A systematic literature review on machine learning for electricity market agent-based models
AJM Kell, AS McGough… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
The electricity market has a vital role to play in the decarbonisation of the energy system.
However, the electricity market is made up of many different variables and data inputs …
However, the electricity market is made up of many different variables and data inputs …
Hourly Solar Power Forecasting Using Optimized Extreme Learning Machine
Due to the many challenges that energy is currently witnessing, it has become necessary to
rely on unlimited renewable energies such as solar ones. However, its discontinuous nature …
rely on unlimited renewable energies such as solar ones. However, its discontinuous nature …
Optimized extreme learning machine using genetic algorithm for short-term wind power prediction
Through the much defiance facing energy today, it has become necessary to rely on wind
energy as a source of unlimited renewable energies. However, energy planning and …
energy as a source of unlimited renewable energies. However, energy planning and …
Wind Power Forecasting Model Based on Extreme Learning Machine and Time series
I Mansoury, D El Bourakadi… - … Computing in Data …, 2021 - ieeexplore.ieee.org
Faced with current energy challenges, renewable energies designate a set of means of
producing energy from resources such as wind which is unlimited on a human scale. But its …
producing energy from resources such as wind which is unlimited on a human scale. But its …
[PDF][PDF] Power Management Simulation of a Renewable Energy Microrid Using Coloured Petri Nets
In this study, an analysis of the energy comsumption and storage was carried out in a
microgrid composed of renewable resources (photovoltaic and wind energy generation) …
microgrid composed of renewable resources (photovoltaic and wind energy generation) …