Statistical Trends in Wind Speed for Khulna, Bangladesh: An Analytical Approach

Md. Sazedur Rahman, Jannatun Ferdous, Tanjim Taharat Aurpa, Md. Mahfuzul Haque, Md. Abul Kalam Azad and Md. Ahsan Habib
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Md. Sazedur Rahman: Department of Electrical and Electronic Engineering (EEE), Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200, Bangladesh.
Jannatun Ferdous: Department of Electronics and Communication Engineering Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200, Bangladesh.Â
Tanjim Taharat Aurpa: Department of Data Science (DS), Bangabandhu Sheikh Mujibur Rahman Digital University, Gazipur, Dhaka, Bangladesh.
Md. Mahfuzul Haque: Department of Electrical and Electronic Engineering, Bangamata Sheikh Fojilatunnesa Mujib Science and Technology University, Jamalpur-2012, Bangladesh.
Md. Abul Kalam Azad: Electrical Engineering Division, Sheikh Hasina University, Netrokona-2400, Bangladesh.
Md. Ahsan Habib: Department of Electrical and Electronic Engineering, Begum Rokeya University, Rangpur-5400, Bangladesh.

Journal of Scientific Reports, 2022, vol. 7, issue 1, 213-225

Abstract: This study aims to examine the characteristics of the speed of wind and evaluate the prospective of wind power in Khulna, Bangladesh, from 2019 to 2023 using numerical methods. The research involves modeling wind speed data with probability density functions, specifically Weibull and the Rayleigh distributions, every month. By determining the parameters of these distributions, the study seeks to assess how wind power varies over time and its potential for energy generation. The insights gained from comparing these distributions are intended to support decision-making in renewable energy planning, infrastructure investment, and resource allocation. The study's relevance lies in its potential to provide valuable information for effectively harnessing wind energy and making informed decisions about renewable energy utilization.

Keywords: Wind speed data; Rayleigh distribution; Shape factor; Weibull distribution; Wind power. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:aif:report:v:7:y:2024:i:1:p:213-225

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