[HTML][HTML] Systematic review on impact of different irradiance forecasting techniques for solar energy prediction
K Sudharshan, C Naveen, P Vishnuram… - Energies, 2022 - mdpi.com
As non-renewable energy sources are in the verge of exhaustion, the entire world turns
towards renewable sources to fill its energy demand. In the near future, solar energy will be …
towards renewable sources to fill its energy demand. In the near future, solar energy will be …
[HTML][HTML] Solar radiation forecasting using machine learning and ensemble feature selection
ES Solano, P Dehghanian, CM Affonso - Energies, 2022 - mdpi.com
Accurate solar radiation forecasting is essential to operate power systems safely under high
shares of photovoltaic generation. This paper compares the performance of several machine …
shares of photovoltaic generation. This paper compares the performance of several machine …
A robust auto encoder-gated recurrent unit (AE-GRU) based deep learning approach for short term solar power forecasting
The increasing presence of solar power plants shows its potency as one of the key
renewable energy resource to fulfill energy needs of the community. This increasing …
renewable energy resource to fulfill energy needs of the community. This increasing …
A hybrid spiking neurons embedded lstm network for multivariate time series learning under concept-drift environment
Complicated temporal patterns can provide important information for accurate time series
forecasting. Existing long short-term memory (LSTM) model with attention mechanism have …
forecasting. Existing long short-term memory (LSTM) model with attention mechanism have …
Execution of synthetic Bayesian model average for solar energy forecasting
O Abedinia, M Bagheri - IET Renewable Power Generation, 2022 - Wiley Online Library
Accurate photovoltaic (PV) forecasting is quite crucial in planning and in the regular
operation of power system. Stochastic habit along with the high risks in PV signal uncertainty …
operation of power system. Stochastic habit along with the high risks in PV signal uncertainty …
Unleashing deep neural network full potential for solar radiation forecasting in a new geographic location with historical data scarcity: a transfer learning approach
More grid-connected solar thermal and photovoltaic power plants are coming online every
year, which necessitates precise irradiance forecasters for plant management. A major …
year, which necessitates precise irradiance forecasters for plant management. A major …
[HTML][HTML] Inter-hour forecast of solar radiation based on long short-term memory with attention mechanism and genetic algorithm
T Zhu, Y Li, Z Li, Y Guo, C Ni - Energies, 2022 - mdpi.com
The installed capacity of photovoltaic power generation occupies an increasing proportion in
the power system, and its stability is greatly affected by the fluctuation of solar radiation …
the power system, and its stability is greatly affected by the fluctuation of solar radiation …
Aggregated independent forecasters of half-hourly global horizontal irradiance
In this study, single and aggregated forecasters of half-hourly global horizontal irradiance
are assessed. The models are the standard persistent model and four newly proposed static …
are assessed. The models are the standard persistent model and four newly proposed static …
[HTML][HTML] Forecasting of Wind and Solar Farm Output in the Australian National Electricity Market: A Review
J Boland, S Farah, L Bai - Energies, 2022 - mdpi.com
Accurately forecasting the output of grid connected wind and solar systems is critical to
increasing the overall penetration of renewables on the electrical network. This is especially …
increasing the overall penetration of renewables on the electrical network. This is especially …
A hybrid ensemble learning model for short-term solar irradiance forecasting using historical observations and sky images
A hybrid multi-modal ensemble learning model is proposed for short-term solar irradiance
forecasting based on historical observations and sky images in this paper. In the proposed …
forecasting based on historical observations and sky images in this paper. In the proposed …