Numerical Analysis Of Horizontal Axis Wind Turbine (Hawt) Operation Variables And Their Influence On Performance Cycle

Wind turbines have been one of the dependable sources renewable energy that due to its abundance, witnessed constant innovations and quest for design productivity optimization. The commonly used type is Horizontal Turbine also known as Axis (HAWT). Understanding imperative factors influencing functionality HAWT provides insight into optimal design. This study therefore x-rays numerical analysis operation variables their influence on performance parameters. Research Likert questionnaires with  identified weighty were developed distributed trained, knowledgeable experienced wind turbine engineers/operators respondents outcome. A data matrix collated. With identified, iterations computed. Ten (10) clusters (F1 F2) optimised, each cluster consisting computed influential variable(s) input rated (output) maximum value variable, being ranked by 13 judges in Sequential Merit Order (SMO) based HAWT. Kendall’s Coefficient Concordance (w) Principal Component Analysis statistical models employed. Respondents’ scores transposed matrix, fed StatistiXL software; eigenvalues, eigenvectors, factor loadings, descriptive statistics case wise (correlation matrix) w=0.56 (middling) obtained level consistency. coherence/agreement using chi-square model had , ( at ). Therefore, null hypothesis H0 rejected; alternative H1 accepted, which implies strong agreement 95% confidence level.