Application of big data and machine learning in smart grid, and associated security concerns: A review
This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …
learning in the electrical power grid introduced through the emergence of the next …
Neuro-fuzzy resource forecast in site suitability assessment for wind and solar energy: A mini review
PA Adedeji, SA Akinlabi, N Madushele… - Journal of Cleaner …, 2020 - Elsevier
Site suitability problems in renewable energy studies have taken a new turn since the
advent of geographical information system (GIS). GIS has been used for site suitability …
advent of geographical information system (GIS). GIS has been used for site suitability …
Deep learning based ensemble approach for probabilistic wind power forecasting
Due to the economic and environmental benefits, wind power is becoming one of the more
promising supplements for electric power generation. However, the uncertainty exhibited in …
promising supplements for electric power generation. However, the uncertainty exhibited in …
Prediction of photovoltaic power output based on similar day analysis, genetic algorithm and extreme learning machine
Y Zhou, N Zhou, L Gong, M Jiang - Energy, 2020 - Elsevier
Recently, many machine learning techniques have been successfully employed in
photovoltaic (PV) power output prediction because of their strong non-linear regression …
photovoltaic (PV) power output prediction because of their strong non-linear regression …
Application of extreme learning machine for short term output power forecasting of three grid-connected PV systems
The power output (PO) of a photovoltaic (PV) system is highly variable because of its
dependence on solar irradiance and other meteorological factors. Hence, accurate PO …
dependence on solar irradiance and other meteorological factors. Hence, accurate PO …
Uncertainty analysis of wind power probability density forecasting based on cubic spline interpolation and support vector quantile regression
Accurate forecasting of wind power plays an important role in an effective and reliable power
system. However, the fact of non-schedulability and fluctuation of wind power significantly …
system. However, the fact of non-schedulability and fluctuation of wind power significantly …
Single-hidden layer neural networks for forecasting intermittent demand
Managing intermittent demand is a vital task in several industrial contexts, and good
forecasting ability is a fundamental prerequisite for an efficient inventory control system in …
forecasting ability is a fundamental prerequisite for an efficient inventory control system in …
Wind power forecasting methods based on deep learning: A survey
X Deng, H Shao, C Hu, D Jiang… - Computer Modeling in …, 2020 - ingentaconnect.com
Accurate wind power forecasting in wind farm can effectively reduce the enormous impact
on grid operation safety when high permeability intermittent power supply is connected to …
on grid operation safety when high permeability intermittent power supply is connected to …
[HTML][HTML] Wind power: Existing status, achievements and government's initiative towards renewable power dominating India
Wind power has shown enormous potential in capacity addition and substantial use
throughout the world during the last few decades. From the very last era of the 1990s, wind …
throughout the world during the last few decades. From the very last era of the 1990s, wind …
Extreme learning machine based prediction of daily dew point temperature
K Mohammadi, S Shamshirband, S Motamedi… - … and Electronics in …, 2015 - Elsevier
The dew point temperature is a significant element particularly required in various
hydrological, climatological and agronomical related researches. This study proposes an …
hydrological, climatological and agronomical related researches. This study proposes an …