E. Torres-Moreno, V. Moreno-Oliva, M. Campos-García, J. R. Dorrego-Portela, Orlando Lastres-Danguillecourt, N. Farrera-Vázquez
This study introduces a metrological approach to measure the aerodynamic shape and the twist of a wind turbine blade. The optical profilometer measurement technique used is laser triangulation. A camera records the image of a line projected onto a section of the blade and, by reconstructing the airfoil shape, the twist angular position of the profile with respect to the axial line of the blade is determined. This methodology is applied to test different sections of a Wortmann FX 63-137 airfoil with a length of 1700 mm. The results of the aerodynamic shape and twist angle are quantitatively verified by comparing them with the ideal or design values. The reconstruction process achieved a resolution of 0.06 mm, and measurement errors in the twist angular position were less than 0.1°. The presented method is efficient, accurate, and low cost to evaluate the blade profiles of low-power wind turbines. However, due to its easy implementation, it is expected to be able to measure any full-scale wind blade profile up to several meters in length.
本研究介绍了一种测量风力涡轮机叶片气动形状和扭曲度的计量方法。采用的光学轮廓仪测量技术是激光三角测量法。相机记录投射到叶片截面上的线条图像，通过重建翼面形状，确定轮廓相对于叶片轴线的扭曲角度位置。这种方法适用于测试长度为 1700 毫米的 Wortmann FX 63-137 机翼的不同部分。通过与理想值或设计值进行比较，对气动外形和扭转角的结果进行了定量验证。重建过程的分辨率达到了 0.06 毫米，扭转角位置的测量误差小于 0.1°。所提出的方法高效、准确、低成本，可用于评估小功率风力涡轮机的叶片轮廓。不过，由于该方法易于实施，预计可用于测量长度达数米的任何全尺寸风力叶片剖面。
{"title":"Use of an optical profilometer to measure the aerodynamic shape and the twist of a wind turbine blade","authors":"E. Torres-Moreno, V. Moreno-Oliva, M. Campos-García, J. R. Dorrego-Portela, Orlando Lastres-Danguillecourt, N. Farrera-Vázquez","doi":"10.1063/5.0176454","DOIUrl":"https://doi.org/10.1063/5.0176454","url":null,"abstract":"This study introduces a metrological approach to measure the aerodynamic shape and the twist of a wind turbine blade. The optical profilometer measurement technique used is laser triangulation. A camera records the image of a line projected onto a section of the blade and, by reconstructing the airfoil shape, the twist angular position of the profile with respect to the axial line of the blade is determined. This methodology is applied to test different sections of a Wortmann FX 63-137 airfoil with a length of 1700 mm. The results of the aerodynamic shape and twist angle are quantitatively verified by comparing them with the ideal or design values. The reconstruction process achieved a resolution of 0.06 mm, and measurement errors in the twist angular position were less than 0.1°. The presented method is efficient, accurate, and low cost to evaluate the blade profiles of low-power wind turbines. However, due to its easy implementation, it is expected to be able to measure any full-scale wind blade profile up to several meters in length.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139457599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Giammichele, V. D’Alessandro, M. Falone, R. Ricci
Nowadays, wind energy plays a central role in the renewable energy production, and the optimization of wind turbine performance is the focus of current research studies. In this context, morphing trailing edge system could be a promising solution to enhance wind turbine blades' aerodynamic performance. In this paper, an innovative morphing trailing edge system was designed, developed, and tested to improve the performance of a wind turbine blade airfoil. The trailing edge deformation is electrically operated through piezoelectric actuators and a compliant surface. Wind tunnel tests were performed for the sake of system validation at Reynolds number equal to 1.75×105 and 3.5×105 and an angle of attack ranging from −8° to 8°. The results put in evidence the effectiveness of the proposed morphing trailing edge system to enhance the aerodynamic performance. The trailing edge deformation allows to increase or decrease the lift coefficient. The mean percentage difference of lift coefficient was found equal to −83.6% and 68.4% for an upward and downward deflection, respectively. Meanwhile, the drag coefficient does not have a significant variation. Consequently, the aerodynamic efficiency will be increased or decreased keeping the angle of attack unchanged. The mean percentage difference of efficiency was found equal to −83.2% and 77.5% for an upward and downward deflection, respectively. In this way, it would be possible to optimize wind turbine blades' efficiency and production under different operating conditions.
{"title":"Experimental assessment of a morphing trailing edge device for wind turbine blade performance improvement","authors":"L. Giammichele, V. D’Alessandro, M. Falone, R. Ricci","doi":"10.1063/5.0174768","DOIUrl":"https://doi.org/10.1063/5.0174768","url":null,"abstract":"Nowadays, wind energy plays a central role in the renewable energy production, and the optimization of wind turbine performance is the focus of current research studies. In this context, morphing trailing edge system could be a promising solution to enhance wind turbine blades' aerodynamic performance. In this paper, an innovative morphing trailing edge system was designed, developed, and tested to improve the performance of a wind turbine blade airfoil. The trailing edge deformation is electrically operated through piezoelectric actuators and a compliant surface. Wind tunnel tests were performed for the sake of system validation at Reynolds number equal to 1.75×105 and 3.5×105 and an angle of attack ranging from −8° to 8°. The results put in evidence the effectiveness of the proposed morphing trailing edge system to enhance the aerodynamic performance. The trailing edge deformation allows to increase or decrease the lift coefficient. The mean percentage difference of lift coefficient was found equal to −83.6% and 68.4% for an upward and downward deflection, respectively. Meanwhile, the drag coefficient does not have a significant variation. Consequently, the aerodynamic efficiency will be increased or decreased keeping the angle of attack unchanged. The mean percentage difference of efficiency was found equal to −83.2% and 77.5% for an upward and downward deflection, respectively. In this way, it would be possible to optimize wind turbine blades' efficiency and production under different operating conditions.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139539419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Linsheng Dai, Zhumei Luo, Tao Guo, Haocheng Chao, Guanghe Dong, Zhikai Hu
With the increase in wind farms in hilly terrain, it is particularly important to explore the downstream wake expansion of wind turbines in hilly terrains. This study established two complex terrain-applicable super-Gaussian wake models based on the Coanda effect and the wind speed-up phenomenon. Then, by considering the wind shear effect and the law of mass conservation, two three-dimensional (3D) super-Gaussian wake models were obtained. The 3D super-Gaussian models were used to describe the shape of the wake deficit and could reflect the wake changes in the full wake region. The introduction of the Coanda effect could reflect the sinking of the wind turbine wake on the top of a hilly terrain. And considering that the wind speed-up phenomenon could better reflect the incoming velocity distribution of the actual hilly terrain. The validation results demonstrated that the prediction results of the 3D super-Gaussian wake models had negligible relative errors compared to the measured data and could better describe the vertical and horizontal expansion changes of the downstream wake. The models established in this study can assist with the development of complex terrain models and super-Gaussian models, as well as providing guidance for power prediction and wind turbine control strategies in complex terrain.
{"title":"Two three-dimensional super-Gaussian wake models for hilly terrain","authors":"Linsheng Dai, Zhumei Luo, Tao Guo, Haocheng Chao, Guanghe Dong, Zhikai Hu","doi":"10.1063/5.0174297","DOIUrl":"https://doi.org/10.1063/5.0174297","url":null,"abstract":"With the increase in wind farms in hilly terrain, it is particularly important to explore the downstream wake expansion of wind turbines in hilly terrains. This study established two complex terrain-applicable super-Gaussian wake models based on the Coanda effect and the wind speed-up phenomenon. Then, by considering the wind shear effect and the law of mass conservation, two three-dimensional (3D) super-Gaussian wake models were obtained. The 3D super-Gaussian models were used to describe the shape of the wake deficit and could reflect the wake changes in the full wake region. The introduction of the Coanda effect could reflect the sinking of the wind turbine wake on the top of a hilly terrain. And considering that the wind speed-up phenomenon could better reflect the incoming velocity distribution of the actual hilly terrain. The validation results demonstrated that the prediction results of the 3D super-Gaussian wake models had negligible relative errors compared to the measured data and could better describe the vertical and horizontal expansion changes of the downstream wake. The models established in this study can assist with the development of complex terrain models and super-Gaussian models, as well as providing guidance for power prediction and wind turbine control strategies in complex terrain.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139455595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rosemary O. Paul-Okore, Chima C. Ike, Godswill N. Nwaji, O. C. Nwufo, N. Ogueke, E. E. Anyanwu
A transient performance of a porous evaporative cooling system was carried out using mathematical models developed from the first principles. The models are based on energy and mass balance analysis on different sections of the evaporative cooler. The developed models were solved using a FlexPDE computational fluid dynamics analyzer, based on the finite element, to generate numerical solutions. The models developed were validated using experimental data from a properly designed, constructed, and tested an evaporative cooler and subsequently used to determine the evaporative cooler performance during four different periods of the year covering the two major climatic seasons experienced in Nigeria. Results obtained showed a reduction in the storage chamber temperature by up to 9 °C from the ambient air condition which was within the range of 22–33 °C. Furthermore, it was observed that it performs best during the dry seasons as compared to the wet season. However, during both seasons, the cooling chamber temperature significantly remained below the ambient value. Thus, the evaporative cooler can serve as an effective means of reducing heat-induced post-harvest losses incurred by farmers while also helping in combating climate change since it uses only water and does not require any external energy input.
根据第一原理开发的数学模型对多孔蒸发冷却系统的瞬态性能进行了分析。这些模型基于蒸发冷却器不同部分的能量和质量平衡分析。使用基于有限元的 FlexPDE 计算流体动力学分析仪对所开发的模型进行求解，以生成数值解。利用适当设计、建造和测试的蒸发冷却器的实验数据对所开发的模型进行了验证，随后用于确定蒸发冷却器在一年中四个不同时期的性能，涵盖尼日利亚经历的两个主要气候季节。结果表明，与 22-33 °C 范围内的环境空气条件相比，储藏室温度最多可降低 9 °C。此外，据观察，与雨季相比，旱季的性能最佳。不过，在这两个季节，冷却室的温度都明显低于环境温度。因此，蒸发冷却器可以作为一种有效的手段，减少农民因高温而造成的收获后损失，同时也有助于应对气候变化，因为它只使用水，不需要任何外部能源输入。
{"title":"A transient performance evaluation of a porous evaporative cooler for preservation of fruits and vegetables","authors":"Rosemary O. Paul-Okore, Chima C. Ike, Godswill N. Nwaji, O. C. Nwufo, N. Ogueke, E. E. Anyanwu","doi":"10.1063/5.0179085","DOIUrl":"https://doi.org/10.1063/5.0179085","url":null,"abstract":"A transient performance of a porous evaporative cooling system was carried out using mathematical models developed from the first principles. The models are based on energy and mass balance analysis on different sections of the evaporative cooler. The developed models were solved using a FlexPDE computational fluid dynamics analyzer, based on the finite element, to generate numerical solutions. The models developed were validated using experimental data from a properly designed, constructed, and tested an evaporative cooler and subsequently used to determine the evaporative cooler performance during four different periods of the year covering the two major climatic seasons experienced in Nigeria. Results obtained showed a reduction in the storage chamber temperature by up to 9 °C from the ambient air condition which was within the range of 22–33 °C. Furthermore, it was observed that it performs best during the dry seasons as compared to the wet season. However, during both seasons, the cooling chamber temperature significantly remained below the ambient value. Thus, the evaporative cooler can serve as an effective means of reducing heat-induced post-harvest losses incurred by farmers while also helping in combating climate change since it uses only water and does not require any external energy input.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140517257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wind farm design generally relies on the use of historical data and analytical wake models to predict farm quantities, such as annual energy production (AEP). Uncertainty in input wind data that drive these predictions can translate to significant uncertainty in output quantities. We examine two sources of uncertainty stemming from the level of description of the relevant meteorological variables and the source of the data. The former comes from a standard practice of simplifying the representation of the wind conditions in wake models, such as AEP estimates based on averaged turbulence intensity (TI), as opposed to instantaneous. Uncertainty from the data source arises from practical considerations related to the high cost of in situ measurements, especially for offshore wind farms. Instead, numerical weather prediction (NWP) modeling can be used to characterize the more exact location of the proposed site, with the trade-off of an imperfect model form. In the present work, both sources of input uncertainty are analyzed through a study of the site of the future Vineyard Wind 1 offshore wind farm. This site is analyzed using wind data from LiDAR measurements located 25 km from the farm and NWP data located within the farm. Error and uncertainty from the TI and data sources are quantified through forward analysis using an analytical wake model. We find that the impact of TI error on AEP predictions is negligible, while data source uncertainty results in 0.4%–3.7% uncertainty over feasible candidate hub heights for offshore wind farms, which can exceed interannual variability.
{"title":"Evaluation of wind resource uncertainty on energy production estimates for offshore wind farms","authors":"Kerry S. Klemmer, Emily P. Condon, M. Howland","doi":"10.1063/5.0166830","DOIUrl":"https://doi.org/10.1063/5.0166830","url":null,"abstract":"Wind farm design generally relies on the use of historical data and analytical wake models to predict farm quantities, such as annual energy production (AEP). Uncertainty in input wind data that drive these predictions can translate to significant uncertainty in output quantities. We examine two sources of uncertainty stemming from the level of description of the relevant meteorological variables and the source of the data. The former comes from a standard practice of simplifying the representation of the wind conditions in wake models, such as AEP estimates based on averaged turbulence intensity (TI), as opposed to instantaneous. Uncertainty from the data source arises from practical considerations related to the high cost of in situ measurements, especially for offshore wind farms. Instead, numerical weather prediction (NWP) modeling can be used to characterize the more exact location of the proposed site, with the trade-off of an imperfect model form. In the present work, both sources of input uncertainty are analyzed through a study of the site of the future Vineyard Wind 1 offshore wind farm. This site is analyzed using wind data from LiDAR measurements located 25 km from the farm and NWP data located within the farm. Error and uncertainty from the TI and data sources are quantified through forward analysis using an analytical wake model. We find that the impact of TI error on AEP predictions is negligible, while data source uncertainty results in 0.4%–3.7% uncertainty over feasible candidate hub heights for offshore wind farms, which can exceed interannual variability.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139455777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chenxu Wang, Yixi Zhou, Yan Peng, Xiaohua Xuan, Deqiang Gan, Junchao Ma
In recent years, the increasing integration of renewable energy and electric vehicles has exacerbated uncertainties in power systems. Operators are interested in identifying potential violation events such as overvoltage and overload via probabilistic power flow calculations. Evaluating the violation probabilities requires sufficient accuracy in tail regions of the output distributions. However, the conventional Monte Carlo simulation and importance sampling typically require numerous samples to achieve the desired accuracy. The required power flow simulations result in substantial computational burdens. This study addresses this challenge by proposing a surrogate-assisted importance sampling method. Specifically, a high-fidelity radial basis function-based surrogate is constructed to approximate the nonlinear power flow model. Subsequently, the surrogate is embedded in the conventional importance sampling technique to evaluate the rare probabilities with high efficiency and reasonable accuracy. The computational strengths of the proposed method are validated in the IEEE 14-bus, 118-bus, and realistic 736-bus systems through comparisons with several well-developed methods. The comparisons provide a reference for system operators to select the appropriate method for evaluating violations based on the intended applications.
{"title":"Efficient surrogate-assisted importance sampling for rare event assessment in probabilistic power flow","authors":"Chenxu Wang, Yixi Zhou, Yan Peng, Xiaohua Xuan, Deqiang Gan, Junchao Ma","doi":"10.1063/5.0177383","DOIUrl":"https://doi.org/10.1063/5.0177383","url":null,"abstract":"In recent years, the increasing integration of renewable energy and electric vehicles has exacerbated uncertainties in power systems. Operators are interested in identifying potential violation events such as overvoltage and overload via probabilistic power flow calculations. Evaluating the violation probabilities requires sufficient accuracy in tail regions of the output distributions. However, the conventional Monte Carlo simulation and importance sampling typically require numerous samples to achieve the desired accuracy. The required power flow simulations result in substantial computational burdens. This study addresses this challenge by proposing a surrogate-assisted importance sampling method. Specifically, a high-fidelity radial basis function-based surrogate is constructed to approximate the nonlinear power flow model. Subsequently, the surrogate is embedded in the conventional importance sampling technique to evaluate the rare probabilities with high efficiency and reasonable accuracy. The computational strengths of the proposed method are validated in the IEEE 14-bus, 118-bus, and realistic 736-bus systems through comparisons with several well-developed methods. The comparisons provide a reference for system operators to select the appropriate method for evaluating violations based on the intended applications.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140519954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
China, a country with a long-standing agricultural legacy, is increasingly prioritizing the reduction of CO2 emissions from its agricultural sector. Initially, the carbon emission sources within the agricultural sector are classified into two categories: direct and indirect emissions. Using this classification, the study calculates the generalized agricultural carbon emissions (GACEs) of 30 provinces in China between 2011 and 2020. To further understand the factors influencing GACEs, the paper employs the logarithmic mean Divisia index method and Tapio decoupling index to analyze seven key factors. These factors include carbon emission intensity, energy consumption of generalized agriculture, and economic benefit level of energy consumption. By comparing the impact and changes of GACEs during the 12th and 13th five-year plan periods, the study reveals valuable insights. The findings suggest that carbon emission intensity plays a crucial role in suppressing GACEs, while the level of economic development acts as a catalyst for their increase. By effectively managing these influencing factors, the paper proposes that the increase in GACEs can be effectively suppressed, and the achievement of agricultural CO2 reduction goals can be expedited.
{"title":"Inter-provincial factors decomposition and decoupling analysis of generalized agricultural carbon emissions in China","authors":"Lei Wen, Wenyu Xue","doi":"10.1063/5.0167854","DOIUrl":"https://doi.org/10.1063/5.0167854","url":null,"abstract":"China, a country with a long-standing agricultural legacy, is increasingly prioritizing the reduction of CO2 emissions from its agricultural sector. Initially, the carbon emission sources within the agricultural sector are classified into two categories: direct and indirect emissions. Using this classification, the study calculates the generalized agricultural carbon emissions (GACEs) of 30 provinces in China between 2011 and 2020. To further understand the factors influencing GACEs, the paper employs the logarithmic mean Divisia index method and Tapio decoupling index to analyze seven key factors. These factors include carbon emission intensity, energy consumption of generalized agriculture, and economic benefit level of energy consumption. By comparing the impact and changes of GACEs during the 12th and 13th five-year plan periods, the study reveals valuable insights. The findings suggest that carbon emission intensity plays a crucial role in suppressing GACEs, while the level of economic development acts as a catalyst for their increase. By effectively managing these influencing factors, the paper proposes that the increase in GACEs can be effectively suppressed, and the achievement of agricultural CO2 reduction goals can be expedited.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139636868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Micro energy grids (MEGs) play a vital role in realizing carbon neutrality and efficient utilization of renewable energy resources. This research focuses on optimizing the synergy of MEG interconnections. Given the diverse development paths of different operating entities within the system, information barriers emerge among MEGs, creating great difficulties for the collaborative system management. In response, this paper proposes a decentralized coordinated dispatch model targeting multiple stakeholders within the system. This model accounts for energy interactions between MEGs and the inherent uncertainty associated with renewable energy sources. Specifically, stochastic optimization approach was applied to characterize the uncertainty of renewable energy output by generating stochastic scenarios. Furthermore, it incorporates the analytical target cascading (ATC) method to decouple objective functions and constraints, creating autonomous scheduling sub-models for individual MEGs. This decentralized approach ensures independent modeling and coordinated problem-solving. Simulations verify that (1) the ATC-based inter-MEG energy interaction strategy effectively achieves decentralized coordinated scheduling of multiple MEGs and (2) the decentralized coordinated scheduling solution closely approximates the global optimum while considering the interest of various system entities.
微能源网（MEG）在实现碳中和及有效利用可再生能源方面发挥着至关重要的作用。这项研究的重点是优化 MEG 互联的协同作用。由于系统内不同运营实体的发展路径各不相同，MEG 之间出现了信息壁垒，给系统的协同管理带来了巨大困难。为此，本文提出了一种针对系统内多个利益相关方的分散式协调调度模型。该模型考虑了 MEG 之间的能源互动以及与可再生能源相关的固有不确定性。具体来说，该模型采用随机优化方法，通过生成随机情景来描述可再生能源输出的不确定性。此外，它还结合了分析目标级联（ATC）方法，将目标函数和约束条件解耦，为单个 MEG 创建自主调度子模型。这种分散方法确保了独立建模和协调解决问题。模拟验证了：(1) 基于 ATC 的 MEG 间能源互动策略有效地实现了多个 MEG 的分散协调调度；(2) 分散协调调度解决方案接近全局最优，同时考虑了各系统实体的利益。
{"title":"A decentralized dispatch model for multiple micro energy grids system considering renewable energy uncertainties and energy interactions","authors":"Shengli Si, Wei Sun, Yuwei Wang","doi":"10.1063/5.0192716","DOIUrl":"https://doi.org/10.1063/5.0192716","url":null,"abstract":"Micro energy grids (MEGs) play a vital role in realizing carbon neutrality and efficient utilization of renewable energy resources. This research focuses on optimizing the synergy of MEG interconnections. Given the diverse development paths of different operating entities within the system, information barriers emerge among MEGs, creating great difficulties for the collaborative system management. In response, this paper proposes a decentralized coordinated dispatch model targeting multiple stakeholders within the system. This model accounts for energy interactions between MEGs and the inherent uncertainty associated with renewable energy sources. Specifically, stochastic optimization approach was applied to characterize the uncertainty of renewable energy output by generating stochastic scenarios. Furthermore, it incorporates the analytical target cascading (ATC) method to decouple objective functions and constraints, creating autonomous scheduling sub-models for individual MEGs. This decentralized approach ensures independent modeling and coordinated problem-solving. Simulations verify that (1) the ATC-based inter-MEG energy interaction strategy effectively achieves decentralized coordinated scheduling of multiple MEGs and (2) the decentralized coordinated scheduling solution closely approximates the global optimum while considering the interest of various system entities.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139637108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aerodynamic performance of wind turbine governs the overall energy efficiency, which has been an ever-lasting research focus in the field of wind power technology. Due to the coupling effect among the highly complex environmental and structural uncertainties, the practical aerodynamic performance may not be reliably predicted. To aggravate, this performance declines with time in service. It is of great significance to efficiently and reliably assess the impact of uncertain factors and reduce these influences on wind turbine aerodynamic performance. This paper establishes an uncertainty analysis and robustness optimization model of wind turbine aerodynamic performance considering wind speed and pitch angle error uncertainties. An approach combined the no-instrusive probabilistic collocation method is used, and the blade element momentum theory is applied to quantify influences of variable uncertainties on NREL 5 MW wind turbine aerodynamic performance. The optimization target is to reduce the sensitivity of wind turbine aerodynamic performance to uncertainties, as well as maintain capture power. The results show that the wind turbine aerodynamic and mechanical performance will be greatly affected with uncertain factors. By optimizing and adjusting wind turbine rotor speed and blade pitch angle, the wind turbine rotor power and thrust load variation can be reduced to 9.14% and 9.36%, respectively, which indeed reduces the uncertainty effects.
{"title":"Optimization and control strategy for wind turbine aerodynamic performance under uncertainties","authors":"Hongyan Tian, Zhihao Tang, Heng Ouyang, Rong Wang, Fang Wang, Shuyong Duan","doi":"10.1063/5.0167442","DOIUrl":"https://doi.org/10.1063/5.0167442","url":null,"abstract":"Aerodynamic performance of wind turbine governs the overall energy efficiency, which has been an ever-lasting research focus in the field of wind power technology. Due to the coupling effect among the highly complex environmental and structural uncertainties, the practical aerodynamic performance may not be reliably predicted. To aggravate, this performance declines with time in service. It is of great significance to efficiently and reliably assess the impact of uncertain factors and reduce these influences on wind turbine aerodynamic performance. This paper establishes an uncertainty analysis and robustness optimization model of wind turbine aerodynamic performance considering wind speed and pitch angle error uncertainties. An approach combined the no-instrusive probabilistic collocation method is used, and the blade element momentum theory is applied to quantify influences of variable uncertainties on NREL 5 MW wind turbine aerodynamic performance. The optimization target is to reduce the sensitivity of wind turbine aerodynamic performance to uncertainties, as well as maintain capture power. The results show that the wind turbine aerodynamic and mechanical performance will be greatly affected with uncertain factors. By optimizing and adjusting wind turbine rotor speed and blade pitch angle, the wind turbine rotor power and thrust load variation can be reduced to 9.14% and 9.36%, respectively, which indeed reduces the uncertainty effects.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140525509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Chinese government is committed to achieve the goal of “double carbon” and proposes to shift from double control of energy consumption to double control of carbon emissions. In this scenario, it is of great theoretical and practical significance to study the impact of renewable energy transformation (RET) and technological innovation on carbon productivity (CP). Based on panel data obtained from 30 provinces of China from 2004 to 2021, this study empirically investigated the influence of RET and technological innovation on CP by using panel mean group (MG) estimation. For robustness test, ordinary least squares estimation method was adopted. The main conclusions are as follows: First, based on MG estimation, it was observed that RET has significant positive impact on CP in China. However, the coefficient of technological innovation was found to be significantly negative, indicating that enhancing technological innovation can improve CP. Additionally, the findings showed that economic development and industrial upgradation had a positive impact on CP. Second, the heterogeneity study showed that the RET in the eastern and western regions of China can improve CP. The coefficient of RET in the western region was significantly higher than that in the eastern region. The technological innovation coefficients in the eastern and central regions were significantly positive and enhancing technological innovation in these two regions can considerably improve CP; the technological innovation coefficient in the eastern region was higher than that in the central region. The Gross Domestic Product (GDP) coefficients of the three regions were significantly positive and enhancing economic development can increase CP in these three regions. Finally, to improve CP, it is suggested to promote RET, increase investment in research and development, enhance technological innovation, emphasize high-quality development, prioritize adapting to local conditions, and implement region-appropriate policies and measures.
{"title":"How do renewable energy transformation and technological innovation promote carbon productivity? Empirical evidence from China","authors":"Xiaohong Liu","doi":"10.1063/5.0188018","DOIUrl":"https://doi.org/10.1063/5.0188018","url":null,"abstract":"The Chinese government is committed to achieve the goal of “double carbon” and proposes to shift from double control of energy consumption to double control of carbon emissions. In this scenario, it is of great theoretical and practical significance to study the impact of renewable energy transformation (RET) and technological innovation on carbon productivity (CP). Based on panel data obtained from 30 provinces of China from 2004 to 2021, this study empirically investigated the influence of RET and technological innovation on CP by using panel mean group (MG) estimation. For robustness test, ordinary least squares estimation method was adopted. The main conclusions are as follows: First, based on MG estimation, it was observed that RET has significant positive impact on CP in China. However, the coefficient of technological innovation was found to be significantly negative, indicating that enhancing technological innovation can improve CP. Additionally, the findings showed that economic development and industrial upgradation had a positive impact on CP. Second, the heterogeneity study showed that the RET in the eastern and western regions of China can improve CP. The coefficient of RET in the western region was significantly higher than that in the eastern region. The technological innovation coefficients in the eastern and central regions were significantly positive and enhancing technological innovation in these two regions can considerably improve CP; the technological innovation coefficient in the eastern region was higher than that in the central region. The Gross Domestic Product (GDP) coefficients of the three regions were significantly positive and enhancing economic development can increase CP in these three regions. Finally, to improve CP, it is suggested to promote RET, increase investment in research and development, enhance technological innovation, emphasize high-quality development, prioritize adapting to local conditions, and implement region-appropriate policies and measures.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140525556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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