Comparison of Wind Energy Generation Using the Maximum Entropy Principle and the Weibull Distribution Function

Muhammad Shoaib, Imran Siddiqui, Shafiqur Rehman, Saif Ur Rehman, Shamim Khan and Aref Lashin
Additional contact information
Muhammad Shoaib: Department of Physics, Federal Urdu University of Arts, Sciences and Technology, Block 9, Gulshan-e-Iqbal, Karachi 75300, Pakistan
Imran Siddiqui: Department of Physics, University of Karachi, Main University Road, Karachi 75270, Pakistan
Shafiqur Rehman: Center for Engineering Research, The Research Institute, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Saif Ur Rehman: Department of Physics, Federal Urdu University of Arts, Sciences and Technology, Block 9, Gulshan-e-Iqbal, Karachi 75300, Pakistan
Shamim Khan: Islamia College Peshawar, University Campus, Peshawar Jamrod Road, Peshawar 25120, Khyber Pakhtunkhwa, Pakistan
Aref Lashin: College of Engineering, Petroleum and Natural Gas Engineering Department, King Saud University, Riyadh 11421, Saudi Arabia

Energies, 2016, vol. 9, issue 10, 1-18

Abstract: Proper knowledge of the wind characteristics of a site is of fundamental importance in estimating wind energy output from a selected wind turbine. The present paper focuses on assessing the suitability and accuracy of the fitted distribution function to the measured wind speed data for Baburband site in Sindh Pakistan. Comparison is made between the wind power densities obtained using the fitted functions based on Maximum Entropy Principle (MEP) and Weibull distribution. In case of MEP-based function a system of (N+1 ) non-linear equations containing ( N+1 ) Lagrange multipliers is defined as probability density function. The maximum entropy probability density functions is calculated for 3–9 low order moments obtained from measured wind speed data. The annual actual wind power density ( P A ) is found to be 309.25 W/m 2 while the Weibull based wind power density ( P W ) is 297.25 W/m 2 . The MEP-based density for orders 5, 7, 8 and 9 ( P E ) is 309.21 W/m 2 , whereas for order 6 it is 309.43 W/m 2 . To validate the MEP-based function, the results are compared with the Weibull function and the measured data. Kolmogorov–Smirnov test is performed between the cdf of the measured wind data and the fitted distribution function ( Q 95 = 0.01457 > Q = 10 ?4 ). The test confirms the suitability of MEP-based function for modeling measured wind speed data and for the estimation of wind energy output from a wind turbine. R 2 test is also performed giving analogous behavior of the fitted MEP-based pdf to the actual wind speed data ( R 2 ~ 0.9). The annual energy extracted using the chosen wind turbine based on Weibull function is P W = 2.54 GWh and that obtained using MEP-based function is P E = 2.57–2.67 GWh depending on the order of moments.

Keywords: Weibull distribution; maximum entropy; modified maximum likelihood method; Baburband; Pakistan (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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