Renewable and Sustainable Energy Reviews最新文献

{"title":"Performance energy production with advanced design and prototype floating ducted tidal turbine for small islands","authors":"Wulfilla Maxmilian Rumaherang ,&nbsp;Hendry Izaac Elim ,&nbsp;Altje Latununuwe ,&nbsp;Estevanus Kristian Huliselan ,&nbsp;Johanis D. Lekalette","doi":"10.1016/j.rser.2025.115664","DOIUrl":"10.1016/j.rser.2025.115664","url":null,"abstract":"<div><div>The urgent need for an energy transition from conventional to renewable energy sources (RE) has become a strategic priority to ensure a sustainable and clean energy supply. In archipelagic nations, renewable energy technologies must be reliable, sustainable, predictable, and environmentally compatible with local wisdom and development goals. Indonesia possesses a total tidal current energy potential of 17.9 GWh, with the Maluku archipelago predicted to have a power density of approximately 4.75 kWh from tidal energy conversion. This study introduces a Floating Ocean Current Power Plant (FOCPP) prototype, incorporating a ducted tidal turbine and a floating moored pontoon system. The platform integrates a low-speed synchronous generator and other electrical components. The prototype was tested in the Haya Strait, Western part of Seram Island, Indonesia, where tidal current speeds reached 2.54 m/s. The results demonstrated a turbine speed enhancement of 1.25–2.65 times, achieving a peak operational period of 19 h per day and producing 72 kWh of energy daily, 2206.4 kWh monthly, and 38.9 MWh annually. These findings suggest that implementing ducted tidal turbines in small island communities can provide a sustainable clean energy solution with minimal greenhouse gas (GHG) emissions. This study highlights the potential for global and national support in accelerating the transition toward renewable energy adoption in remote and underserved regions.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115664"},"PeriodicalIF":16.3,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient energy harvesting using triboelectric nanogenerators (TENGs): Integration with technologies, wearable applications, and future trends","authors":"Seyed Mohammad Vahidhosseini ,&nbsp;Saman Rashidi ,&nbsp;Mohammad Hossein Ehsani","doi":"10.1016/j.rser.2025.115662","DOIUrl":"10.1016/j.rser.2025.115662","url":null,"abstract":"<div><div>The escalating energy demands and the urgent need for sustainable power solutions have highlighted the potential of triboelectric nanogenerators (TENGs) as viable energy harvesting technologies. This paper continues the comprehensive review by focusing on the integration of TENGs with other technologies, their applications in wearable devices, and emerging future trends. This review introduces the integration of TENGs with various technologies, emphasizing hybrid energy harvesting systems, such as TENG-photovoltaic hybrids, TENG-piezoelectric generator systems, and TENG-TEG systems. The paper also explores the application of TENGs in smart systems and internet of things (IoT) applications, including self-powered sensors, IoT connectivity, wearable devices, environmental monitoring, smart homes, and industrial IoT. These integrations demonstrate TENGs’ potential to enhance the efficiency and sustainability of modern technology. Significant attention is given to the advancements in wearable and flexible TENGs. This includes self-powered health monitoring, integration with smart clothing, biocompatible materials, and applications in rehabilitation and fitness tracking. The paper discusses the development of flexible and stretchable TENGs, highlighting innovations in stretchable polymers, serpentine interconnects, and encapsulation techniques, which expand the possibilities for wearable technology, soft robotics, and flexible electronics. Finally, the review addresses environmental and large-scale applications of TENGs, such as ocean wave and wind energy harvesting, and environmental monitoring and sensing systems. It also considers the future prospects and emerging trends, including the integration of TENGs with artificial intelligence and their application in next-generation technologies. By covering these areas, this paper underscores the transformative potential of TENGs in various domains, contributing to sustainable and efficient energy solutions for the future.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115662"},"PeriodicalIF":16.3,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of grid parity assessment for solar photovoltaics","authors":"Rong Wang,&nbsp;Sandra Hasanefendic,&nbsp;Bart Bossink","doi":"10.1016/j.rser.2025.115679","DOIUrl":"10.1016/j.rser.2025.115679","url":null,"abstract":"<div><div>Grid parity is considered the tipping point of economic competitiveness of PV systems. However, accurately determining when grid parity is achieved hinges on the reliability and precision of the methodologies and data employed. This paper systematically reviews existing methods for assessing PV grid parity, proposes a structured three-step framework for grid parity assessment, and identifies the potential enhancements for more accurate evaluation outcomes. The framework begins with the calculation of PV costs using the Levelized Cost of Electricity (LCOE) method, continues with predicting PV cost trends through learning curves, and is completed by benchmarking PV costs against electricity prices. Our findings reveal that most current PV cost calculations for grid parity primarily rely on the LCOE method, which can be enhanced by incorporating modifications for integration costs, revenues, PV performance metrics, regional-specific characteristics, and uncertainties. Moreover, learning curve models used to predict PV cost trends can be refined by tailoring learning rates and model formulations to reflect specific stages of technological development and regional differences. Additionally, the results suggest that electricity prices used in grid parity assessment can be adjusted to reflect the impact of policies and market dynamics. This comprehensive review provides a robust framework for assessing grid parity and serves as an essential reference for conducting more precise techno-economic feasibility assessment of PV systems.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115679"},"PeriodicalIF":16.3,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-term prediction of mooring tension for floating offshore wind turbines under typhoon conditions based on the VMD-MI-LSTM method","authors":"Lehan Hu ,&nbsp;Wei Shi ,&nbsp;Weifei Hu ,&nbsp;Wei Chai ,&nbsp;Zhiqiang Hu ,&nbsp;Jun Wu ,&nbsp;Xin Li","doi":"10.1016/j.rser.2025.115606","DOIUrl":"10.1016/j.rser.2025.115606","url":null,"abstract":"<div><div>The safety of mooring systems for floating offshore wind turbine platforms is critical for their normal operation. During extreme weather events such as typhoons, ensuring the integrity of mooring lines becomes a paramount concern. With advancements in artificial intelligence technology, the integration of deep learning methods for short-term prediction of mooring line tension under typhoon conditions has introduced innovative solutions to address this safety issue. In this study, the proposed VMD-MI-LSTM neural network is employed to forecast mooring line tension under typhoon conditions over short periods. The platform model utilized in this research is the 5-MW Braceless semisubmersible platform, with the transient wind fields of Typhoon Hagibis serving as the research scenarios. Through fully coupled simulations, the tension of mooring lines under typhoon conditions is computed. Using wave height time series and typhoon wind speed as input data and mooring line tension data as output, a dataset is constructed. The optimal model parameters are determined through exploration of the hyperparameter space to develop the multi-input long short-term memory (MI-LSTM) mooring line tension prediction model. An analysis of the prediction results for mooring line #1 is conducted. Given the similarity of environmental conditions across different platform mooring lines, the model's universality is evaluated by predicting mooring line #1 and comparing it with the VMD-MI-LSTM model. This comparison highlights the optimization effect of the VMD variational mode decomposition method. This study provides short-term predictions of mooring line tension under typhoon conditions. By integrating with the mooring line adjustment system, effective adjustment of the mooring system of the floating wind turbine platform can be achieved under extreme environmental conditions, thereby enhancing the platform's safety and resilience against risks.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115606"},"PeriodicalIF":16.3,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven wind farm flow control and challenges towards field implementation: A review","authors":"Tuhfe Göçmen ,&nbsp;Jaime Liew ,&nbsp;Elie Kadoche ,&nbsp;Nikolay Dimitrov ,&nbsp;Riccardo Riva ,&nbsp;Søren Juhl Andersen ,&nbsp;Alan W.H. Lio ,&nbsp;Julian Quick ,&nbsp;Pierre-Elouan Réthoré ,&nbsp;Katherine Dykes","doi":"10.1016/j.rser.2025.115605","DOIUrl":"10.1016/j.rser.2025.115605","url":null,"abstract":"<div><div>Data-driven wind farm flow control (WFFC) is an innovative approach that leverages the collected data and advanced analytics to enhance the performance of wind turbines within wind farms. Its significance lies in its ability to adapt to changing wind and turbine conditions and improve operations, boosting energy yield, extending turbine/component lifetime, and potentially reducing socio-environmental impact and costs, thus supporting the viability and sustainability of wind energy as a renewable power source. This review explores the dynamic field of data-driven WFFC and its challenges towards practical implementation. Building on top of traditional wind farm modelling and model-based control, it details the virtues and limitations of these methods while introducing the concept of data-informed or data-driven flow models that harness data to augment predictive accuracy and control strategies. The analysis then covers the methodologies for power and load surrogates, elucidating the pivotal role of surrogate modelling in enhancing WFFC, and showcasing its value in decision-making and energy optimisation. Furthermore, the growing field of reinforcement learning (RL) is highlighted, showcasing its adaptive potential to revolutionise wind farm control through learning from past interactions. The investigation concludes by identifying key challenges impeding the practical deployment of data-driven WFFC, including data quality concerns, cybersecurity risks, and limitations of the current algorithms. In summary, this comprehensive review presents the ongoing development of data-driven WFFC, emphasising the synergy between traditional methods, surrogate modelling, RL, and the critical challenges to be addressed for successful integration of these methodologies in real-world wind farm operations.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115605"},"PeriodicalIF":16.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal models for mono/bifacial modules in ground/floating photovoltaic systems: A review","authors":"Amr Osama ,&nbsp;Giuseppe Marco Tina ,&nbsp;Antonio Gagliano","doi":"10.1016/j.rser.2025.115627","DOIUrl":"10.1016/j.rser.2025.115627","url":null,"abstract":"<div><div>Since the world's policy tends to rely on solar energy to meet energy needs, photovoltaics are considered a crucial asset that requires continuous monitoring. Several installation solutions, including different PV technologies, created challenges in providing a reliable evaluation to depend on. Thermal modeling is essential to predict the cell temperature that is utilized in anticipating the system's electrical performance, as in most commercial software. Hence, this work provides an overview of the most used thermal models for installation solutions (free-standing, roof-mounted, floating, etc.) utilizing both mono and bifacial module technology. The provided analysis is focused on evaluating the different responses of the thermal models that can be used for the same configuration and technology. A sensitive comparative analysis of the various thermal models is provided to assess their response to the climatic parameters as an input to the thermal model. The analysis revealed that for monofacial thermal models, Ross models underestimate the cell temperature at any radiation intensity, while the Faiman model using PVsyst coefficients generates the highest overestimated cell temperature among the examined models. It can be seen that the effect of wind speed reduces for a velocity higher than 10 m/s. As for the bifacial PV module, it can be noticed that the Sandia model using Bifacial optimized coefficients is very sensitive to the back surface radiation as it tends to overestimate relative to the Faiman model. Furthermore, floating PV thermal models are significantly affected by the heat transfer coefficient that usually produces a lower cell temperature.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115627"},"PeriodicalIF":16.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methodologies for offshore wind power plant dynamic stability analysis","authors":"Germano Rugendo Mugambi ,&nbsp;Nicolae Darii ,&nbsp;Hesam Khazraj ,&nbsp;Oscar Saborío-Romano ,&nbsp;Alin George Raducu ,&nbsp;Ranjan Sharma ,&nbsp;Nicolaos A. Cutululis","doi":"10.1016/j.rser.2025.115635","DOIUrl":"10.1016/j.rser.2025.115635","url":null,"abstract":"<div><div>The development of larger Offshore wind power plants (OWPPs) is growing exponentially and also evolving in larger multi-vendor setups, ultimately aiming to constitute offshore Energy hubs. At the same time, interactions among wind turbine converters and power systems have been observed, and this critical phenomenon can significantly impact the dynamic stability of the system. While various stability analysis methods have been proposed to analyze the interactions between OWPPs and the power system at the Point-of-connection (PoC), these stability studies rarely consider the complex offshore transmission system behind the PoC. Typically, the overall OWPP is blamed for the instability issues. However, since the plant itself is a complex system, it is important to understand which part of the OWPP behind the PoC is causing the problem or is likely to become unstable under certain conditions. Therefore, this paper provides a detailed overview of the current system screening indexes and dynamic stability analysis methodologies used in OWPP design. It critically evaluates the advantages and limitations of each approach, emphasizing their applicability to various OWPP structures. The analysis indicates that a combination of time domain and frequency domain methods is necessary to better define stability boundaries and enhance accurate dynamic stability analysis of OWPPs.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115635"},"PeriodicalIF":16.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing sustainable energy harvesting with triboelectric nanogenerators (TENGs): Advanced materials and performance enhancement strategies","authors":"Seyed Mohammad Vahidhosseini ,&nbsp;Saman Rashidi ,&nbsp;Mohammad Hossein Ehsani","doi":"10.1016/j.rser.2025.115663","DOIUrl":"10.1016/j.rser.2025.115663","url":null,"abstract":"<div><div>The growing global energy demand and the pressing need for sustainable power solutions have intensified the search for innovative energy harvesting technologies. Triboelectric nanogenerators (TENGs) have emerged as promising candidates due to their ability to convert mechanical energy into electrical energy efficiently. This paper provides a comprehensive review of advanced materials and performance enhancement strategies for TENGs, emphasizing their critical role in addressing the current energy crisis. This review explores the foundational principles and operational modes of TENGs, including vertical contact-separation, lateral sliding, single-electrode, and freestanding triboelectric-layer modes. The paper highlights TENGs’ unique attributes such as high efficiency at low frequencies, lightweight and flexible design, scalability, cost-effectiveness, and environmental friendliness, making them suitable for various applications. Key sections of this review focus on the advanced materials used in TENGs, including nanostructured surfaces and interfaces, hybrid and composite materials, and eco-friendly and biodegradable materials. Techniques such as nanoimprinting, etching, and nanomaterial coatings are discussed in detail, showcasing their impact on enhancing TENG performance. Furthermore, the review delves into performance enhancement strategies, covering multi-dimensional TENGs, optimization of contact electrification through surface modification, selection of triboelectric pairs, nano and microstructuring, and dynamic tuning mechanisms. By providing a thorough examination of these advanced materials and strategies, this paper underscores their importance in improving TENG efficiency and reliability, paving the way for sustainable energy solutions in the future.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115663"},"PeriodicalIF":16.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Representative energy management strategies for hybrid energy storage systems derived from a meta-review","authors":"Sebastian Günther,&nbsp;Astrid Bensmann,&nbsp;Richard Hanke-Rauschenbach","doi":"10.1016/j.rser.2025.115610","DOIUrl":"10.1016/j.rser.2025.115610","url":null,"abstract":"<div><div>Hybrid energy storage systems integrate diverse storage technologies to enhance system performance, efficiency, and longevity. Despite a plurality of proposed energy management strategies to operate these systems and a significant number of reviews on this topic, the field lacks a systematic, actionable and reusable summary of available energy management strategies.</div><div>Therefore, we conducted a meta-review of available review articles to ascertain a joint base for representative energy management strategies for hybrid energy storage systems. In subsequent reviews of each determined class, we extracted, defined, and detailed core concepts, which were then implemented in Python for demonstration and analysis.</div><div>We identified four representatives: filter-based, deadzone-based, fuzzy-logic-based, and model-predictive-control-based energy management. Each one is discussed with its operational mechanisms and implementable equations and is illustrated through simulations. Notably, we excluded machine-learning-based candidates due to the limited foundation and generalizability in the current literature.</div><div>With the identified representatives, we seek to provide a foundation and framework for further development, including quantitative assessments of energy management performance in various configurations. Also, this work facilitates targeted and effective enhancements in energy management development for each class, accelerating future research and supporting industry stakeholders to develop more efficient renewable energy systems. To allow easy reuse and reproducibility, the source code is available at GitHub.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115610"},"PeriodicalIF":16.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new framework for the technical biogas potential: Concept design, method development, and analytical application in a case study from Germany","authors":"Matthias Steindl ,&nbsp;Thomas J. Venus ,&nbsp;Konrad Koch","doi":"10.1016/j.rser.2025.115645","DOIUrl":"10.1016/j.rser.2025.115645","url":null,"abstract":"<div><div>A flexible framework for estimating the technical and unused biomass potential for biogas production with high spatial resolution has been developed to integrate biomethane into future energy systems. By classifying agricultural biomass into non-competitive biomass (NCB), livestock-competitive biomass (LCB), and food/feed-competitive biomass (FCB), the model accounts for their competing uses in livestock production and food security. Applied to Bavaria, the analysis covers 2,229 municipalities, using data from agricultural enterprises, biomass yields, and biogas production. The results show an unused methane potential of 1.58·10⁹ m³ from agricultural NCB and LCB, potentially covering 12.2 % of Bavaria's natural gas consumption in 2021. A Monte Carlo simulation was performed to account for uncertainty in the underlying data and to perform a sensitivity analysis. The results highlight that agricultural policy decisions, particularly those affecting livestock production, significantly influence the technical biogas potential: Decreases in manure and slurry formation may reduce the potential, but this could be offset by the availability of unused biomass from livestock feed, depending on policy choices. The presented framework may be used for different regions given availability of data, while the results offer valuable insights for policymakers and stakeholders for developing the biogas sector and its integration into a renewable energy system in the studied region.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"216 ","pages":"Article 115645"},"PeriodicalIF":16.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}