Development of Small Domestic Wind Turbine Tower and Blades Systems: An Optimization Approach

Transcription

1 Development of Small Domestic Wind Turbine Tower and Blades Systems: An Optimization Approach Dr. Sachin Modgil Symbiosis Institute of Operations Management, Nashik Abstract The design of experiment has been carried out to design the turbine tower blades. The control factors and levels are identified to design the blade system. This analysis will help to enhance the performance of the power generation to transmission. After designing the experiment the higher- the better case is chosen to achieve the thermodynamic model application. 1. Introduction Taguchi of Nippon Telephones and Telegraph Company, Japan has developed a method based on "ORTHOGONAL ARRAY "experiments which gives much reduced " variance " for the experiment with " optimum settings " of control parameters. Thus the marriage of Design of Experiments with optimization of control parameters to obtain BEST results is achieved in the Taguchi Method. "Orthogonal Arrays" ( OA) provide a set of well balanced (minimum) experiments and Dr. Taguchi's Signal-to-Noise ratios (S/N), which are log functions of desired output, serve as objective functions for optimization, help in data analysis and prediction of optimum results. Building up a clean energy future has been recognized as one of the great challenges of our time. To deal with this challenge, a comprehensive new energy plan was developed, which demands some percent of our electricity to be utilized from renewable resources. An assured use of electricity from renewable resources, such as wind, along with the latest deployment of large turbines that grow to great heights, makes achieving the most efficient and safe designs of the structures that support them incredibly. In attaining this goal, the present work inquires to understand how optimization concepts and suitable optimization capabilities can be involved in wind turbine blades and tower design. Drastic demand of electricity in current generation is of key importance due to the sort of mankind lead. Power production by conventional strategies has taken its toll on environment and the earth has been polluted to degrees beyond imagination. The need of the hour is an alternative and green energy from natural recourses. Technology serves human need and luxuries but still it does not show any impact to our planet. With growing awareness on our needs and priorities one alternative source to draw power would be the wind. 2. Literature Review On the account of manipulation of large number of variables with a small number of experiments, Taguchi approach, a statistical technique is used which handles a set of orthogonal arrays from design of experiments theory. The number of experimental runs to be performed is reduced predominantly by the orthogonal arrays. Furthermore, over the entire Experimental region evolved by the control factors and their settings, valid conclusions pinched off from small scale experimental runs. Earlier discovered noticeable Orthogonal arrays are not unique to Taguchi. In this study the Taguchi approach of experimental design methodology was engaged, with the orthogonal array design involved to analyze the effects of the design parameters, such as base length, top length, tower height and number of sections. The main operational parameters and levels depend upon the experiments conducted and from previously reported studies. 783 Dr. Sachin Modgil

2 Figure 1.Schematic Representation of the Steps Involved in the Taguchi Optimization Procedure. 3. Methodology Step 1: Statement of the Problem. To satisfy the growing electricity generation demand through an alternative of green energy from natural resources green energy from natural resources i.e. wind energy & windmill in combination with Taguchi s optimization approach to determine the optimum engine design and operating parameters. Step 2: Objectives of Study. To understand the deployment of Taguchi approach for problem-solving; To introduce a systematic 10 step Taguchi approach; To determine the optimum engine design and operating parameters of small domestic wind turbine tower and blades system. Step 3: Measurement System Analysis. Gauge R&R is calculated for all applicable measurements such as instability in reduced power generation, space of installation, reduced power loss generation to transmission, etc. and found that it is well within limits. The concept of measurement system analysis was deployed to minimize the error in measuring the experimental output by ensuring the accuracy of the inspection tools and equipmentand also by training the operator in rating the parameters. Step 4: Identification of Stability Characteristics that is to be optimized. The experts of the product design department, production operation department and equipment management department determined the main factors affecting the affecting the wastage of electricity from generation to transmission system by using the brainstorming method and maximizing the spindle transmission stability. Step 5: Identification of the Controllable Factors and Factor Levels that are affecting Spindle Transmission Stability. 784 Dr. Sachin Modgil

3 The outcomes of brainstorming have been used for understanding the cause and effect relationships between parameters and windmill power transmission stability. The five significant process parameters that are identified as control parameters, along with the factor levels, are presented in Table 2. Table-2- Parameters, factors and levels Design Unit Symbol Level 1 Level 2 Level 3 parameter Base length m A Top length m B Tower height m C Number of D sections Step 6: Development of Experimentation Design After collecting information about the factors and factor levels, the experimental design is prepared. The experimental design was prepared by considering two replications on each run for windmill Stability as shown in Table 3. Table 3 Taguchi Design of Experiment Base length Top length Tower height Number of sections R1 R Step 7: Conducting Experimentation. As per the design shown in Table 3, two experiments were conducted for each of sixteen treatments (3 * 9 = 27) and windmill transmission Stability is tested and the value were predicted by Minitab for optimal setting after analyses are shown in Table 4. Here windmill power generation to transmission Stability is considered as smaller the better. Table-4- Experimental design output Base length 785 Dr. Sachin Modgil Top length Tower height Number of sections R1 R

4 Response Table for S/N Ratio for windmill power generation to transmission Stability vs. A, B, C, D, E& F smaller the Better. Table-5- S/N ratios Level Base Length Top Length Tower Length No. Sections Delta Rank Response Table for Mean for windmill power generation to transmission Stability vs. A, B, C, D, E& F Smaller the Better Table-6- Means Level Base Length Top Length Tower Length No. of Sec Delta Rank Step 8: Analysis of Data Analysis of data of Windmill power generation to transmission Stability by ANOVA and Taguchi approach, interpretation of analyses and selection of the optimum levels. The General Linear Model for ANOVA has been developed to investigate the effect of nine input variables, viz., A, B, C&D. From ANOVA table, it is concluded that in case of STS, all ten input variables, viz., A, B, C&D all the p-values are greater than 0.05except B, thus these parameters are significantly affecting the stability of windmill power generation to transmission. Table-6- Analysis of variance Source DF Seq SS AdjSS AdjMS F P Base Top Tower No Error Total Table-7- Optimal Levels of Factors Sr. No. Name of the Factor Unit of Measure No. of Factor Levels Optimal Level 1 A mm B mm C D of 786 Dr. Sachin Modgil

5 The optimal setting as shown in table below has been arrived after developing and observing main effect plots for S/N ratio and means windmill power generation to transmission Stability as shown in Figures 2 and 3 below. Main Effect Plots of windmill power generation to transmission Stability for S/N Ratio Figure-2 Main effect plot for S/N ratio Main Effects Plot of windmill power generation to transmission Stability for Means. Figure-3 Main effect plot for means Step 9: Prediction of the Expected Results for Optimal Setting The windmill power generation to transmission stability content has been predicted by Minitab for optimal setting that is arrived after analyses is as follows: Optimal setting-1: Factor levels for prediction of windmill power generation to transmission Stability. 787 Dr. Sachin Modgil

6 A B C D Predicted values S/N Ratio Mean Step 10: Validation of Optimal Setting Validation has been done and mean of 90 to is achieved and confirmed after a trial of 20 days. 4. Conclusion: The Taguchi s approach based thermodynamic modeling analysis has been carried out for optimizing the performance of windmill power generation to transmission. The various input parameters of the model have been optimized using SNR. The higher-the-better quality characteristic has been used for maximizing the thermal efficiency of the windmill.hence, Taguchi s approach based thermodynamic model application can be extended to study the suitability of different types of biodiesel under research for optimization of windmill performance. References [1.] Taguchi G, Konishi S,Taguchi Methods, orthogonal arrays and linear graphs, tools for quality American supplier institute, American Supplier Institute; 1987 [p. 8-35] [2.] Rao, RavellaSreenivas; C. Ganesh Kumar, R. ShettyPrakasham, Phil J. Hobbs, The Taguchi Methodology as a statistical tool for biotechnological applications: A critical appraisal, Biotechnology Journal 3 (4): [3.] W.T. Foster, Basic Taguchi design of experiments, National Association of Industrial Technology Conference, Pittsburgh, PA, 2000 [4.] DomnitaFratilia, CristianCaizar, Application of Taguchi method to selection of optimal lubrication and cutting conditions in face milling of AlMg3, Journal of Cleaner Production 19 (2011) [5.] Ernest Doebelin, Engineering Experimentation, Tata MCGRAW HILL Publication 788 Dr. Sachin Modgil