Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
December 8, 2025EnergiesOpen Access

A Review of Recent Trends in Electricity Price Forecasting Using Deep Learning Techniques

View Full Paper
Ask AI
Bookmark
Share

Authors

TJTomasz Jasiński

Discussion

Loading...

Member takes

Overview

Review highlights advancements and research gaps in electricity price forecasting using deep learning methods and error metrics.

Key Points

  • Electricity price forecasting has evolved as deep learning methods become more prevalent, improving prediction accuracy.
  • The analysis covers numerous articles since 2023, focusing on deep learning neural networks for electricity markets.
  • Key findings reveal limitations in test set duration, often restricting them to just a few days.
  • Hybrid approaches that combine varied neural network architectures show promise in enhancing forecasting accuracy.

Cite This Study

Tomasz Jasiński (2025) studied this question.

synapsesocial.com/papers/694020e82d562116f28facbchttps://doi.org/10.3390/en18246422
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Data-Driven Techniques for Short-Term Electricity Price Forecasting through Novel Deep Learning Approaches with Attention Mechanisms2024 · 39 citations
  2. 2Hybrid Deep Learning Approaches for Accurate Electricity Price Forecasting: A Day-Ahead US Energy Market Analysis with Renewable Energy2025
  3. 3Forecasting Day-Ahead Electricity Prices using Technical Prediction Methods2024
  4. 4Enhancing Electricity Demand Forecasting Accuracy Through Hybrid Models and Deep Learning Techniques: A Systematic Literature Review2024
  5. 5Review of Methods and Models for Forecasting Electricity Consumption2025 · 32 citations