Kathmandu University International Symposium on Current Research in HydraulicTurbines (CRHT-VII) DESIGN AND CFD ANALYSIS OF PICO HYDRO TURGO TURBINE Sudish Gyanwali 1*, Kush Kuikel 1 and Abinath Thapa 1 1 Department of Mechanical Engineering, Kathmandu University, Dhulikhel, Nepal Supervised by Mr. Atmaram Kayastha Research fellow 4th April, 2017, Kathmandu University Dhulikhel, Nepal 1
Introduction PHP Pico-hydro covers hydroelectric power generation under 5kW. PHP have a lower cost per kilowatt than solar or wind power. Turgo Turbine It is an impulse water turbine It usually have the efficiency of about 87% It is operated in a head range where the Francis and Pelton overlap. Is popular for small hydro where low cost is very important It produces the same power as that of Pelton turbine if it has twice the diameter as that Pelton runner CRHT VII, 2017 Kathmandu University 2
Methodology Research tools used Literature Review Design Analysis Comparison TOOLS MS Excel SOLIDWORKS Creo Parametric 2.0 ANSYS Workbench 13.0 OBJECTIVE Mathematical modeling Designing the 3D model of a bucket Designing the domain of Turgo turbine To generate structured mesh of nozzle, spear and runner CRHT VII, 2017 ANSYS ICEM 13.0 ANSYS CFX 13.0 SigmaPlot To generate structured mesh of casing Performance analysis through simulation Plotting the Main Characteristics Curves Kathmandu University 3
Mathematical modeling Selection parameters Criteria for selection Obtained values Remark PCD Diameter of jet 9.09 8.2 OK Specific speed 10-80 53 OK Head 10-300 10 OK 4
CAD modeling Spear valve Nozzle Casing Bucket stem 5
Meshing Runner Casing Nozzle 6
Meshing, Boundary Conditions & Solver Details Meshing Relevance Center Fine Advanced Size function On curvature Smoothing Medium Transition Slow Inflation option First layer thickness Method Tetra dominant Inflation algorithm Post Working fluid Air (25 ) Water (25 ) Boundary Conditions Inlet the specified value of the velocity Outlet 0 atm pressure Turbulence model SST Turbulent conditions Medium (5%) Interfaces Runner and casing Interfaces model: Transitional periodicity Nozzle and casing Interfaces model: General connection Convergence Minimum 1 Maximum 200 Physical time scale 0.01 seconds Tolerances e-4 Solution Parallel Processors 2 7
Domain Runner Nozzle Casing CRHT VII, 2017 Kathmandu University 8
CFX-pre setup Boundary condition of whole setting 9
Overall efficiency Mass flow rate at inlet Velocity at the outlet Grid Independence Test 9.97 9.965 9.96 9.955 9.95 9.945 9.94 9.935 9.93 9.925 Nozzle 2 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1 Casing Number of Nodes Number of Nodes 100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% Whole setting 1135672 1208607 1380184 1321348 1398742 Number of Nodes 10
Pressure and Velocity distribution Pressure distribution in a plane at Y-axis Velocity distribution in a plane at Y-axis 11
Pressure distribution Pressure distribution in runner Pressure distribution in two consecutive buckets At the places where the jet strikes the value of pressure is 99920 Pa and it decreases to the value of 38250 Pa 12
Performance curve Efficiency Vs N11 Q11 Vs N11 100 0.22 90 0.20 80 0.18 Efficiency 70 60 50 Q11 0.16 0.14 0.12 40 0.10 30 0.08 20 20 25 30 35 40 45 50 55 N11 100% full spear valve opening 70% spear valve opening 25% speat valve opening 0.06 20 25 30 35 40 45 50 55 100% spear valve opening 70% spear valve opening 25% spear valve opening N11 Curve η-n11 indicates that at a particular speed the efficiency is maximum. Q depends only upon gate opening & is independent of N u 13
Hill chart Diagram Hill chart 90 0.20 60 70 80 90 90 80 At the designed condition the 0.18 50 70 BEP is achieved at discharge factor 0.2 (0.044 m 3 /s discharge) and speed factor 38 (453 rpm) Q11 0.16 0.14 40 30 60 50 40 70 60 80 70 80 80 70 60 60 50 at the head of 10m. 0.12 50 70 0.10 30 40 60 60 50 40 50 50 25 30 35 40 45 50 Efficiency contour N11 14
Conclusions The simulations in ANSYS CFX for the Turgo turbine at different opening conditions were performed and performance curve was obtained. The results were obtained using computers with low computational capacity which took more time for simulations. Further work can be done in super computers in order to reduce the computational time and to obtain the accurate result. The result we obtained contain errors, changing mesh quality and refining could be done in future. 15
REFERENCES [1] P. &. D. H. N. B.Rajkarnikar, "Sustainability Issues of Micro Hydropower Plants in Nepal," Nepal, 2010. [2] D. Singh, "Micro Hydro Power Resource Assessment Handbook," 2009. [3] C. Warnick, "Hydro Power Engineering," BULGARIA SERBIA IPA CROSS- BORDER PROGRAMME, 1984. [4] Hydropower Basics, [Online]. Available: https://energypedia.info/wiki/hydro_power_basics#by_size. [Accessed 4 February 2016]. [5] "General classification of turbines," [Online]. Available: https://www.scribd.com/doc/72522271/classification-of-turbines. [Accessed 8 March 2016]. [6] Thake, Jeremy, "The Micro Hydro Pelton Turbine Manual," 2011. [7] E. R. Rajput, A Text Book of Fluid Mehcanics and Hydraulic Machines, Delhi: S. Chand, 2008. 16
Kathmandu University Thank you for your attention! sudish.gyanwali@gmail.com 17