Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …

Since the inception of competitive power markets two decades ago, electricity price
forecasting (EPF) has gradually become a fundamental process for energy companies' …

To a large extent, electricity price prediction is a daunting task because it depends on
factors, such as weather, fuel, load and bidding strategies etc. Those features generate a lot …

Accurate electricity price forecasts is the common concern of market participants. With the
integration of high penetration of wind and solar energy resources into the power system …

A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the
last 15 years, with varying degrees of success. This review article aims to explain the …

Electric power, as an efficient and clean energy, has considerable importance in industries
and human lives. Electricity price is becoming increasingly crucial for balancing electricity …

Electricity prices have rather complex features such as high volatility, high frequency,
nonlinearity, mean reversion and non-stationarity that make forecasting very difficult …

Wind speed interval prediction is one of the most elusive and long-standing challenges in
wind power production. As a data source with intermittent and fluctuant characteristics, wind …

Wavelet transform (WT), as a data preprocessing algorithm, has been widely applied in
electricity price forecasting. However, this deterministic-based algorithm does not present …

Prediction of photovoltaic power is a significant research area using different forecasting
techniques mitigating the effects of the uncertainty of the photovoltaic generation …