Energy generation forecasting: elevating performance with machine and deep learning
Abstract Distribution System Operators (DSOs) and Aggregators benefit from novel Energy
Generation Forecasting (EGF) approaches. Improved forecasting accuracy may make it …
Generation Forecasting (EGF) approaches. Improved forecasting accuracy may make it …
Energy Forecasting: A Comprehensive Review of Techniques and Technologies
Distribution System Operators (DSOs) and Aggregators benefit from novel energy
forecasting (EF) approaches. Improved forecasting accuracy may make it easier to deal with …
forecasting (EF) approaches. Improved forecasting accuracy may make it easier to deal with …
Introducing a novel approach in one-step ahead energy load forecasting
Energy sector stakeholders, such as Distribution System Operators (DSO) or Aggregators
take advantage of improved forecasting methods. Increased forecasting accuracy facilitates …
take advantage of improved forecasting methods. Increased forecasting accuracy facilitates …
Energy forecasting in smart grid systems: recent advancements in probabilistic deep learning
Energy forecasting plays a vital role in mitigating challenges in data rich smart grid (SG)
systems involving various applications such as demand‐side management, load shedding …
systems involving various applications such as demand‐side management, load shedding …
Energy forecasting in smart grid systems: A review of the state-of-the-art techniques
Energy forecasting has a vital role to play in smart grid (SG) systems involving various
applications such as demand-side management, load shedding, and optimum dispatch …
applications such as demand-side management, load shedding, and optimum dispatch …
Comparison of short-term electrical load forecasting methods for different building types
The transformation of the energy system towards volatile renewable generation, increases
the need to manage decentralized flexibilities more efficiently. For this, precise forecasting of …
the need to manage decentralized flexibilities more efficiently. For this, precise forecasting of …
A novel accurate and fast converging deep learning-based model for electrical energy consumption forecasting in a smart grid
Energy consumption forecasting is of prime importance for the restructured environment of
energy management in the electricity market. Accurate energy consumption forecasting is …
energy management in the electricity market. Accurate energy consumption forecasting is …
A hybrid approach for energy consumption forecasting with a new feature engineering and optimization framework in smart grid
Electric energy consumption forecasting enables distribution system operators to perform
efficient energy management by flexibly engaging energy consumers under the intelligent …
efficient energy management by flexibly engaging energy consumers under the intelligent …
BiGTA-Net: A hybrid deep learning-based electrical energy forecasting model for building energy management systems
The growth of urban areas and the management of energy resources highlight the need for
precise short-term load forecasting (STLF) in energy management systems to improve …
precise short-term load forecasting (STLF) in energy management systems to improve …
Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions
Developing a reliable and robust algorithm for accurate energy demand prediction is
indispensable for utility companies for various applications, eg, power dispatching, market …
indispensable for utility companies for various applications, eg, power dispatching, market …