Scientific Reports, Год журнала: 2025, Номер 15(1)
Опубликована: Май 2, 2025
Язык: Английский
Energies, Год журнала: 2023, Номер 16(13), С. 5029 - 5029
Опубликована: Июнь 28, 2023
The increasing demand for clean energy and the global shift towards renewable sources necessitate reliable solar radiation forecasting effective integration of into system. Reliable has become crucial design, planning, operational management systems, especially in context ambitious greenhouse gas emission goals. This paper presents a study on application auto-regressive integrated moving average (ARIMA) models seasonal different climatic conditions. performance prediction capacity ARIMA are evaluated using data from Jordan Poland. essence modeling analysis use both as reference model evaluating other approaches basic generation presented. current state source utilization selected countries adopted transition strategies to more sustainable system investigated. two time series (for monthly hourly data) built locations forecast is developed. research findings demonstrate that suitable can contribute stable long-term countries’ systems. However, it develop location-specific due variability characteristics. provides insights highlights their potential supporting planning operation
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
48
Advances in Applied Energy, Год журнала: 2023, Номер 11, С. 100150 - 100150
Опубликована: Авг. 7, 2023
Renewable energy forecasting is crucial for integrating variable sources into the grid. It allows power systems to address intermittency of supply at different spatiotemporal scales. To anticipate future impact cloud displacements on generated by solar facilities, conventional modeling methods rely numerical weather prediction or physical models, which have difficulties in assimilating information and learning systematic biases. Augmenting computer vision with machine overcomes some these limitations fusing real-time cover observations surface measurements acquired from multiple sources. This Review summarizes recent progress multisensor Earth a focus deep learning, provides necessary theoretical framework develop architectures capable extracting relevant data ground-level sky cameras, satellites, stations, sensor networks. Overall, has potential significantly improve accuracy robustness meteorology; however, more research realize this its limitations.
Язык: Английский
Процитировано
43
Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 159556 - 159556
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
3
Energy, Год журнала: 2023, Номер 271, С. 126980 - 126980
Опубликована: Фев. 20, 2023
Язык: Английский
Процитировано
23
Sustainable Horizons, Год журнала: 2024, Номер 11, С. 100108 - 100108
Опубликована: Апрель 18, 2024
Solar energy is the most common, cheapest, and mature renewable technology. With solar photovoltaics taking over recently, an in-depth look into their supply chain shows a surprising dependency on Chinese market from raw materials to assembled PVs. This article tackles main challenges in sheds light opportunities that industry. The research results show China controls of primary materials, manufacturing, installed capacity, recycling capacity. alone produces at least 80 % components Also, more than 30 cumulative capacity China, top exporter manufactured PVs World with competitive manufacturing costs reached less $0.24/W. However, value panels some issues might pose potential risks future such as trade barriers material shortage possibility. also presents opportunities.
Язык: Английский
Процитировано
14
Energy Reports, Год журнала: 2024, Номер 11, С. 3256 - 3266
Опубликована: Март 11, 2024
This study investigates the estimation of daily solar radiation (SR) through various machine learning (ML) models, including k-nearest neighbor algorithm (KNN), support vector regression (SVR), and random forest (RF), both individually in combination with wavelet transform (WT). The assessment these models is based on meteorological data spanning three decades (1981–2010) from province Kütahya Türkiye. To address inherent uncertainty data-driven quantile method employed for analysis. Statistical metrics, such as mean absolute error (MAE), root square (RMSE), coefficient determination (R2), prediction interval (MPI), coverage probability (PICP), are utilized to evaluate effectiveness uncertainties models. SVR KNN exhibit comparable performances concerning predictive accuracy levels. However, hybrid KNN-WT, RF-WT, SVR-WT, display enhanced compared individual ML indicated by statistical performance criteria. Notably, SVR-WT model, incorporating inputs sunshine duration, air temperature, wind speed, relative humidity, outperforms other terms RMSE (2.174 MJ/m2), MAE (1.721 R2 (0.923), MPI (28.55), PICP (0.80) testing dataset. In conclusion, integration WT significantly improves providing valuable insights design operation energy systems, where precise SR critical optimal cost-efficient operation.
Язык: Английский
Процитировано
10
Energies, Год журнала: 2024, Номер 17(13), С. 3156 - 3156
Опубликована: Июнь 26, 2024
Effective solar forecasting has become a critical topic in the scholarly literature recent years due to rapid growth of photovoltaic energy production worldwide and inherent variability this source energy. The need optimise systems, ensure power continuity, balance supply demand is driving continuous development methods approaches based on meteorological data or plant characteristics. This article presents results meta-review literature, including current state knowledge methodological discussion. It comprehensive set methods, evaluates classifications, proposes new synthetic typology. emphasises increasing role artificial intelligence (AI) machine learning (ML) techniques improving forecast accuracy, alongside traditional statistical physical models. explores challenges hybrid ensemble models, which combine multiple enhance performance. paper addresses emerging trends research, such as integration big advanced computational tools. Additionally, from perspective, outlines rigorous approach research procedure, scientific associated with conducting bibliometric highlights best practices principles. article’s relevance consists providing up-to-date forecasting, along insights trends, future directions, anticipating implications for theory practice.
Язык: Английский
Процитировано
10
Energy, Год журнала: 2024, Номер 297, С. 131187 - 131187
Опубликована: Апрель 9, 2024
Язык: Английский
Процитировано
9
Applied Thermal Engineering, Год журнала: 2025, Номер unknown, С. 125550 - 125550
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1