| dc.description.abstract | Human activities emit a considerable quantity of greenhouse gases, intensifying the greenhouse effect and causing the global average temperature to increase further. The numerous effects of global warming have drastically altered the living environment. Countries throughout the world have proposed a variety of remedies to keep the global average temperature from rising further, and the use of renewable energy to replace fossil fuels can significantly decrease greenhouse gas emissions. As a result, countries all around the world have widely installed solar panels. Many elements will influence the power generation efficiency of solar panels, with the environment being one of the most important. Because dirt in the surroundings, such as dust or animal dung, casts shadows on solar panels, cleaning solar panels is critical. Traditionally, solar panels are cleaned by manpower, but the installation area of solar panels is a roof or a large-scale solar power plant. Using manpower to clean is not only time-consuming, but also may cause accidents. If a solar panel cleaning robot is used and transported with a drone, accidents can be avoided, and decentralized solar panel cleaning needs can also be met.
Because there are a number of solar panel cleaning robots on the market, differences in performance such as cleaning speed, power consumption, and appropriate maximum tilt angle will impact the overall time necessary to finish solar panel cleaning. Therefore, the purpose of this research is to choose a proper solar panel cleaning robot configuration that minimizes overall completion time while achieving all cleaning requirements. In this study, five solar panel cleaning robots with different performances were considered and analyzed using randomly generated solar panel data. In the solar panel cleaning robot configuration problem, in order to meet the actual application situation, it is assumed that each area only uses one solar panel cleaning robot, and the genetic algorithm is used for optimization. The configuration of the solar panel cleaning robot is represented by the chromosome, and the solar panel cleaning robot under the same number is dispatched according to the information of the chromosome. Through computer experiments, it is known that the genetic algorithm can handle the performance differences of solar panel cleaning robots, the size of the area and the angle of inclination, and other constraints and variables. This will help improve the efficiency of cleaning operations, reducing the time and labor costs required for cleaning. | en_US |