The Effect of Rotor Radius Ratio on The Performance of Hybrid Vertical Axis Wind Turbine Savonius-Darrieus NREL S809

Irawan, Elysa Nensy; Sitompul, Sandro; Yamashita, K.; Fujita, Goro

doi:10.21926/jept.2301001

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…Their study revealed that a hybrid VAWT with the Savonius above the Darrieus can generate more power than a conventional hybrid VAWT. Irawan et al 13 studied the improvements of the hybrid VAWT using the CFD approach. The 2D URANS equations were solved to obtain the complex flow problems in Ansys Fluent.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of an idealized Darrieus–Savonius combined vertical axis wind turbine

Pan,

Ferreira,

van Zuijlen

2024

Wind Energy

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To investigate the effect of force distributions of each turbine component on the power performance of the Darrieus–Savonius combined vertical axis wind turbine (hybrid VAWT), the hybrid VAWT is modeled as idealized turbine under various force distributions. The goal of idealization is to simplify the intricate interactions between the Savonius and Darrieus components. The simulation actuator surfaces with uniform force distributions lead to a cost‐effective way to identify the optimal force distribution of each turbine component. The numerical model was validated against momentum theory. The results demonstrated that the numerical and theoretical results yield similar predictions in the low‐thrust cases but show differences in the high‐thrust cases. The maximum power coefficient of an idealized hybrid VAWT with given thrust coefficient is lower than that of a single actuator. This is a consequence of the nonoptimal loading on the actuator. The results indicate that an idealized hybrid VAWT does not show a significant power increase compared with an optimal single Darrieus rotor. Therefore, the presence of a Savonius rotor inside a Darrieus rotor leads to a lower power output in any circumstance. The hybrid configuration is primarily advantageous for the start‐up performance of the combined rotor, which is not explored in this study.

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Section: Introductionmentioning

confidence: 99%

Performance analysis of an idealized Darrieus–Savonius combined vertical axis wind turbine

Pan,

Ferreira,

van Zuijlen

2024

Wind Energy

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“…These neural solvers combine physics with the flexibility of deep learning by building neural networks in domain knowledge. Neural solvers have been applied to solve differential equations in various fields, including computational fluid dynamics [5,6], thermodynamic prediction [7,8], rigid chemical kinetics, Eikonal equations, and so on [9][10][11]. In the modeling of mechanical dynamics, continuous time can also be modeled by neural ordinary differential equations [10,12].…”

Section: Introductionmentioning

confidence: 99%

PINN-TI: Physical Information embedded in Neural Networks for solving ordinary differential equations with Time-varying Inputs

Zhao,

du,

Shi

et al. 2024

Preprint

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Modeling and predicting the dynamics of multiphysics and multiscale systems with hidden physics methods is often costly, requiring different formulations and complex computer codes. There has been significant progress in solving differential equations using physical information embedded in neural networks, but solving and generalizing for differential equations with time-varying inputs is still an open problem. In this paper, we design a PINN-TI network structure and a Step-by-Step Forward (SSF) algorithm. It enables the network to predict the results of ordinary differential equations under different initial values or boundary conditions and different time-varying inputs (including segmented functions) after one training. Our approach can extend the time domain of the solution to a larger range. We validated our model using a variant of Vander Pol’s equation, which contains one or two external inputs. The results show that our network can handle the prediction and generalization problem of ordinary differential equations under time-varying inputs well. Our method provides a new solution for solving and generalizing differential equations under time-varying inputs.

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“…Despite this drawback, VAWTs have a lot of advantages over HAWTs [8]. As a result, from the beginning through 2022, VAWT's research continues to grow [9].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Non-Overlap and Overlap Savonius Wind Turbines in the Physics Aspect Using Computational Fluid Dynamics Method

Nensy Irawan,

Yamashita,

Fujita

2024

J. Phys.: Conf. Ser.

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Wind energy has good potential as a renewable energy source. Savonius-type wind turbines can provide power generation at a low cost with minimal environmental impact. Due to its low efficiency, researchers were focused on increasing it through many methods, such as applying twisted-bladed, optimizing the blade shape, and applying overlap. Most researchers have studied the effects of overlap on Savonius blades only in terms of performance improvements. This study evaluates the effect of overlap on the Savonius blade from a physics perspective using the Computational Fluid Dynamics method to get a new approach based on the improvement. The models are 2-bladed Savonius with non-overlap and 0.2 overlap. The main software used is Ansys Student 2023 R2. The turbulent model chosen is a realizable k- enhanced wall treatment. Then, pressure and velocity coupling were done using SIMPLE: 2nd order upwind, 1st order implicit. As a result, the overlap model has a higher reverse flow but lower pressure for all Tip Speed Ratio. Another finding shows that turbulent kinetic energy decreases with overlap. For the non-overlap model, the amount of turbulence is greater downstream, which causes vortices to form and lowers turbine performance. So, the effects of the overlap blade result in higher average Torque Coefficient than non-overlap.

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The Effect of Rotor Radius Ratio on The Performance of Hybrid Vertical Axis Wind Turbine Savonius-Darrieus NREL S809

Cited by 9 publications

References 16 publications

Performance analysis of an idealized Darrieus–Savonius combined vertical axis wind turbine

Performance analysis of an idealized Darrieus–Savonius combined vertical axis wind turbine

PINN-TI: Physical Information embedded in Neural Networks for solving ordinary differential equations with Time-varying Inputs

Comparison of Non-Overlap and Overlap Savonius Wind Turbines in the Physics Aspect Using Computational Fluid Dynamics Method

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