Cover Image

Optimal day-ahead offering strategy for large producers based on market price response learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Alcántara, António, Ruiz, Carlos
Format:	Preprint
Published:	2022
Subjects:	Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A practical scenario generation method for electricity prices on day-ahead and intraday spot markets
by: Papadimitriou, Chrysanthi, et al.
Published: (2024)

From day-ahead to mid and long-term horizons with econometric electricity price forecasting models
by: Ghelasi, Paul, et al.
Published: (2024)

Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression
by: Lipiecki, Arkadiusz, et al.
Published: (2024)

Scenario generation of intraday electricity price paths for optimal trading in continuous markets
by: Puć, Andrzej, et al.
Published: (2026)

A representation-learning approach for insurance pricing with images
by: Blier-Wong, Christopher, et al.
Published: (2023)

Corrected Support Vector Regression for intraday point forecasting of prices in the continuous power market
by: Puć, Andrzej, et al.
Published: (2024)

Saving for sunny days: The impact of climate (change) on consumer prices in the euro area
by: Rodrigues, Paulo M. M., et al.
Published: (2024)

Optimal bidding in hourly and quarter-hourly electricity price auctions: trading large volumes of power with market impact and transaction costs
by: Narajewski, Michał, et al.
Published: (2021)

Identification of socioeconomic factors influencing global food price security using machine learning
by: Shan, Shan
Published: (2024)

A divide-and-conquer approach for spatio-temporal analysis of large house price data from Greater London
by: Gupta, Kapil, et al.
Published: (2024)

Mapping the causal structure of price formation in Texas's transitioning electricity market
by: Madadkhani, Shiva, et al.
Published: (2026)

Surface temperature extremes produced by huge machine learning hindcasts of summer 2023
by: Risser, Mark, et al.
Published: (2026)

Probabilistic intraday electricity price forecasting using generative machine learning
by: Chen, Jieyu, et al.
Published: (2025)

Certification of MPC-based zonal controller security properties using accuracy-aware machine learning proxies
by: Houdouin, Pierre, et al.
Published: (2024)

Optimal pursuit strategies for multi‐pursuer single‐evader games based on cooperative tracking
by: Yinglu Zhou, et al.
Published: (2024)

Adaptive probabilistic forecasting of French electricity spot prices
by: Dutot, Grégoire, et al.
Published: (2024)

Multifractal behavior of price changes in the Green Bonds funds
by: Barbosa, Wenderson Gomes, et al.
Published: (2025)

An adaptive standardisation methodology for Day-Ahead electricity price forecasting
by: Sebastián, Carlos, et al.
Published: (2023)

Using large language models to produce literature reviews: Usages and systematic biases of microphysics parametrizations in 2699 publications
by: Zhang, Tianhang, et al.
Published: (2025)

Bayesian Optimal Phase II design with optimised stopping boundaries and response-adaptive randomisation
by: Fitchett, Connor, et al.
Published: (2025)

Expectile regression averaging method for probabilistic forecasting of electricity prices
by: Janczura, Joanna
Published: (2024)

Regularization for electricity price forecasting
by: Uniejewski, Bartosz
Published: (2024)

Estimating the Causal Effect of Redlining on Present-day Air Pollution
by: Zhou, Xiaodan, et al.
Published: (2025)

Precrop Payoffs: Causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets
by: Kluger, Dan M., et al.
Published: (2025)

Optimising pandemic response through vaccination strategies using neural networks
by: Zhai, Chang, et al.
Published: (2025)

Optimal bidding in multiperiod day-ahead electricity markets assuming non-uniform uncertainty of clearing prices
by: Csercsik, Dávid, et al.
Published: (2025)

Variational Bayes latent class approach for EHR-based phenotyping with large real-world data
by: Buckley, Brian, et al.
Published: (2023)

Towards the use of multiple ROIs for radiomics-based survival modelling: finding a strategy of aggregating lesions
by: Wilk, Agata Małgorzata, et al.
Published: (2024)

Microlearning strategy in the promotion of motivation and learning outcomes in software project management
by: Gloria P. Gasca‐Hurtado, et al.
Published: (2024)

Optimal Experimental Design for Microplastics Sampling Experiments
by: Aquino-López, Marco A., et al.
Published: (2025)

Estimation methods for estimands using the treatment policy strategy; a simulation study based on the PIONEER 1 Trial
by: Bell, James, et al.
Published: (2024)

The day after mowing: Time and type of mowing influence grassland arthropods
by: Johanna L. Berger, et al.
Published: (2024)

Similarities among top one day batters: physics-based quantification
by: Patra, Dipak
Published: (2024)

Evacuation decisions in response to natural disasters: Insights from a large-scale social media survey
by: Maas, Paige, et al.
Published: (2020)

Agricultural intensification indirectly reshapes bee–plant interaction networks through shifts in bee functional traits
by: Domingo Cano, et al.
Published: (2025)

A new moment-independent uncertainty importance measure based on cumulative residual entropy for developing uncertainty reduction strategies
by: Chen, Shi-Shun, et al.
Published: (2024)

Improving ex ante accuracy assessment in predicting house price dispersion: evidence from the USA
by: Chwila, Adam, et al.
Published: (2025)

Predicting the volatility of major energy commodity prices: the dynamic persistence model
by: Barunik, Jozef, et al.
Published: (2024)

Deep learning‐based postprocessing for hourly temperature forecasting
by: Li Zhou, et al.
Published: (2024)

Rank-based transfer learning for high-dimensional survival data with application to sepsis data
by: Qiao, Nan, et al.
Published: (2025)