KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 2 of 2
  • Some of the metrics are blocked by your 
    Item type:Item,
    Assessment of Potential Area for Solar Energy Investment in Northeastern Thailand by Entropy-TOPSIS Method
    (2024-01-01)
    Phonphoon, Phichata
    ;
    Kiatcharoenpol, Tossapol
    ;
    Klongboonjit, Sakon
    Agriculture is one of the important engines of Thailand's food industrial growth however the cost of fossil energy is quite high for Thai farmers. Since Thailand has great solar potential, especially northeastern region, renewable energy sources of sunlight in this region should be considered to be another energy source for Thai agriculture. To assess and classify the potential of the investment in agricultural solar power systems of 20 provinces in Thailand's northeastern region, this study applied the combining method of Entropy Weight Method and TOPSIS with secondary data of solar irradiance, farmer household density, and income of farmer households. With this combining method, the results showed that farmer household density and income of farmer household were more influence on assessing and classifying the potential of this investment than solar irradiance. Finally, all 20 provinces were classified into four groups of Group A (A<inf>12</inf>, A<inf>2</inf>, A<inf>4</inf>, A<inf>1</inf>, and A<inf>10</inf>), Group B (A<inf>8</inf>, A<inf>9</inf>, A<inf>19</inf>, A<inf>3</inf>, and A<inf>15</inf>)), Group C (A<inf>17</inf>, A<inf>13</inf>, A<inf>18</inf> A<inf>16</inf>, and A<inf>20</inf>) and Group D (A<inf>6</inf>, A<inf>11</inf>, A<inf>7</inf>, A<inf>14</inf>, and A<inf>5</inf>) from the most potential province group for investment in agriculture solar power system to the least potential province group for investment in agriculture solar power system.
  • Some of the metrics are blocked by your 
    Item type:Item,
    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
    (2023-10-01)
    Klongboonjit, Sakon
    ;
    Kiatcharoenpol, Tossapol
    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<inf>i</inf>) for each of the 18 sub-districts. P<inf>i</inf> 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<inf>i</inf> values, with the implication that sub-districts exhibiting higher P<inf>i</inf> 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<inf>i</inf> values.