A feature extraction-and ranking-based framework for electricity spot price forecasting using a hybrid deep neural network
Z Shao, Q Zheng, C Liu, S Gao, G Wang… - Electric Power Systems …, 2021 - Elsevier
In deregulated electricity markets, reliable electricity market price forecasting is the
foundation for making the bidding strategy, operating dispatch control, and hedging volatility …
foundation for making the bidding strategy, operating dispatch control, and hedging volatility …
Day-ahead electricity price forecasting employing a novel hybrid frame of deep learning methods: A case study in NSW, Australia
YQ Tan, YX Shen, XY Yu, X Lu - Electric Power Systems Research, 2023 - Elsevier
Day-ahead electricity price forecasting plays a vital role in electricity markets under
liberalization and deregulation, which can provide references for participants in bidding …
liberalization and deregulation, which can provide references for participants in bidding …
A deep learning based hybrid framework for day-ahead electricity price forecasting
R Zhang, G Li, Z Ma - IEEE Access, 2020 - ieeexplore.ieee.org
With the deregulation of the electric energy industry, accurate electricity price forecasting
(EPF) is increasingly significant to market participants' bidding strategies and uncertainty risk …
(EPF) is increasingly significant to market participants' bidding strategies and uncertainty risk …
A hybrid model based on bidirectional long short-term memory neural network and Catboost for short-term electricity spot price forecasting
Electricity price forecasting plays a crucial role in a liberalised electricity market. Generally
speaking, long-term electricity price is widely utilised for investment profitability analysis, grid …
speaking, long-term electricity price is widely utilised for investment profitability analysis, grid …
GHTnet: Tri-Branch deep learning network for real-time electricity price forecasting
H Yang, KR Schell - Energy, 2022 - Elsevier
A highly accurate electricity price prediction model is of the utmost importance for multiple
power systems tasks, such as generation dispatch and bidding. Due to the liberalization of …
power systems tasks, such as generation dispatch and bidding. Due to the liberalization of …
Deep learning for day‐ahead electricity price forecasting
Deregulation exposes the inherent volatility of the electricity price. Accurate electricity price
forecasting (EPF) could help the market participants to hedge against the price movements …
forecasting (EPF) could help the market participants to hedge against the price movements …
Short term electricity spot price forecasting using catboost and bidirectional long short term memory neural network
Electricity price forecasting plays a crucial role in liberalized electricity markets. Generally
speaking, short term electricity price forecasting is essential for electricity providers to adjust …
speaking, short term electricity price forecasting is essential for electricity providers to adjust …
An optimized deep learning approach for forecasting day-ahead electricity prices
ÇB Bozlak, CF Yaşar - Electric Power Systems Research, 2024 - Elsevier
Electricity price forecasting is essential for reliable and cost-effective operations in the power
industry. However, the complex and nonlinear structure of the electricity price series …
industry. However, the complex and nonlinear structure of the electricity price series …
[HTML][HTML] Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark
While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …
A hybrid framework for day-ahead electricity spot-price forecasting: A case study in China
S Huang, J Shi, B Wang, N An, L Li, X Hou, C Wang… - Applied Energy, 2024 - Elsevier
The electricity price volatility can be aggravated by multiple factors, such as load pattern, line
limit, regulations, renewable energy generations, weather conditions and holiday. Due to …
limit, regulations, renewable energy generations, weather conditions and holiday. Due to …