Rooftop solar pv penetration impacts on distribution network and further growth factors—a comprehensive review
In order to meet the electricity needs of domestic or commercial buildings, solar energy is
more attractive than other renewable energy sources in terms of its simplicity of installation …
more attractive than other renewable energy sources in terms of its simplicity of installation …
Review of low voltage load forecasting: Methods, applications, and recommendations
The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
Photovoltaic power forecasting with a hybrid deep learning approach
G Li, S Xie, B Wang, J Xin, Y Li, S Du - IEEE access, 2020 - ieeexplore.ieee.org
Solar energy is the key to clean energy, which can generate large amounts of electricity for
the future smart grid. Unfortunately, the randomness and intermittency of solar energy …
the future smart grid. Unfortunately, the randomness and intermittency of solar energy …
[HTML][HTML] Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions
Integrating large proportions of intermittent renewable energy sources into electric grids is
challenging. A well-established approach aimed at addressing this difficulty involves the …
challenging. A well-established approach aimed at addressing this difficulty involves the …
A techno-economic sizing method for grid-connected household photovoltaic battery systems
Battery storage provides an effective solution to alleviate the burden of the intermittent
photovoltaic production on the grid and increase photovoltaic penetration in residential …
photovoltaic production on the grid and increase photovoltaic penetration in residential …
Short-term solar irradiance forecasting based on a novel Bayesian optimized deep Long Short-Term Memory neural network
Accurate forecasting is indispensable for improving solar renewables integration and
minimizing the effects of solar energy's intermittency. Existing research on time series solar …
minimizing the effects of solar energy's intermittency. Existing research on time series solar …
Recurrent neural networks based photovoltaic power forecasting approach
The intermittency of solar energy resources has brought a big challenge for the optimization
and planning of a future smart grid. To reduce the intermittency, an accurate prediction of …
and planning of a future smart grid. To reduce the intermittency, an accurate prediction of …
Benchmarking of solar irradiance nowcast performance derived from all-sky imagers
Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic
and concentrating solar thermal power plants. Accurate solar nowcasting becomes …
and concentrating solar thermal power plants. Accurate solar nowcasting becomes …
Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery
FJ Rodríguez-Benítez, M López-Cuesta… - Applied Energy, 2021 - Elsevier
This work proposes and evaluates methods for extending the forecasting horizon of all-sky
imager (ASI)-based solar radiation nowcasts and estimating the uncertainty of these …
imager (ASI)-based solar radiation nowcasts and estimating the uncertainty of these …
A model for evaluating the configuration and dispatch of PV plus battery power plants
An open-source model was developed to optimize energy storage operation for photovoltaic-
(PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the …
(PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the …