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Spectral normalization generative adversarial networks for photovoltaic power scenario generation

IET renewable power generation, 2024-03

2024

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Technical indicator enhanced ultra‐short‐term wind power forecasting based on long short‐term memory network combined XGBoost algorithm

IET renewable power generation, 2024-02

2024

Volltextzugriff (PDF)

Data‐driven robust look‐ahead power dispatch with preidentification of the worst‐case scenario using combined multilayer perceptron

IET renewable power generation, 2024-02

2024

Volltextzugriff (PDF)

Deep learning based carbon emissions forecasting and renewable energy's impact quantification

IET renewable power generation, 2023-03, Vol.17 (4), p.873-884

2023

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Wind turbines anomaly detection based on power curves and ensemble learning

IET renewable power generation, 2020-12, Vol.14 (19), p.4086-4093

2020

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Systematic literature review of photovoltaic output power forecasting

IET renewable power generation, 2020-12, Vol.14 (19), p.3961-3973

2020

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Photovoltaic cell defect classification using convolutional neural network and support vector machine

IET renewable power generation, 2020-10, Vol.14 (14), p.2693-2702

2020

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Deep learning approach for wind speed forecasts at turbine locations in a wind farm

IET renewable power generation, 2020-10, Vol.14 (13), p.2416-2428

2020

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Data-driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance

IET renewable power generation, 2020-10, Vol.14 (13), p.2386-2394

2020

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PVHybNet: a hybrid framework for predicting photovoltaic power generation using both weather forecast and observation data

IET renewable power generation, 2020-09, Vol.14 (12), p.2192-2201

2020

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Structural and behavioural evaluation of renewable energy power plants' impacts on transmission network congestion using an analytical approach

IET renewable power generation, 2020-05, Vol.14 (7), p.1164-1173

2020

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Deep learning enhanced situation awareness for high renewable-penetrated power systems with multiple data corruptions

IET renewable power generation, 2020-05, Vol.14 (7), p.1134-1142

2020

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Forecast uncertainty-based performance degradation diagnosis of solar PV systems

IET renewable power generation, 2020-04, Vol.14 (6), p.968-975

2020

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Point and interval forecasting of solar irradiance with an active Gaussian process

IET renewable power generation, 2020-04, Vol.14 (6), p.1020-1030

2020

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Short-term wind power forecasting based on two-stage attention mechanism

IET renewable power generation, 2020-02, Vol.14 (2), p.297-304

2020

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Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed

IET renewable power generation, 2020-01, Vol.14 (1), p.100-109

2020

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Weather division-based wind power forecasting model with feature selection

IET renewable power generation, 2019-12, Vol.13 (16), p.3050-3060

2019

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Wind turbine power curve estimation based on earth mover distance and artificial neural networks

IET renewable power generation, 2019-11, Vol.13 (15), p.2939-2946

2019

Volltextzugriff (PDF)

Uncertainty-aware forecast interval for hourly PV power output

IET renewable power generation, 2019-10, Vol.13 (14), p.2656-2664

2019

Volltextzugriff (PDF)

IoT-based approach to condition monitoring of the wave power generation system

IET renewable power generation, 2019-09, Vol.13 (12), p.2207-2214

2019

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Proactive frequency control based on ultra-short-term power fluctuation forecasting for high renewables penetrated power systems

IET renewable power generation, 2019-09, Vol.13 (12), p.2166-2173

2019

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Data-driven wind speed forecasting using deep feature extraction and LSTM

IET renewable power generation, 2019-09, Vol.13 (12), p.2062-2069

2019

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Probabilistic deep neural network price forecasting based on residential load and wind speed predictions

IET renewable power generation, 2019-08, Vol.13 (11), p.1840-1848

2019

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Multi-step wind power forecast based on VMD-LSTM

IET renewable power generation, 2019-07, Vol.13 (10), p.1690-1700

2019

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Confidence-aware deep learning forecasting system for daily solar irradiance

IET renewable power generation, 2019-07, Vol.13 (10), p.1681-1689

2019

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Spectral normalization generative adversarial networks for photovoltaic power scenario generation

Technical indicator enhanced ultra‐short‐term wind power forecasting based on long short‐term memory network combined XGBoost algorithm

Data‐driven robust look‐ahead power dispatch with preidentification of the worst‐case scenario using combined multilayer perceptron

Deep learning based carbon emissions forecasting and renewable energy's impact quantification

Wind turbines anomaly detection based on power curves and ensemble learning

Systematic literature review of photovoltaic output power forecasting

Photovoltaic cell defect classification using convolutional neural network and support vector machine

Deep learning approach for wind speed forecasts at turbine locations in a wind farm

Data-driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance

PVHybNet: a hybrid framework for predicting photovoltaic power generation using both weather forecast and observation data

Structural and behavioural evaluation of renewable energy power plants' impacts on transmission network congestion using an analytical approach

Deep learning enhanced situation awareness for high renewable-penetrated power systems with multiple data corruptions

Forecast uncertainty-based performance degradation diagnosis of solar PV systems

Point and interval forecasting of solar irradiance with an active Gaussian process

Short-term wind power forecasting based on two-stage attention mechanism

Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed

Weather division-based wind power forecasting model with feature selection

Wind turbine power curve estimation based on earth mover distance and artificial neural networks

Uncertainty-aware forecast interval for hourly PV power output

IoT-based approach to condition monitoring of the wave power generation system

Proactive frequency control based on ultra-short-term power fluctuation forecasting for high renewables penetrated power systems

Data-driven wind speed forecasting using deep feature extraction and LSTM

Probabilistic deep neural network price forecasting based on residential load and wind speed predictions

Multi-step wind power forecast based on VMD-LSTM

Confidence-aware deep learning forecasting system for daily solar irradiance

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