PV power forecasting based on data-driven models: a review
Accurate PV power forecasting techniques are a prerequisite for the optimal management of
the grid and its stability. This paper presents a review of the recent developments in the field …
the grid and its stability. This paper presents a review of the recent developments in the field …
Hybridization of hybrid structures for time series forecasting: A review
Achieving the desired accuracy in time series forecasting has become a binding domain,
and develo** a forecasting framework with a high degree of accuracy is one of the most …
and develo** a forecasting framework with a high degree of accuracy is one of the most …
An integrated framework of Bi-directional long-short term memory (BiLSTM) based on sine cosine algorithm for hourly solar radiation forecasting
T Peng, C Zhang, J Zhou, MS Nazir - Energy, 2021 - Elsevier
Accurate and reliable solar radiation forecasting is of great significance for the management
and utilization of solar energy. This study proposes a deep learning model based on Bi …
and utilization of solar energy. This study proposes a deep learning model based on Bi …
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 …
Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions
The nature of streamflow in the basins is stochastic and complex making it difficult to make
an accurate prediction about the future river flows. Recently, artificial neural-based deep …
an accurate prediction about the future river flows. Recently, artificial neural-based deep …
Completed review of various solar power forecasting techniques considering different viewpoints
Solar power has rapidly become an increasingly important energy source in many countries
over recent years; however, the intermittent nature of photovoltaic (PV) power generation …
over recent years; however, the intermittent nature of photovoltaic (PV) power generation …
Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting
Accurate forecasting of rainfall is extremely important due to its complex nature and
enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant …
enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant …
Potential assessment of the TVF-EMD algorithm in forecasting hourly global solar radiation: Review and case studies
Accurate and effective forecasting of short-term global solar radiation is critical for the
development of photovoltaic systems, particularly for integration into existing grid systems …
development of photovoltaic systems, particularly for integration into existing grid systems …
Modeling and predicting the electricity production in hydropower using conjunction of wavelet transform, long short-term memory and random forest models
M Zolfaghari, MR Golabi - Renewable Energy, 2021 - Elsevier
Electricity is an important pillar for the economic growth and the development of societies.
Surveying and predicting the electricity production (EP) is a valuable factor in the hands of …
Surveying and predicting the electricity production (EP) is a valuable factor in the hands of …
New double decomposition deep learning methods for river water level forecasting
Forecasting river water levels or streamflow water levels (SWL) is vital to optimising the
practical and sustainable use of available water resources. We propose a new deep …
practical and sustainable use of available water resources. We propose a new deep …