THE EFFECT OF HYBRID SAVONIUS AND DARRIEUS TURBINE ON THE CHANGE OF WAKE RECOVERY AND IMPROVEMENT OF WIND ENERGY HARVESTING
The energy crisis encourages the development of renewable energy; one of the potential renewable energy is wind. In the field of wind turbine there is a two-way development of the utilization of wind energy, first by making a large wind turbine, the second by making a wind farm energy with a relatively small wind turbine.This hybrid VAWT wind turbine (Sultan Wind Turbine) is designed to work optimally on a farm array, on a wind turbine farm array will always cause a wake effect that will reduce overall wind turbine and farm array performance, an investigation with a CFD simulation is required to predict how far the wake effect will be before farm array build.The use of simulation software has been widely used to predict the effects of this wake, and experiments in the laboratory have also been done to predict the effects of a wake as well.This study'spurpose is to predict the distance area of the recovery wake behind the wind turbine, this distance which will be the reference distance between wind turbine units and determining the density of the turbine in a farm. Simulation using Computational Fluid Dynamics (CFD), with a method of Multi Frame Reference (MRF). Analysis using descriptive and inferential method in statistics such as mean, Kolmogorov-Smirnov Z and KruskalWalis test.From the analysis of simulation results and data processing descriptively and analytic statistic, it can be concluded from the data given, the distance of x/D=4, wind speed has recovery to the value near the input speed and no significant change to x/D= 9. Then it can be concluded that the distance between two wind turbines that can be used is a distance of 3.6 meters.These data suggest that the hybrid farm array VAWT savonius and darrieus have a higher power density compared to HAWT. From this power density calculation the hybrid VAWT has a greater electrical potential up to 300 percent compared to the HAWT farm array.
Dabiri JO. Potential order-of-magnitude enhancement of wind farm power density via counter-rotating vertical-axis wind turbine arrays. Journal of Renewable and Sustainable Energy. 2011;3:043104.
Robert WW, Sebastian L, John OD. Fish schooling as a basis for vertical axis wind turbine farm design. Bioinspiration & Biomimetics. 2010;5:035005.
Bartl J, Pierella F, Sætrana L. Wake Measurements Behind an Array of Two Model Wind Turbines. Energy Procedia. 2012;24:305-12.
Li Qa, Maeda T, Kamada Y, Ogasawara T, Nakai A, Kasuya T. Investigation of power performance and wake on a straight-bladed vertical axis wind turbine with field experiments. Energy. 2017.
Rolin VFC, Porté-Agel F. Experimental investigation of vertical-axis wind-turbine wakes in boundary layer flow. Renewable Energy. 2018;118:1-13.
Gao X, Yang H, Lu L. Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model. Applied Energy. 2016;174:192-200.
Emami A, Noghreh P. New approach on optimization in placement of wind turbines within wind farm by genetic algorithms. Renewable Energy. 2010;35:1559- 64.
Bansal JC, Farswan P. Wind farm layout using biogeography-based optimization. Renewable Energy. 2017;107:386-402.
Serrano González J, Trigo García ÁL, Burgos Payán M, Riquelme Santos J, González Rodríguez ÁG. Optimal wind-turbine micro-siting of offshore wind farms: A grid-like layout approach. Applied Energy. 2017;200:28-38.
Lam HF, Peng HY. Measurements of the wake characteristics of co- and counter-rotating twin H-rotor vertical axis wind turbines. Energy. 2017;131:13-26.
Bukala J, Damaziak K, Kroszczynski K, Krzeszowiec M, Malachowski J. Investigation of parameters influencing the efficiency of small wind turbines. Journal of Wind Engineering and Industrial Aerodynamics. 2015;146:29-38.
Hezaveh SH, Bou-Zeid E, Lohry MW, Martinelli L. Simulation and wake analysis of a single vertical axis wind turbine. Wind Energy. 2017;20:713-30.
Erwin Erwin SW, Erny Listijorini, Rina Lusiani, Tresna P Soemardi. Development of the Third Darrieus Blade of Sultan Wind Turbine for Low Wind Speed. Applied Mechanics and Materials. 2015;758:7.
González-Longatt F, Wall P, Terzija V. Wake effect in wind farm performance: Steady-state and dynamic behavior. Renewable Energy. 2012;39:329-38.
Zuo W, Wang X, Kang S. Numerical simulations on the wake effect of H-type vertical axis wind turbines. Energy. 2016;106:691-700.
Mohamed MH, Ali AM, Hafiz AA. CFD analysis for H-rotor Darrieus turbine as a low speed wind energy converter. Engineering Science and Technology, an International Journal. 2015;18:1-13.
Nobile R, Vahdati M, Barlow JF, Mewburn-Crook A. Unsteady flow simulation of a vertical axis augmented wind turbine: A two-dimensional study. Journal of Wind Engineering and Industrial Aerodynamics. 2014;125:168-79.
Liu J, Lin H, Purimitla SR. Wakefield studies of tidal current turbines with different numerical methods. Ocean Engineering. 2016;117:383-97.
Rukthong W, Weerapakkaroon W, Wongsiriwan U, Piumsomboon P, Chalermsinsuwan B. Integration of computational fluid dynamics simulation and statistical factorial experimental design of thick-wall crude oil pipeline with heat loss. Advances in Engineering Software. 2015;86:49-54.
Prošek A, Končar B, Leskovar M. Uncertainty analysis of CFD benchmark case using optimal statistical estimator. Nuclear Engineering and Design. 2017;321:132-43.
Hemsch MJ. Statistical Analysis of Computational Fluid Dynamics Solutions from the Drag Prediction Workshop. Journal of Aircraft. 2004;41:95-103.
Ghosh A, Biswas A, Sharma KK, Gupta R. Computational analysis of flow physics of a combined three bladed Darrieus Savonius wind rotor. Journal of the Energy Institute. 2015;88:425-37.
Chowdhury H, Mustary I, Loganathan B, Alam F. Adjacent Wake Effect of a Vertical Axis Wind Turbine. Procedia Engineering. 2015;105:692-7.
Posa A, Parker CM, Leftwich MC, Balaras E. Wake structure of a single vertical axis wind turbine. International Journal of Heat and Fluid Flow. 2016;61:75- 84.
Matthias Kinzel QM, John O. Dabiri. Energy exchange in an array of vertical-axis wind turbines. Journal of Turbulence. 2012;13:13.
Sedaghatizadeh N, Arjomandi M, Kelso R, Cazzolato B, Ghayesh MH. Modelling of wind turbine wake using large eddy simulation. Renewable Energy. 2018;115:1166-76.
Miao W, Li C, Pavesi G, Yang J, Xie X. Investigation of wake characteristics of a yawed HAWT and its impacts on the inline downstream wind turbine using unsteady CFD. Journal of Wind Engineering and Industrial Aerodynamics. 2017;168:60-71.
Naderi S, Torabi F. Numerical investigation of wake behind a HAWT using modified actuator disc method. Energy Conversion and Management. 2017;148:1346-57.
Hu D-m, Du Z-h. Near Wake of a Model Horizontal-Axis Wind Turbine. Journal of Hydrodynamics, Ser B. 2009;21:285-91.
Hemsch, M. J. (2004). "Statistical Analysis of Computational Fluid Dynamics Solutions from the Drag Prediction Workshop." Journal of Aircraft 41(1): 95- 103.
Suto, H., Y. Hattori, et al. (2017). "Computational fluid dynamics simulation and statistical procedure for estimating wide-area distributions of airborne sea salt considering local ground conditions." Structure and Infrastructure Engineering 13(10): 1359-1371.
Migliori, S., C. Chiastra, et al. (2017). "A framework for computational fluid dynamic analyses of patient-specific stented coronary arteries from optical coherence tomography images." Medical Engineering & Physics 47: 105-116.
Thönnißen, F., M. Marnett, et al. (2016). "A numerical analysis to evaluate Betz's Law for vertical axis wind turbines." Journal of Physics: Conference Series 753(2): 022056.
Erwin, E., P. S. Tresna, et al. (2018). "Design optimization of hybrid biomass and wind turbine for minapolitan cluster in Domas, Serang, Banten, Indonesia." IOP Conference Series: Earth and Environmental Science 105(1): 012010.
Satria, D., Haryadi, et al. (2016). "Design of drying chamber and biomass furnace for sun-biomass hybrid rice-drying machine." AIP Conference Proceedings 1717(1): 050015.