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Priority of Wind Energy in West Coast of Southern Thailand for Installing the Water Pumping Windmill System with Combining of Entropy Weight Method and TOPSIS

Author

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  • Sakon Klongboonjit

    (Industrial Engineering Department, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

  • Tossapol Kiatcharoenpol

    (Industrial Engineering Department, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

Abstract

Wind energy potential or quality serve as the primary determinants influencing the decisions of Thai farmers regarding the installation of water-pumping windmills with heights ranging from 9 to 15 m and a cut-in wind speed requirement of 4 m/s, aimed at reducing their fuel costs. To introduce a simplified calculation method as one of their decision-making tools, the combined approach of the entropy weight method with TOPSIS has been introduced to assist them in prioritizing and assessing the wind quality in their respective areas. This study focuses on the western region of Southern Thailand, known for its high agricultural productivity. Initially, only 18 out of the 227 sub-districts with a minimum monthly wind speed exceeding 4 m/s were selected for thorough investigation. Subsequently, the entropy weight method was applied to the monthly wind speed data of these 18 chosen sub-districts to calculate their monthly weight values. These monthly weight values provide a quantifiable characterization of the wind quality in these specific sub-districts, revealing variations in wind quality between seasons, with superior quality during the summer season compared to the rainy season. Following the calculation of monthly weight values, the TOPSIS technique was applied to the wind data in conjunction with these monthly weight values, resulting in the determination of performance scores (P i ) for each of the 18 sub-districts. P i values were found to vary from 0.0641 to 0.9006. In the final step of the analysis, these 18 sub-districts were ranked based on their respective P i values, with the implication that sub-districts exhibiting higher P i values are more suitable for the installation of water-pumping windmills with heights ranging from 9 to 15 m compared to those with lower P i values.

Suggested Citation

  • Sakon Klongboonjit & Tossapol Kiatcharoenpol, 2023. "Priority of Wind Energy in West Coast of Southern Thailand for Installing the Water Pumping Windmill System with Combining of Entropy Weight Method and TOPSIS," Energies, MDPI, vol. 16(20), pages 1-13, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7097-:d:1259986
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    References listed on IDEAS

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    1. Anqi Wang & Yanhua An & Shuhua Yu, 2023. "Research on the Evaluation of Green Technology Renovation Measurement for Multi-Storey Houses in Severe Cold Regions Based on Entropy-Weight-TOPSIS," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    2. Wei Fu & Jie Sun & Xiaodong Lee, 2023. "Research on the Openness of Digital Platforms Based on Entropy-Weighted TOPSIS: Evidence from China," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    3. Chingulpitak, Sakkarin & Wongwises, Somchai, 2014. "Critical review of the current status of wind energy in Thailand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 312-318.
    4. Mohammed Alghassab, 2023. "A Computational Case Study on Sustainable Energy Transition in the Kingdom of Saudi Arabia," Energies, MDPI, vol. 16(13), pages 1-18, July.
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