A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …
renewable energy sources (RESs), energy storage devices, and load management …
A review of deep learning for renewable energy forecasting
As renewable energy becomes increasingly popular in the global electric energy grid,
improving the accuracy of renewable energy forecasting is critical to power system planning …
improving the accuracy of renewable energy forecasting is critical to power system planning …
Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks
Accurate and reliable solar irradiance forecasting can bring significant benefits for managing
electricity generation and distributing modern smart grid. However, the characteristics of …
electricity generation and distributing modern smart grid. However, the characteristics of …
Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction …
J Qu, Z Qian, Y Pei - Energy, 2021 - Elsevier
Accurate forecasting of photovoltaic power plays a pivotal role in the integration, operation,
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
Hourly stepwise forecasting for solar irradiance using integrated hybrid models CNN-LSTM-MLP combined with error correction and VMD
Accurate and reliable solar irradiance forecasting is critical for distribution planning and
modern smart grid management and dispatch. However, due to the time series of solar …
modern smart grid management and dispatch. However, due to the time series of solar …
Ridge regression ensemble of machine learning models applied to solar and wind forecasting in Brazil and Spain
TC Carneiro, PAC Rocha, PCM Carvalho… - Applied Energy, 2022 - Elsevier
In recent years, with the rapid development of wind and solar power generation, some
problems arise gradually and are often inherent to intermittency. Currently, one of the …
problems arise gradually and are often inherent to intermittency. Currently, one of the …
The value of solar forecasts and the cost of their errors: A review
Despite the advances in solar forecasting methods, and their ever-increasing accuracy, little
is known about their value for real applications, eg, bidding in the electricity market, power …
is known about their value for real applications, eg, bidding in the electricity market, power …
[HTML][HTML] Advances in solar forecasting: Computer vision with deep learning
Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …
It allows power systems to address the intermittency of the energy supply at different …
[HTML][HTML] Different conventional and soft computing MPPT techniques for solar PV systems with high step-up boost converters: A comprehensive analysis
CHH Basha, C Rani - Energies, 2020 - mdpi.com
Solar photovoltaic (PV) systems are attracting a huge focus in the current energy scenario.
Various maximum power point tracking (MPPT) methods are used in solar PV systems in …
Various maximum power point tracking (MPPT) methods are used in solar PV systems in …
Optimal capacity configuration of the wind-photovoltaic-storage hybrid power system based on gravity energy storage system
H Hou, T Xu, X Wu, H Wang, A Tang, Y Chen - Applied energy, 2020 - Elsevier
Reasonable capacity configuration of wind farm, photovoltaic power station and energy
storage system is the premise to ensure the economy of wind-photovoltaic-storage hybrid …
storage system is the premise to ensure the economy of wind-photovoltaic-storage hybrid …