Machine learning in energy economics and finance: A review
Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …
energy economics and finance. We critically review the burgeoning literature dedicated to …
Recent advances in electricity price forecasting: A review of probabilistic forecasting
Since the inception of competitive power markets two decades ago, electricity price
forecasting (EPF) has gradually become a fundamental process for energy companies' …
forecasting (EPF) has gradually become a fundamental process for energy companies' …
Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm
Electricity price forecasting is a key aspect for market participants to maximize their
economic efficiency in deregulated markets. Nevertheless, due to its non-linearity and non …
economic efficiency in deregulated markets. Nevertheless, due to its non-linearity and non …
Forecasting methods in energy planning models
KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
[HTML][HTML] Electricity price forecasting: A review of the state-of-the-art with a look into the future
R Weron - International journal of forecasting, 2014 - Elsevier
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 …
last 15 years, with varying degrees of success. This review article aims to explain the …
Electricity price forecasting using recurrent neural networks
Accurate electricity price forecasting has become a substantial requirement since the
liberalization of the electricity markets. Due to the challenging nature of electricity prices …
liberalization of the electricity markets. Due to the challenging nature of electricity prices …
Energy models for demand forecasting—A review
Energy is vital for sustainable development of any nation–be it social, economic or
environment. In the past decade energy consumption has increased exponentially globally …
environment. In the past decade energy consumption has increased exponentially globally …
Forecast the electricity price of US using a wavelet transform-based hybrid model
W Qiao, Z Yang - Energy, 2020 - Elsevier
Wavelet transform (WT), as a data preprocessing algorithm, has been widely applied in
electricity price forecasting. However, this deterministic-based algorithm does not present …
electricity price forecasting. However, this deterministic-based algorithm does not present …
Day-ahead electricity price forecasting via the application of artificial neural network based models
Traditionally, short-term electricity price forecasting has been essential for utilities and
generation companies. However, the deregulation of electricity markets created a …
generation companies. However, the deregulation of electricity markets created a …
Neural network based optimization approach for energy demand prediction in smart grid
Energy usage and demand forecasting is an essential and complex task in real time
implementation. Proper coordination is required between the consumer and power …
implementation. Proper coordination is required between the consumer and power …