Traditionally, short-term electricity price forecasting has been essential for utilities and
generation companies. However, the deregulation of electricity markets created a …

Due to recent technical improvements, the smart grid has become a feasible platform for
electricity market participants to successfully regulate their bidding process based on …

The increased integration of wind power into the electric grid, as nowadays occurs in
Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction …

This paper presents an artificial neural network approach for short-term wind power
forecasting in Portugal. The increased integration of wind power into the electric grid, as …

In this paper, a hybrid electricity price forecasting method which is composed of two-stage
feature selection method and optimized adaptive neuro-fuzzy inference system (ANFIS) …

Short-term electricity price forecasting has become a crucial issue in the power markets,
since it forms the basis of maximising profits for the market participants. This paper presents …

Determination of the output power of wind generators is always associated with some
uncertainties due to wind speed and other weather parameters variation, and accurate short …

Load and price forecasting are key challenges for current electricity market participants.
Load and price in electricity markets have complex peculiarities, such as nonlinearity, being …

Consumers are often blamed for not making necessary investments in energy-efficient
durables despite that these investments have positive net present value (NPV). Several …

This paper proposed a price forecasting system for electric market participants to reduce the
risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal …