Optimal load dispatch of community microgrid with deep learning based solar power and load forecasting
L Wen, K Zhou, S Yang, X Lu - Energy, 2019 - Elsevier
A deep recurrent neural network with long short-term memory units (DRNN-LSTM) model is
developed to forecast aggregated power load and the photovoltaic (PV) power output in …
developed to forecast aggregated power load and the photovoltaic (PV) power output in …
National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?
As the volatility of electricity demand increases owing to climate change and electrification,
the importance of accurate peak load forecasting is increasing. Traditional peak load …
the importance of accurate peak load forecasting is increasing. Traditional peak load …
Issues with data quality for wind turbine condition monitoring and reliability analyses
In order to remain competitive, wind turbines must be reliable machines with efficient and
effective maintenance strategies. However, thus far, wind turbine reliability information has …
effective maintenance strategies. However, thus far, wind turbine reliability information has …
An improved seasonal GM (1, 1) model based on the HP filter for forecasting wind power generation in China
W Qian, J Wang - Energy, 2020 - Elsevier
With rapid development of wind power in China, it has become an integral part of the energy
structure, so it is of practical significance to forecast wind power generation accurately. As …
structure, so it is of practical significance to forecast wind power generation accurately. As …
Abnormal vibration detection of wind turbine based on temporal convolution network and multivariate coefficient of variation
A working wind turbine generates a large amount of multivariate time-series data, which
contain abundant operation state information and can predict impending anomalies. The …
contain abundant operation state information and can predict impending anomalies. The …
[HTML][HTML] Multi-target normal behaviour models for wind farm condition monitoring
A Meyer - Applied Energy, 2021 - Elsevier
The trend towards larger wind turbines and remote locations of wind farms fuels the demand
for automated condition monitoring strategies that can reduce the operating cost and avoid …
for automated condition monitoring strategies that can reduce the operating cost and avoid …
A multi-criteria decision making (MCDM) for renewable energy plants location selection in Vietnam under a fuzzy environment
In the context of increasing energy demands in Vietnam, and as a result of the limited supply
of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy …
of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy …
Wind turbines offshore foundations and connections to grid
F Manzano-Agugliaro, M Sánchez-Calero, A Alcayde… - Inventions, 2020 - mdpi.com
Most offshore wind farms built thus far are based on waters below 30 m deep, either using
big diameter steel monopiles or a gravity base. Now, offshore windfarms are starting to be …
big diameter steel monopiles or a gravity base. Now, offshore windfarms are starting to be …
Artificial intelligence and mathematical models of power grids driven by renewable energy sources: A survey
To face the impact of climate change in all dimensions of our society in the near future, the
European Union (EU) has established an ambitious target. Until 2050, the share of …
European Union (EU) has established an ambitious target. Until 2050, the share of …
[HTML][HTML] Use of new variables based on air temperature for forecasting day-ahead spot electricity prices using deep neural networks: A new approach
T Jasiński - Energy, 2020 - Elsevier
The paper presents a way of creating three new, innovative variables based on air
temperature to be used in forecasts of electricity demand and prices. The forecasting …
temperature to be used in forecasts of electricity demand and prices. The forecasting …