<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>In order to meet the growing agricultural demands, modern machinery needs to be deployed and cheaper energy supply needs to be ensured. With advancements in artificial intelligence, fruit harvesting robots can improve both the quality and productivity of fruit picking and increase orange fruit exports. However, to ensure effective working of the fruit harvesting robot, an energy source that is both efficient and cost-effective is necessary. This paper aims at designing of a solar energy system for a lightweight fruit harvesting robot for orange orchards in Pakistan and conducting a feasibility study for the deployment of the robot for remote agricultural land. The site for fruit harvesting robot employment is decided by irradiance using random forest regression. Solar system sizing is done based on the design and energy requirements of the fruit harvesting robot. The Homer Pro software is used for simulation of the system to analyse the potential of using solar system for fruit harvesting robot in Sargodha, Pakistan. The results show that compared to hybrid system, a stand-alone system is a more cost effective, reliable, and efficient option with a payback time of 3.36 years and levelized cost of energy being $0.085 per unit kWh. This study proves that solar energy is a viable and cheaper solution for using modern agricultural machineries, like fruit harvesting robot, in remote areas in developing countries, like Pakistan, to enhance productivity and improving quality of the produce.</p>
</abstract>

In order to meet the growing agricultural demands, modern machinery needs to be deployed and cheaper energy supply needs to be ensured. With advancements in artificial intelligence, fruit harvesting robots can improve both the quality and productivity of fruit picking and increase orange fruit exports. However, to ensure effective working of the fruit harvesting robot, an energy source that is both efficient and cost-effective is necessary. This paper aims at designing of a solar energy system for a lightweight fruit harvesting robot for orange orchards in Pakistan and conducting a feasibility study for the deployment of the robot for remote agricultural land. The site for fruit harvesting robot employment is decided by irradiance using random forest regression. Solar system sizing is done based on the design and energy requirements of the fruit harvesting robot. The Homer Pro software is used for simulation of the system to analyse the potential of using solar system for fruit harvesting robot in Sargodha, Pakistan. The results show that compared to hybrid system, a stand-alone system is a more cost effective, reliable, and efficient option with a payback time of 3.36 years and levelized cost of energy being $0.085 per unit kWh. This study proves that solar energy is a viable and cheaper solution for using modern agricultural machineries, like fruit harvesting robot, in remote areas in developing countries, like Pakistan, to enhance productivity and improving quality of the produce.

Design and Analysis of a Solar Energy System for a Fruit Harvesting Robot in Pakistan

Acta Technologica Agriculturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

In order to meet the growing agricultural demands, modern machinery needs to be deployed and cheaper energy supply needs to be ensured. With advancements in...

Design and Analysis of a Solar Energy System for a Fruit Harvesting Robot in Pakistan

Data publikacji: 14 lis 2023

Zakres stron: 185 - 193

DOI: https://doi.org/10.2478/ata-2023-0025

Słowa kluczowe
orange harvesting, random forest regression, Homer Pro, solar potential, fruit harvesting robot

© 2023 Sadaf Zeeshan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Design and Analysis of a Solar Energy System for a Fruit Harvesting Robot in Pakistan

Data publikacji: 14 lis 2023

Zakres stron: 185 - 193

DOI: https://doi.org/10.2478/ata-2023-0025

Słowa kluczoweorange harvesting, random forest regression, Homer Pro, solar potential, fruit harvesting robot

© 2023 Sadaf Zeeshan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
orange harvesting, random forest regression, Homer Pro, solar potential, fruit harvesting robot