Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances

Results in Engineering, Год журнала: 2024, Номер 24, С. 103075 - 103075

Опубликована: Окт. 9, 2024

Язык: Английский

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IntDEM: an intelligent deep optimized energy management system for IoT-enabled smart grid applications

Electrical Engineering, Год журнала: 2024, Номер unknown

Опубликована: Июль 24, 2024

Язык: Английский

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Comparison of control strategies for efficient thermal energy storage to decarbonize residential buildings in cold climates: A focus on solar and biomass sources

Renewable Energy, Год журнала: 2023, Номер 220, С. 119681 - 119681

Опубликована: Ноя. 18, 2023

Язык: Английский

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CNN-GRU model based on attention mechanism for large-scale energy storage optimization in smart grid

Frontiers in Energy Research, Год журнала: 2023, Номер 11

Опубликована: Июль 26, 2023

Introduction: Smart grid (SG) technologies have a wide range of applications to improve the reliability, economics, and sustainability power systems. Optimizing large-scale energy storage for smart grids is an important topic in optimization. By predicting historical load electricity price system, reasonable optimization scheme can be proposed. Methods: Based on this, this paper proposes prediction model combining convolutional neural network (CNN) gated recurrent unit (GRU) based attention mechanism explore grid. The CNN extract spatial features, GRU effectively solve gradient explosion problem long-term forecasting. Its structure simpler faster than LSTM models with similar accuracy. After CNN-GRU extracts data, features are finally weighted by module performance further. Then, we also compared different forecasting models. Results Discussion: results show that our has better predictive computational power, making contribution developing schemes grids.

Язык: Английский

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Review of load frequency control in modern power systems: a state-of-the-art review and future trends

Electrical Engineering, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 13, 2024

Язык: Английский

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LTPNet Integration of Deep Learning and Environmental Decision Support Systems for Renewable Energy Demand Forecasting

Journal of Organizational and End User Computing, Год журнала: 2025, Номер 37(1), С. 1 - 29

Опубликована: Фев. 21, 2025

Against the backdrop of increasingly severe global environmental changes, accurately predicting and meeting renewable energy demands has become a key challenge for sustainable business development. Traditional demand forecasting methods often struggle with complex data processing low prediction accuracy. To address these issues, this paper introduces novel approach that combines deep learning techniques decision support systems. The model integrates advanced techniques, including LSTM Transformer, PSO algorithm parameter optimization, significantly enhancing predictive performance practical applicability. Results show our achieves substantial improvements across various metrics, 30% reduction in MAE, 20% decrease MAPE, 25% drop RMSE, 35% decline MSE. These results validate model's effectiveness reliability forecasting. This research provides valuable insights applying

Язык: Английский

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Long-term policy guidance for sustainable energy transition in Nigeria: A deep learning-based peak load forecasting with econo-environmental scenario analysis

Energy, Год журнала: 2025, Номер unknown, С. 135707 - 135707

Опубликована: Март 1, 2025

Язык: Английский

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Enhanced electrical and thermal energy storage systems performance in smart building using FLHNN and BWOA approach

Journal of Energy Storage, Год журнала: 2025, Номер 122, С. 116651 - 116651

Опубликована: Апрель 22, 2025

Язык: Английский

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Deep learning in energy conversion systems

Elsevier eBooks, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Solving electric power distribution uncertainty using deep learning and incentive-based demand response

Utilities Policy, Год журнала: 2023, Номер 82, С. 101579 - 101579

Опубликована: Май 12, 2023

Язык: Английский

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