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 …
Design of input vector for day-ahead price forecasting of electricity markets
N Amjady, A Daraeepour - Expert Systems with Applications, 2009 - Elsevier
In new deregulated electricity market, price forecasts have become a fundamental input to
an energy company's decision making and strategy development process. However, the …
an energy company's decision making and strategy development process. However, the …
Predicting long-term electricity prices using modified support vector regression method
The energy market operates in a highly deregulated and competitive environment, where
electricity price plays a crucial role. Forecasting electricity prices presents a significant …
electricity price plays a crucial role. Forecasting electricity prices presents a significant …
A hybrid model for electricity price forecasting based on least square support vector machines with combined kernel
With the continuous development of the global electricity market, the electricity market needs
the electricity price forecasting result to be accurate, and electricity price forecasting also has …
the electricity price forecasting result to be accurate, and electricity price forecasting also has …
Day-ahead price forecasting of electricity markets by mutual information technique and cascaded neuro-evolutionary algorithm
In a competitive electricity market, price forecasts are important for market participants.
However, electricity price is a complex signal due to its nonlinearity, nonstationarity, and …
However, electricity price is a complex signal due to its nonlinearity, nonstationarity, and …
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 …
Recent development in electricity price forecasting based on computational intelligence techniques in deregulated power market
The development of artificial intelligence (AI) based techniques for electricity price
forecasting (EPF) provides essential information to electricity market participants and …
forecasting (EPF) provides essential information to electricity market participants and …
Electricity price forecasting using neural networks with an improved iterative training algorithm
M Gholipour Khajeh, A Maleki, MA Rosen… - … Journal of Ambient …, 2018 - Taylor & Francis
In a competitive electricity market, the forecasting of energy prices is an important activity for
all market participants either for developing bidding strategies or for making investment …
all market participants either for developing bidding strategies or for making investment …
Day-ahead electricity price forecasting by modified relief algorithm and hybrid neural network
In a power market, the price of electricity is the most important signal to all market
participants. However, electricity price forecast is a complex task due to non-linearity, non …
participants. However, electricity price forecast is a complex task due to non-linearity, non …
A neural network approach to day-ahead deregulated electricity market prices classification
S Anbazhagan, N Kumarappan - Electric Power Systems Research, 2012 - Elsevier
This paper proposes a day-ahead electricity price classification that could be realized using
three-layered feed forward neural network (FFNN), cascade-forward neural network (CFNN) …
three-layered feed forward neural network (FFNN), cascade-forward neural network (CFNN) …