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 …
Machine learning based solar photovoltaic power forecasting: a review and comparison
J Gaboitaolelwe, AM Zungeru, A Yahya… - IEEE …, 2023 - ieeexplore.ieee.org
The growing interest in renewable energy and the falling prices of solar panels place solar
electricity in a favourable position for adoption. However, the high-rate adoption of …
electricity in a favourable position for adoption. However, the high-rate adoption of …
[HTML][HTML] Operational day-ahead solar power forecasting for aggregated PV systems with a varying spatial distribution
Accurate forecasts of the power production of distributed photovoltaic (PV) systems are
essential to support grid operation and enable a high PV penetration rate in the electricity …
essential to support grid operation and enable a high PV penetration rate in the electricity …
[HTML][HTML] A systematic analysis of meteorological variables for PV output power estimation
While the large-scale deployment of photovoltaics (PV) for generating electricity plays an
important role to mitigate global warming, the variability of PV output power poses …
important role to mitigate global warming, the variability of PV output power poses …
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 …
A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine …
Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence
(AI) combined with Machine Learning (ML) has introduced a new era of remarkable …
(AI) combined with Machine Learning (ML) has introduced a new era of remarkable …
On the trade-off between environmental and economic objectives in community energy storage operational optimization
The need to limit climate change has led to policies that aim for the reduction of greenhouse
gas emissions. Often, a trade-off exists between reducing emissions and associated costs. In …
gas emissions. Often, a trade-off exists between reducing emissions and associated costs. In …
Forecasting hourly day-ahead solar photovoltaic power generation by assembling a new adaptive multivariate data analysis with a long short-term memory network
Accurate multi-step PV power forecasting is a challenging task because of complex time
series and error buildup in muti-step forecasts. This work is based on developing a …
series and error buildup in muti-step forecasts. This work is based on developing a …
[HTML][HTML] Regulation strategies for mitigating voltage fluctuations induced by photovoltaic solar systems in an urban low voltage grid
LR Visser, EMB Schuurmans, TA AlSkaif… - International Journal of …, 2022 - Elsevier
Transient clouds cause rapid changes in the power output of Photovoltaic (PV) solar
systems. These ramp rates may lead to power quality problems, such as voltage fluctuations …
systems. These ramp rates may lead to power quality problems, such as voltage fluctuations …
Principal component analysis and machine learning approaches for photovoltaic power prediction: A comparative study
S Chahboun, M Maaroufi - Applied Sciences, 2021 - mdpi.com
Nowadays, in the context of the industrial revolution 4.0, considerable volumes of data are
being generated continuously from intelligent sensors and connected objects. The proper …
being generated continuously from intelligent sensors and connected objects. The proper …