Recent developments of energy management strategies in microgrids: An updated and comprehensive review and classification

Energy Conversion and Management, Год журнала: 2023, Номер 297, С. 117723 - 117723

Опубликована: Окт. 5, 2023

Язык: Английский

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Eco-environmental scheduling of multi-energy communities in local electricity and natural gas markets considering carbon taxes: A decentralized bi-level strategy

Journal of Cleaner Production, Год журнала: 2024, Номер 440, С. 140902 - 140902

Опубликована: Янв. 29, 2024

Язык: Английский

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Artificial intelligence integrated grid systems: Technologies, potential frameworks, challenges, and research directions

Renewable and Sustainable Energy Reviews, Год журнала: 2025, Номер 211, С. 115251 - 115251

Опубликована: Янв. 8, 2025

Язык: Английский

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Two-stage optimal dispatch framework of active distribution networks with hybrid energy storage systems via deep reinforcement learning and real-time feedback dispatch

Journal of Energy Storage, Год журнала: 2025, Номер 108, С. 115169 - 115169

Опубликована: Янв. 5, 2025

Язык: Английский

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Coordinated energy management for integrated energy system incorporating multiple flexibility measures of supply and demand sides: A deep reinforcement learning approach

Energy Conversion and Management, Год журнала: 2023, Номер 297, С. 117728 - 117728

Опубликована: Окт. 6, 2023

Язык: Английский

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Multi-agent optimal scheduling for integrated energy system considering the global carbon emission constraint

Energy, Год журнала: 2023, Номер 288, С. 129732 - 129732

Опубликована: Ноя. 21, 2023

Язык: Английский

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Artificial intelligence for hydrogen-enabled integrated energy systems: A systematic review

International Journal of Hydrogen Energy, Год журнала: 2024, Номер unknown

Опубликована: Авг. 1, 2024

Hydrogen-enabled Integrated Energy Systems (H-IES) stand out as a promising solution with the potential to replace current non-renewable energy systems. However, their development faces challenges and has yet achieve widespread adoption. These main include complexity of demand supply balancing, dynamic consumer demand, in integrating utilising hydrogen. Typical management strategies within domain rely heavily on accurate models from experts or conventional approaches, such simulation optimisation which cannot be satisfied real-world operation H-IES. Artificial Intelligence (AI) Advanced Data Analytics (ADA), especially Machine Learning (ML), ability overcome these challenges. ADA is extensively used across several industries, however, further investigation into incorporation hydrogen for purpose enabling H-IES needs investigated. This paper presents systematic literature review study research gaps, directions, benefits ADA, well role

Язык: Английский

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Review of Energy Management Systems in Microgrids

Applied Sciences, Год журнала: 2024, Номер 14(3), С. 1249 - 1249

Опубликована: Фев. 2, 2024

Microgrids usually employ distributed energy resources such as wind turbines, solar photovoltaic modules, etc. When multiple generation with different features are used in microgrids, managing these becomes an important problem. The generated power of modules and turbines microgrids is constantly changing irradiation speed. Due to this impermanent uncertain nature renewable resources, generally, storage systems employed microgrid systems. To control the units sustain supply demand balance within provide sustainable reliable loads, management used. Many methods realize optimize microgrids. This review article provides a comparative critical analysis system can be tailored for purposes, which also discussed detail. Additionally, various uncertainty measurement summarized manage variability intermittency sources load demand. Finally, some thoughts about potential future directions practical applications given.

Язык: Английский

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An overview: Attention mechanisms in multi-agent reinforcement learning

Neurocomputing, Год журнала: 2024, Номер 598, С. 128015 - 128015

Опубликована: Июнь 11, 2024

Язык: Английский

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Improving small-signal stability of inverter-based microgrids using fractional-order control

International Journal of Electrical Power & Energy Systems, Год журнала: 2024, Номер 156, С. 109746 - 109746

Опубликована: Янв. 5, 2024

Augmenting the range of active droop gain in inverter-based microgrids (IBMGs) is required for faster power sharing and improved control at secondary level. However, IBMG stability degraded when increased, which reveals an obvious tradeoff. Therefore, fractional-order (FOC) used this paper to increase (IB) MGs' margin by increasing stable gain. So, a thorough small-signal model IBMGs developed assess MG tune parameters case using FOCs. Also, low-pass filter (FO-LPF) proposed outer loop increases damping factor reduces oscillations same Moreover, further boost achieved combining FO-LPF with FO-PI controllers inner loops. The results FO are validated on MATLAB/SIMULINK benchmark system. comparative study has shown superiority approach over recent ones reconfigured meshed network. discretization scheme FOCs outlined tested under load disturbance event.

Язык: Английский

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