Forecasting and uncertainty analysis of day-ahead photovoltaic power using a novel forecasting method

Applied Energy, Год журнала: 2021, Номер 299, С. 117291 - 117291

Опубликована: Июнь 24, 2021

Язык: Английский

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Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy

Renewable and Sustainable Energy Reviews, Год журнала: 2022, Номер 162, С. 112473 - 112473

Опубликована: Апрель 21, 2022

Язык: Английский

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LOWESS smoothing and Random Forest based GRU model: A short-term photovoltaic power generation forecasting method

Energy, Год журнала: 2022, Номер 256, С. 124661 - 124661

Опубликована: Июнь 28, 2022

Язык: Английский

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An enhanced multivariable dynamic time-delay discrete grey forecasting model for predicting China's carbon emissions

Energy, Год журнала: 2022, Номер 249, С. 123681 - 123681

Опубликована: Март 9, 2022

Язык: Английский

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Short-term photovoltaic power point-interval forecasting based on double-layer decomposition and WOA-BiLSTM-Attention and considering weather classification

Energy, Год журнала: 2023, Номер 275, С. 127348 - 127348

Опубликована: Апрель 6, 2023

Язык: Английский

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Energy Forecasting: A Comprehensive Review of Techniques and Technologies

Energies, Год журнала: 2024, Номер 17(7), С. 1662 - 1662

Опубликована: Март 30, 2024

Distribution System Operators (DSOs) and Aggregators benefit from novel energy forecasting (EF) approaches. Improved accuracy may make it easier to deal with imbalances between generation consumption. It also helps operations such as Demand Response Management (DRM) in Smart Grid (SG) architectures. For utilities, companies, consumers manage resources effectively educated decisions about consumption, EF is essential. many applications, Energy Load Forecasting (ELF), Generation (EGF), grid stability, accurate crucial. The state of the art examined this literature review, emphasising cutting-edge techniques technologies their significance for industry. gives an overview statistical, Machine Learning (ML)-based, Deep (DL)-based methods ensembles that form basis EF. Various time-series are explored, including sequence-to-sequence, recursive, direct forecasting. Furthermore, evaluation criteria reported, namely, relative absolute metrics Mean Absolute Error (MAE), Root Square (RMSE), Percentage (MAPE), Coefficient Determination (R2), Variation (CVRMSE), well Execution Time (ET), which used gauge prediction accuracy. Finally, overall step-by-step standard methodology often utilised problems presented.

Язык: Английский

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Deep learning model for short-term photovoltaic power forecasting based on variational mode decomposition and similar day clustering

Computers & Electrical Engineering, Год журнала: 2024, Номер 115, С. 109116 - 109116

Опубликована: Фев. 15, 2024

Язык: Английский

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Short-term PV power prediction based on meteorological similarity days and SSA-BiLSTM

Systems and Soft Computing, Год журнала: 2024, Номер 6, С. 200084 - 200084

Опубликована: Фев. 23, 2024

Accurate short-term photovoltaic (PV) power forecasting can reduce the un- certainty of PV generation, which is crucial for grid operation as well energy dispatch. Considering influence seasonal and meteorological factors on prediction, a predic- tion method based similarity day sparrow search algo- rithm bi-directional long memory network combination (SSA-BiLSTM) proposed. Firstly, correlation between generation calculated by using Pearson coefficients, getting strongly correlated affecting generation; afterwards,the historical data are clustered fuzzy C-means clustering to achieve similar clustering; then, best selected from according test features data, Forming training set with original BiLSTM network. SSA algorithm was used find optimal parameters. Finally, Using parameters construct prediction. The experiments were conducted plant in Xinjiang, also compared existing prediction algorithms.The results show that accuracy different weather conditions 33.1 %, 31.9 % 24.1 higher than under same intelligent optimization neural networks, 27.9 24.7 18.0 algorithms Therefore, this paper has better seasons conditions.

Язык: Английский

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A hybrid ensemble optimized BiGRU method for short-term photovoltaic generation forecasting

Energy, Год журнала: 2024, Номер 299, С. 131458 - 131458

Опубликована: Апрель 27, 2024

Язык: Английский

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Forecasting the sales and stock of electric vehicles using a novel self-adaptive optimized grey model

Engineering Applications of Artificial Intelligence, Год журнала: 2021, Номер 100, С. 104148 - 104148

Опубликована: Янв. 13, 2021

Язык: Английский

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