Modeling and forecasting the electricity clearing price: A novel BELM based pattern classification framework and a comparative analytic study on multi-layer BELM …
With the deregulation of power market and the increasing penetration of renewable energy,
the core role of demand side management (DSM) has become even more prominent. In this …
the core role of demand side management (DSM) has become even more prominent. In this …
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 …
Short-term electricity price forecasting based on similarity day screening, two-layer decomposition technique and Bi-LSTM neural network
K Wang, M Yu, D Niu, Y Liang, S Peng, X Xu - Applied Soft Computing, 2023 - Elsevier
Electricity price forecasting (EPF) has been challenged by the widespread grid integration of
renewable energy (RE), so it is critical to develop a highly accurate and reliable EPF model …
renewable energy (RE), so it is critical to develop a highly accurate and reliable EPF model …
[HTML][HTML] Short-term electricity price forecasting by employing ensemble empirical mode decomposition and extreme learning machine
Day-ahead electricity price forecasting plays a critical role in balancing energy consumption
and generation, optimizing the decisions of electricity market participants, formulating …
and generation, optimizing the decisions of electricity market participants, formulating …
Electricity price classification using extreme learning machines
Forecasting electricity prices has been a widely investigated research issue in the
deregulated power market scenario. High price volatilities, price spikes caused by a number …
deregulated power market scenario. High price volatilities, price spikes caused by a number …
A new electricity price prediction strategy using mutual information-based SVM-RFE classification
Z Shao, SL Yang, F Gao, KL Zhou, P Lin - Renewable and Sustainable …, 2017 - Elsevier
Owing to the central role in electricity market operation, researchers have long sought to
investigate the price responsiveness of both electricity supply and consumption sides. From …
investigate the price responsiveness of both electricity supply and consumption sides. From …
Short-term electricity price forecasting and classification in smart grids using optimized multikernel extreme learning machine
Short-term electricity price forecasting in deregulated electricity markets has been studied
extensively in recent years but without significant reduction in price forecasting errors. Also …
extensively in recent years but without significant reduction in price forecasting errors. Also …
[HTML][HTML] Electricity market price forecasting using ELM and Bootstrap analysis: A case study of the German and Finnish Day-Ahead markets
S Loizidis, A Kyprianou, GE Georghiou - Applied Energy, 2024 - Elsevier
Electricity market liberalization and the absence of cost-efficient energy storage
technologies have led to the transformation of state-owned electricity companies into …
technologies have led to the transformation of state-owned electricity companies into …
A novel machine learning-based electricity price forecasting model based on optimal model selection strategy
Current electricity price forecasting models rely on only simple hybridizations of data
preprocessing and optimization methods while ignoring the significance of adaptive data …
preprocessing and optimization methods while ignoring the significance of adaptive data …
Wavelet transform and Kernel-based extreme learning machine for electricity price forecasting
Y Zhang, C Li, L Li - Energy Systems, 2018 - Springer
In deregulated electricity markets, sophisticated factors, such as the weather, the season,
high frequencies, the presence of jumps and the relationship between electricity loads and …
high frequencies, the presence of jumps and the relationship between electricity loads and …