Renewable Energy最新文献

{"title":"Techno-economic optimization of microgrid operation with integration of renewable energy, hydrogen storage, and micro gas turbine","authors":"Reyhaneh Banihabib ,&nbsp;Fredrik Skaug Fadnes ,&nbsp;Mohsen Assadi","doi":"10.1016/j.renene.2024.121708","DOIUrl":"10.1016/j.renene.2024.121708","url":null,"abstract":"<div><div>Microgrids are integral to modern energy systems, yet they face substantial challenges in integrating diverse components, managing complex dynamics, and ensuring stability amid renewable energy variability. This study investigates the integration of wind turbines, an electrolyzer, and a hydrogen-compatible micro gas turbine (MGT), with a focus on enhancing operational efficiency and maintaining dynamic equilibrium within the microgrid. The synergy between the electrolyzer and MGT provides a robust energy storage solution, improving both system stability and performance.</div><div>Using advanced machine learning and real operational data, this research generates highly accurate, rapid models with greater precision and detail than conventional methods. The intelligent management system developed combines real-time optimization and adaptive fine-tuning, using forecasts of weather, electricity prices, and energy demand to devise optimized operational strategies. The study systematically analyzes various configurations, including grid-connected and island modes, and evaluates the impact of hydrogen storage in each scenario.</div><div>The results demonstrate that the optimization approach substantially enhances economic returns. However, this can also lead to increased natural gas consumption and emissions, revealing a trade-off between financial gains and environmental sustainability. This highlights the necessity for strategies that reconcile economic incentives with sustainability objectives, offering valuable insights for improved microgrid management.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121708"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743118","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":"The impact of soiling on temperature and sustainable solar PV power generation: A detailed analysis","authors":"Shubham Sharma ,&nbsp;Prashant Malik ,&nbsp;Sunanda Sinha","doi":"10.1016/j.renene.2024.121864","DOIUrl":"10.1016/j.renene.2024.121864","url":null,"abstract":"<div><div>Soiling accumulation and high temperatures have a detrimental impact on the performance of solar photovoltaic modules. However, the effect of soiling on module temperatures remains a relatively unexplored area despite offering intriguing research possibilities. This study investigates the impact of soiling on solar photovoltaic modules, focusing on the variation in module temperatures. The research uses experimental investigations and a hybrid diode model to account for soiling losses. Furthermore, the model is employed to quantify the power reduction due to the temperature rise caused by soiling. The experimental investigations revealed that soiling deposition results in both substantial energy reductions and higher module temperatures. The soiling-induced variation in temperature profiles and corresponding power reductions on certain days was also analyzed. The results showed that the daily average reduction in power due to increased temperature was 0.614 %, 1.044 % and 1.31 %, while on the same days, the daily maximum reduction observed was 1.55 %, 2.53 % and 3.46 %, respectively. Thus, higher temperatures lead to substantial power degradation and may also affect the health of PV modules in the long run. The outcomes of this study emphasize the importance of addressing soiling-induced temperature variations, offering valuable insights for improved design and maintenance practices of power plants.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121864"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743208","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":"Variable frequency interharmonic domain methodology for transient analysis and simulation of distributed generation systems","authors":"Uriel Vargas,&nbsp;George Cristian Lazaroiu","doi":"10.1016/j.renene.2024.121634","DOIUrl":"10.1016/j.renene.2024.121634","url":null,"abstract":"<div><div>As the integration of renewable energy resources into the power grid increases, accurate modeling of variable frequency distributed generation systems becomes essential for ensuring grid stability, reliability, and optimal operation. Existing models often fail in effectively capturing the frequency dynamics of these systems, particularly when dealing with variable frequency sources. This gap hinders comprehensive analysis and the development of effective planning, control, and mitigation strategies.</div><div>To address this challenge, this paper introduces a novel modeling methodology named here as the variable frequency interharmonic domain (VFID), which is based on the flexible extended harmonic domain (FEHD) approach. VFID dynamically adjusts the set of pre-selected frequencies within the state-space system to reflect changes in variable frequency sources. This method eliminates the need for post-processing routines, accurately representing both instantaneous values and frequency evolution of time-varying harmonics and interharmonics.</div><div>Key results demonstrate that VFID offers significant improvements in simulation accuracy over conventional FEHD and PSCAD methods, making it a valuable tool for analyzing and simulating modern distributed generation systems. This advancement not only fills a critical research gap but also contributes to the development of more resilient and sustainable energy infrastructures.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121634"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756659","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":"Multi-stage control design for oscillating water column-based ocean wave energy conversion system","authors":"Muhammad Noman ,&nbsp;Guojie Li ,&nbsp;Muhammad Waseem Khan ,&nbsp;Keyou Wang ,&nbsp;Bei Han","doi":"10.1016/j.renene.2024.121622","DOIUrl":"10.1016/j.renene.2024.121622","url":null,"abstract":"<div><div>Despite the enormous global potential of ocean wave energy, it has yet to achieve a level of maturity and economic competitiveness that would result in a substantial impact. Challenges include direct integration into weak or isolated microgrids, a high proportion of uncertain marine environments, nonlinear dynamics, oscillating water column (OWC) device limitations, slower response times, unplanned power outages, power fluctuations, high capital and operational costs in ocean wave energy conversion (OWEC) systems. To this end, a new independent multi-stage design approach is proposed for the performance enhancement of an OWC-based OWEC system. Firstly, an airflow and rotational speed optimal control stage enhances power capture in the Wells turbine-based OWC plant. Secondly, compared to conventional control, the proposed permanent magnet synchronous generator control incorporates an adaptive nonlinear back-stepping control algorithm based on Lyapunov stability theory. Thirdly, introducing reconfigurable control into the conventional six-leg power converter ensures the uninterrupted operation of an OWEC system. Lastly, a model-predictive control-based energy management system is integrated with a bidirectional DC-DC converter that delivers steady power from the grid-connected OWC OWEC system. Hence, MATLAB simulations ensure the overall performance enhancement and feasibility of the OWEC system application and verify that the proposed multi-stage solution is efficient, robust, and reliable.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121622"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756657","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":"Spatial and temporal analysis of decomposition models in China","authors":"Ying Sun ,&nbsp;Ning Lu","doi":"10.1016/j.renene.2024.121850","DOIUrl":"10.1016/j.renene.2024.121850","url":null,"abstract":"<div><div>This study presents a comprehensive evaluation of 15 decomposition models (12 empirical and 3 atmospheric transmittance models) for estimating diffuse horizontal irradiance at 17 radiation sites in China, using hourly radiation data from 2011 to 2020. Our results show distinct patterns in model performance across different geographical regions, seasons, and sky conditions. The Liu model demonstrates the best overall performance with an RMSE of 78.20 W/m², while model accuracy shows significant geographical variation, performing best in South and Southeast China (RMSE&lt;70 W/m²) and worst in the Qinghai-Tibet Plateau and Northwest China (RMSE&gt;90 W/m²). Seasonal analysis reveals better performance in winter than in summer, with RMSE differences approaching 40 W/m², mainly due to the higher proportion of solar elevation angles exceeding 30° in summer. Under different sky conditions (classified by clearness index: 0–0.35 for overcast, 0.35–0.65 for partly cloudy, 0.65–1 for clear skies), most models follow an RMSE pattern of partly cloudy &gt; clear sky &gt; overcast. However, the Reindl2, Boland, DIRINT, and DIRINDEX models deviate from this trend due to their formula structure and sensitivity to atmospheric parameters. To reduce these regional disparities, we propose a new region-specific model selection strategy: the DIRINDEX model for eastern regions, DIRINT for central areas, and Karatasou for western regions. This combined approach reduces the overall RMSE to 73.17 W/m². This research deepens our understanding of the application of decomposition models in China's complex geographical and climatic conditions, offering valuable references for solar radiation modeling and renewable energy forecasting in diverse climatic regions.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121850"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743210","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":"Sulfur migration and conversion during co-combustion of sewage sludge and coal slime","authors":"Yanlin Wang ,&nbsp;Lei Ye ,&nbsp;Yun Chen ,&nbsp;Jingkuan Li ,&nbsp;Tao Bai ,&nbsp;Zhiping Jin ,&nbsp;Yan Jin","doi":"10.1016/j.renene.2024.121646","DOIUrl":"10.1016/j.renene.2024.121646","url":null,"abstract":"<div><div>Co-combustion is an effective way to achieve high-value utilization of sewage sludge (SS) and coal slime (CS). In this study, thermogravimetric-mass spectrometry and X-ray photoelectron spectroscopy were combined to investigate the morphology and changing law of sulfur in the gas-solid phase. H₂S, COS, and SO₂ were detected in SS and CS mono-combustion, and the SO₂ release from CS was 8.8 times that of SS. During SS combustion, the oxidation of aliphatic-sulfur and thiophene led to a staged increase in sulfone content. Sulfate was generated after 500 °C and decomposed after 700 °C to form SO₂. During CS combustion, aliphatic-sulfur was converted to H₂S, thiophene was sequentially oxidized to sulfoxide and sulfone, and a part of sulfone and sulfate decomposed to SO₂ at high temperature. During co-combustion, the release of H₂S was inhibited after the CS ratio reached 50 %, and the release of COS was promoted at different ratios. Co-combustion significantly promoted the sulfur fixation of the inorganic components, which led to the inhibition of SO₂ release, and the deviation between the experimental and theoretical values was as high as 91.3 % at a CS ratio of 50 %, as well as the content of sulfate in the solid phase was significantly increased.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121646"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756655","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":"Biogas production modeling: Developing a logistic equation satisfying the zero initial condition","authors":"M. Meraz ,&nbsp;P. Castilla ,&nbsp;E.J. Vernon-Carter ,&nbsp;J. Alvarez-Ramirez","doi":"10.1016/j.renene.2024.121816","DOIUrl":"10.1016/j.renene.2024.121816","url":null,"abstract":"<div><div>Biogas produced by the fermentation of organic waste has emerged as a viable alternative for displacing fossil fuels. The accurate characterization of the biogas production kinetics is an important issue for management, optimization, and control purposes. The classical logistic equation (CLE) and its modifications are widely used for modeling biogas production. Although a tight-fitting can be obtained, these models have the physical inconsistency of predicting a non-zero value of initial biogas production. This work fixes the problem found with CLE by deriving a new function, named biogas logistic equation (BLE), from a simple kinetics scheme. The derivation departs from the differential equations for substrate, biomass and biogas obtained via the law of mass action to reduce these equations to a differential equation having an analytical solution. The parameters of the BLE are linked to the parameters of the kinetics scheme, having a meaningful physical interpretation. An extension to the multi-substrate case was proposed, leading to an expression with the flexibility of detecting phase transitions in the biogas production dynamics. Experimental data from the literature showed that the proposed logistic equation has superior fitting performance than the modified Gompertz equations and in most instances to the CLE.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121816"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743207","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":"Development of an engineering-friendly evaluation model for solar spectral irradiance using readily accessible subaerial meteorology","authors":"Shuhao Wang ,&nbsp;Jinqing Peng ,&nbsp;Yimo Luo ,&nbsp;Tao Ma ,&nbsp;Peng Xue ,&nbsp;Yupeng Wu ,&nbsp;Qiangzhi Zhang ,&nbsp;Jiayu Zhou","doi":"10.1016/j.renene.2024.121632","DOIUrl":"10.1016/j.renene.2024.121632","url":null,"abstract":"<div><div>Solar spectral irradiance has a crucial impact on building energy conservation, especially on photovoltaic (PV) generation. However, it takes a high cost to measure and predict the dynamic solar spectral irradiance for various atmosphere conditions and sun positions. Combining with machine learning, this paper developed a novel solar spectral irradiance estimation model to evaluate the annual solar spectral property in a region. This paper employs the readily accessible subaerial meteorology as model input. The average photon energy (APE) serves as a connection between the normalized solar spectral irradiance and the meteorology parameters. Verification showed the model this paper proposed estimated the normalized solar spectral irradiance well. Further, annual simulation of solar spectral irradiance was conducted by inputting typical meteorology year (TMY) dataset. The annual difference of the normalized spectral irradiance reached to 10.57 %, which reflects the great importance to determine the practical solar spectral irradiance. A typical day of spectra was proposed for each month to reveal the monthly variation in solar spectral irradiance. This study provides a convenient technical method to evaluate the solar spectral property for engineering applications. The results may guide industries in selecting suitable solar cells for the region, thereby prompting the development of solar applications.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121632"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756660","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":"Machine learning model with a novel self–adjustment method: A powerful tool for predicting biomass ash fusibility and enhancing its potential applications","authors":"Lin Mu ,&nbsp;Zhen Wang ,&nbsp;Meng Sun ,&nbsp;Yan Shang ,&nbsp;Hang Pu ,&nbsp;Ming Dong","doi":"10.1016/j.renene.2024.121650","DOIUrl":"10.1016/j.renene.2024.121650","url":null,"abstract":"<div><div>Biomass ash has been extensively studied for its potential applications, owing to its high content of alkali and alkaline earth metallic species (AAEMs). These AAEMs can act as catalysts in biomass thermochemical conversion and other industrial processes. However, AAEMs can also cause slagging and agglomeration, which can significantly impact system operations. To better understand these effects, we investigated the relationship between ash melting behavior and the chemical composition of biomass ash using a machine learning (ML) model. To enhance the model's performance, we employed a self-adjustment (SA) method, which significantly improved predictive accuracy. The SA-ETR model achieved an R² value greater than 0.93, based on a dataset of 268 data points. We provided a detailed explanation of the SA-optimized ML model using Python's Shapley Additive Explanations (SHAP) library, which included global and local feature importance analysis, investigation of simultaneous effects between two features, and individual data point prediction analysis. The contents of K₂O, SiO₂, CaO, and Al₂O₃ were considered as the most significant factors affecting biomass ash's initial deformation temperature (IDT). The insights gained from this study can help investors and researchers reduce experimental complexity and improve system operation.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"237 ","pages":"Article 121650"},"PeriodicalIF":9.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756662","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":"Predicting photovoltaic greenhouse irradiance at low-latitudes of plateau based on ultra-short-term time series","authors":"Yinlong Zhu ,&nbsp;Guoliang Li ,&nbsp;Yonglei Jiang ,&nbsp;Ming Li ,&nbsp;Yunfeng Wang ,&nbsp;Ying Zhang ,&nbsp;Yali Liu ,&nbsp;Muchi Yao","doi":"10.1016/j.renene.2024.122053","DOIUrl":"10.1016/j.renene.2024.122053","url":null,"abstract":"<div><div>Accurate and reliable ultra-short-term prediction of solar irradiance in photovoltaic (PV) greenhouses at low-latitude plateau is essential to precisely control electricity consumption of greenhouse equipment and ensure high quality crop yields. However, the irradiance in the low-latitude plateau has problems such as poor data quality, limited short-term prediction accuracy, and insufficient ability to capture nonlinear characteristics. Therefore, in order to achieve efficient utilization of photovoltaic resources, this study proposed a new hybrid integrated model TTAO-CNN-BiGRU-Attention framework to predict ultra-short-term photovoltaic greenhouse irradiance in the region. Monthly and seasonal characteristics of irradiance in low-latitude plateau areas were analyzed by statistical methods. The performance of the proposed model was verified using 9 different models for 5 different data volumes and 4 different seasons. Comprehensive analysis results show that Total radiant instantaneous (TRI) demonstrates a seasonal trend, generally low in spring, high in summer and autumn, relatively stable in autumn and winter. The monthly trend initially increases and then decreases, reaching the highest value of the year in September. The scheme proposed in this paper makes full use of the advantages of CNN, BiGRU, Attention and TTAO, greatly improving the comprehensive prediction ability of the model. In predicting different data amounts, 1 year prediction performance was the best, with RMSE, MAE, MAPE and R² reaching 70.61 W/m², 31 W/m², 9.3 % and 95.84 %, respectively. With regard to different seasons, autumn prediction performance was the best, with RMSE, MAE, MAPE and R² reaching 66.27 W/m², 31.02 W/m², 8.37 % and 95.87 %, respectively. The TRI prediction curve of the proposed model was closer to the actual value than other comparison models. The study found that the TTAO-CNN-BiGRU-Attention model is more accurate and stable than many traditional models in predicting ultra-short-term TRI in low-latitude plateau photovoltaic greenhouses, which can provide a reference for the comprehensive performance of PV greenhouse irradiance prediction models and precise regulation of energy supply in the future.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"239 ","pages":"Article 122053"},"PeriodicalIF":9.0,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759346","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}