International Journal of Green Energy, Год журнала: 2025, Номер unknown, С. 1 - 22
Опубликована: Апрель 17, 2025
Язык: Английский
International Journal of Hydrogen Energy, Год журнала: 2024, Номер 67, С. 1009 - 1025
Опубликована: Янв. 19, 2024
Язык: Английский
Процитировано
52
Energy & Environment, Год журнала: 2024, Номер 35(7), С. 3833 - 3879
Опубликована: Май 22, 2024
The global transition toward sustainable energy sources has prompted a surge in the integration of renewable systems (RES) into existing power grids. To improve efficiency, reliability, and economic viability these systems, synergistic application artificial intelligence (AI) methods emerged as promising avenue. This study presents comprehensive review current state research at intersection AI, highlighting key methodologies, challenges, achievements. It covers spectrum AI utilizations optimizing different facets RES, including resource assessment, forecasting, system monitoring, control strategies, grid integration. Machine learning algorithms, neural networks, optimization techniques are explored for their role complex data sets, enhancing predictive capabilities, dynamically adapting RES. Furthermore, discusses challenges faced implementation such variability, model interpretability, real-time adaptability. potential benefits overcoming include increased yield, reduced operational costs, improved stability. concludes with an exploration prospects emerging trends field. Anticipated advancements explainable reinforcement learning, edge computing, discussed context impact on Additionally, paper envisions AI-driven solutions smart grids, decentralized development autonomous management systems. investigation provides important insights landscape applications
Язык: Английский
Процитировано
45
Energy Economics, Год журнала: 2024, Номер 132, С. 107489 - 107489
Опубликована: Март 20, 2024
Язык: Английский
Процитировано
22
Energy Strategy Reviews, Год журнала: 2024, Номер 53, С. 101409 - 101409
Опубликована: Май 1, 2024
The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling forecasting tasks. While excels in capturing intricate patterns data, it may falter achieving optimality due to nonlinear nature energy data. Conversely, offer optimization capabilities but suffer from computational burdens, especially with high-dimensional This paper provides comprehensive review spanning 2018 2023, examining integration within frameworks applications. We analyze state-of-the-art techniques, innovations, recent advancements, identifying open research challenges. Additionally, we propose novel framework that seamlessly merges into paradigms, aiming enhance performance efficiency addressing problems. contributions include: 1. Overview advancements MHs, DL, integration. 2. Coverage trends 2023. 3. Introduction Alpha metric evaluation. 4. Innovative harmonizing MHs DL
Язык: Английский
Процитировано
17
Scientific Reports, Год журнала: 2025, Номер 15(1)
Опубликована: Янв. 7, 2025
Abstract This manuscript focuses on optimizing a Hybrid Renewable Energy System (HRES) that integrates photovoltaic (PV) panels, wind turbines (WT), and various energy storage systems (ESS), including batteries, supercapacitors (SCs), hydrogen storage. The system uses multi-objective optimization strategy to balance power management, aiming minimize costs reduce the likelihood of loss supply probability (LPSP). Seven different algorithms are assessed identify most efficient one for achieving these objectives, with goal selecting algorithm best balances cost efficiency performance. is across three operational scenarios: (1) when meets demand help from backup systems, (2) exceeds depleted, (3) generation surpasses full. HBA-based effectively manages flow storage, ensuring grid stability minimizing overcharging risks. offers reliable sustainable isolated microgrids, managing production, distribution. research sets new benchmark future studies in decentralized particularly balancing technical economic feasibility.
Язык: Английский
Процитировано
2
Energies, Год журнала: 2023, Номер 16(7), С. 3137 - 3137
Опубликована: Март 30, 2023
Academic contributions regarding the Sustainable Development Goals (SDGs) and renewable energy have been steadily increasing, given their essential relevance to economic, societal, environmental progress. This research aims examine structure of scientific knowledge on connection between SDGs by utilizing bibliometric methods analyzing 3132 articles published 1992 2022. Results indicate a sharp rise in production rate since 2015, Environmental Sciences as most prevalent area study, leading role publishers Elsevier, MDPI, Springer publication papers related subject. Consequently, this may prove useful for both novice veteran researchers who wish further understanding academic energy.
Язык: Английский
Процитировано
35
Heliyon, Год журнала: 2024, Номер 10(4), С. e26088 - e26088
Опубликована: Фев. 1, 2024
The use of renewable energy sources (RESs) at the distribution level has become increasingly appealing in terms costs and technology, expecting a massive diffusion near future placing several challenges to power grid. Since RESs depend on stochastic —solar radiation, temperature wind speed, among others— they introduce high uncertainty grid, leading imbalance deteriorating network stability. In this scenario, managing forecasting RES is vital successfully integrate them into grids. Traditionally, physical- statistical-based models have been used predict outputs. Nevertheless, former are computationally expensive since rely solving complex mathematical atmospheric dynamics, whereas latter usually consider linear models, preventing from addressing challenging scenarios. recent years, advances machine learning techniques, which can learn historical data, allowing analysis large-scale datasets either under non-uniform characteristics or noisy provided researchers with powerful data-driven tools that outperform traditional methods. paper, systematic literature review conducted identify most widely learning-based approaches forecast results show deep artificial neural networks, especially long-short term memory accurately model autoregressive nature output, ensemble strategies, allow handling large amounts highly fluctuating best suited ones. addition, promising integrating forecasted output decision-making problems, such as unit commitment, address economic, operational managerial grid discussed, solid directions for research provided.
Язык: Английский
Процитировано
15
Intelligent Systems with Applications, Год журнала: 2024, Номер 22, С. 200389 - 200389
Опубликована: Май 19, 2024
Concerned by the continuous decline in quality of life, poverty, environmental degradation, and escalated war conflicts, United Nations 2015 instituted 17 Sustainable Development Goals (SDGs) 169 targets. Access to clean, modern, affordable energy, also known as SDG 7, is one goals. Universal access electricity metrics for measuring a good life it fundamentally affects education, healthcare, food security, job creation, other socioeconomic indices. To achieve this goal targets, there has been increased traction research, development, actionable plans, policies, activities governments, scientific community, environmentalists, development experts, stakeholders achieving goal. This review presents various avenues which AI digitization can provide impetus 7. The global trends attaining clean electricity, cooking fuel, renewable energy efficiency, international public financial flows between 2005 2021 are reviewed while contribution towards meeting 7 highlighted. study concludes that deployment into sector will catalyze attainment 2030, provided ethical issues, regulatory concerns, manpower shortage, shortcomings effectively handled. recommends adequate infrastructural upgrades, modernization data collection, storage, analysis capabilities, improved awareness professional collaborative innovation, promotion legal issues ways advancing universal 2030. Going forward, more collaborations academic research institutions producers help produce experts professionals propel innovative digital technologies sector.
Язык: Английский
Процитировано
14
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
Процитировано
14
Journal of Cleaner Production, Год журнала: 2024, Номер 436, С. 140585 - 140585
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
11