by FOA-SVR hybrid strategy

Liu, C., Wu, G., Zhang, L., Yao, Q., Yang, Y., & Xiao, Q. (2025) · Frontiers in Energy Research · doi:10.3389/fenrg.2025.1566664 · Cited by 4

Probability Density Forecasting of Electricity Price Difference in the Spot Market

Li, Z., Li, K., Huang, C., & Fotuhi‐Firuzabad, M. (2026) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2026.3651988 · Cited by 4

Bayesian Structural Time-Series Approach to a Long-Term Electricity Demand Forecasting

Mokilane, P., Debba, P., Yadavalli, V. S. S., & Sigauke, C. (2019) · Applied Mathematics & Information Sciences · doi:10.18576/amis/130206 · Cited by 4

Application to Real Case Studies

de Simón‐Martín, M., Bracco, S., Piazza, G., Pagnini, L., González-Martínez, A., & Delfino, F. (2022) · SpringerBriefs in applied sciences and technology · doi:10.1007/978-3-030-95932-6_4 · Cited by 4

Day-Ahead Electricity Market Price Forecasting Considering the Components of the Electricity Market Price; Using Demand Decomposition, Fuel Cost, and the Kernel Density Estimation

Jin, A., Lee, D.-H., Park, J., & Roh, J. H. (2023) · Energies · doi:10.3390/en16073222 · Cited by 4

Hybrid Power Plant Bidding in Models of Future Electricity Systems

Kemp, J. M., Heleno, M., & Mills, A. (2023) · IEEE Power Engineering Society General Meeting · doi:10.1109/pesgm52003.2023.10252335 · Cited by 4

A Study on the Nature of Complexity in the Spanish Electricity Market Using a Comprehensive Methodological Framework

Inglada‐Pérez, L., & y Gil, S. G. (2024) · Mathematics · doi:10.3390/math12060893 · Cited by 4

BiLSTM Model for Electricity Consumption Prediction: A Comparative Study with Traditional Machine Learning Approaches

Chauhan, N., Bansal, S. A., & Malik, M. (2024) · IEEE Delhi Section Conference (DELCON) · doi:10.1109/delcon64804.2024.10866016 · Cited by 4

Energy efficiency pricing in regulated electricity markets

Jin, G., Lim, Y.-M., & Nam, K. (2025) · Energy Economics · doi:10.1016/j.eneco.2025.108406 · Cited by 4

A sequential optimization approach for competitive procurement of energy and Ancillary Services

Banshwar, A., Sharma, N. K., Sood, Y. R., & Shrivastava, R. (2016) · IEEE International Conference on Electrical Power and Energy Systems (ICEPES) · doi:10.1109/icepes.2016.7915981 · Cited by 4

Cash flow at risk of offshore wind plants

Claudio, V., Ιωάννου, Α., & Brennan, F. (2017) · International Conference on Clean Electrical Power · doi:10.1109/iccep.2017.8004797 · Cited by 4

Grain Price Forecasting Using a Hybrid Stochastic Method

Zhao, Y. N., Zhang, X., Shi, Z., & He, L. (2017) · Asia Pacific Journal of Operational Research · doi:10.1142/s0217595917500208 · Cited by 4

Hedging local volume risk using forward markets: Nordic case

Ernstsen, R. R., Boomsma, T. K., Tegnér, M., & Skajaa, A. (2017) · Energy Economics · doi:10.1016/j.eneco.2017.10.017 · Cited by 4

Leveraging forecasting techniques for power procurement and improving grid stability: A strategic approach

Mahendra, L., Kalluri, R., Rao, M. S., Kumar, R., & Bindhumadhava, B. S. (2017) · Asia-Pacific Power and Energy Engineering Conference (APPEEC) · doi:10.1109/appeec.2017.8308978 · Cited by 4

Hurst Exponent with ARIMA and Simple Exponential Smoothing for Measuring Persistency of M3- Competition Series

Ponce-Flores, M. P., Frausto–Solís, J., Valdez, G. C., Barbosa, J. J. G., Pérez-Ortega, J., & Villanueva, J. D. T. (2019) · IEEE Latin America Transactions · doi:10.1109/tla.2019.8891950 · Cited by 4

A Mathematical Modeling for Contract Flexibility Optimization by Brazilian Free Consumers

Takigawa, F. Y. K., Scuzziato, M. R., Tenfen, D., & Fernandes, R. C. (2020) · IEEE Latin America Transactions · doi:10.1109/tla.2020.9381794 · Cited by 4

Forecasting of electricity prices, demand, and renewable resources

Lujano-Rojas, J. M., Dufo‐López, R., & Dominguez-Navarro, J. A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-823889-9.00003-5 · Cited by 4

Social efficiency forecasting based on social sustainability practices in the service supply chain

Nouri, F. A., Nikabadi, M. S., & Olfat, L. (2023) · Environment Development and Sustainability · doi:10.1007/s10668-023-03221-0 · Cited by 4

An ANFIS-Fuzzy Tree-GA Model for a Hospital’s Electricity Purchasing Decision-Making Process Integrated with Virtual Cost Concept

Panagiotou, D. K., & Dounis, A. I. (2023) · Sustainability · doi:10.3390/su15108419 · Cited by 4

Unlocking market secrets: Revealing wholesale electricity market price dynamics with a novel application of spectrum analysis

Maticka, M. J., & Mahmoud, T. S. (2023) · The Electricity Journal · doi:10.1016/j.tej.2023.107330 · Cited by 4

Electricity Price Forecasting based on Order Books: a differentiable optimization approach

Tschora, L., Guns, T., Pierre, E., Plantevit, M., & Robardet, C. (2023) · IEEE International Conference on Data Science and Advanced Analytics (DSAA) · doi:10.1109/dsaa60987.2023.10302542 · Cited by 4

A Predictive-Prescriptive Framework for Portable Energy Storage Operation in Real-Time Market

Chen, X., Chen, X., & Gao, F. (2024) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2024.3400172 · Cited by 4

A review of electricity price forecasting: The past, the present and the futurePreprint

Weron, R. (2014) · RePEc: Research Papers in Economics

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