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Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …
renewable energy generation using machine learning (ML) and deep learning (DL) …
Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
Prediction of energy production level in large PV plants through AUTO-encoder based neural-network (AUTO-NN) with restricted Boltzmann feature extraction
In general, reliable PV generation prediction is required to increase complete control quality
and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV …
and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV …
Long short term memory–convolutional neural network based deep hybrid approach for solar irradiance forecasting
The volatile behavior of solar energy is the biggest challenge in its successful integration
with existing grid systems. Accurate global horizontal irradiance (GHI) forecasting can …
with existing grid systems. Accurate global horizontal irradiance (GHI) forecasting can …
A review on global solar radiation prediction with machine learning models in a comprehensive perspective
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …
for economic and environmental considerations. However, because solar-radiation …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models
The uncertainty associated with modeling and performance prediction of solar photovoltaic
systems could be easily and efficiently solved by artificial intelligence techniques. During the …
systems could be easily and efficiently solved by artificial intelligence techniques. During the …
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 …
Application and suitability analysis of the key technologies in nearly zero energy buildings in China
The energy consumption in buildings accounts for a significant proportion of total energy
and carbon emissions over the world. To reduce the building energy consumption and …
and carbon emissions over the world. To reduce the building energy consumption and …