Deep learning in smart grid technology: A review of recent advancements and future prospects
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …
a promising landscape for high grid reliability and efficient energy management. This …
[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 …
Short-term photovoltaic power forecasting based on long short term memory neural network and attention mechanism
Photovoltaic power generation forecasting is an important topic in the field of sustainable
power system design, energy conversion management, and smart grid construction …
power system design, energy conversion management, and smart grid construction …
An improved moth-flame optimization algorithm for support vector machine prediction of photovoltaic power generation
GQ Lin, LL Li, ML Tseng, HM Liu, DD Yuan… - Journal of Cleaner …, 2020 - Elsevier
With the expansion of grid-connected solar power generation, the variability of photovoltaic
power generation has become increasingly pronounced. Accurate photovoltaic output …
power generation has become increasingly pronounced. Accurate photovoltaic output …
Multi-step short-term power consumption forecasting with a hybrid deep learning strategy
Electric power consumption short-term forecasting for individual households is an important
and challenging topic in the fields of AI-enhanced energy saving, smart grid planning …
and challenging topic in the fields of AI-enhanced energy saving, smart grid planning …
Review of power system impacts at high PV penetration Part II: Potential solutions and the way forward
Issues and challenges of integrating intermittent renewable energy from large photovoltaic
(PV) systems have been a significant area of study. Numerous research works have …
(PV) systems have been a significant area of study. Numerous research works have …
Deep learning based multistep solar forecasting for PV ramp-rate control using sky images
Solar forecasting is one of the most promising approaches to address the intermittent
photovoltaic (PV) power generation by providing predictions before upcoming ramp events …
photovoltaic (PV) power generation by providing predictions before upcoming ramp events …
Inertia estimation in modern power system: A comprehensive review
The worldwide motivation to use renewable energy sources and power electronics
interfaced electric drive loads has not only reduced the power system inertia constant but …
interfaced electric drive loads has not only reduced the power system inertia constant but …
A novel adaptive power smoothing approach for PV power plant with hybrid energy storage system
Clouds passing over solar photovoltaic (PV) power system causes power fluctuations, which
contributes to power quality issues. Power fluctuations are usually compensated by an …
contributes to power quality issues. Power fluctuations are usually compensated by an …
A graph neural network based deep learning predictor for spatio-temporal group solar irradiance forecasting
The fast growth of photovoltaic (PV) power generation raises the concern of grid instability
due to its intermittent nature. Solar irradiance forecasting is becoming an effective way to …
due to its intermittent nature. Solar irradiance forecasting is becoming an effective way to …