Design of Optimal Strategy for Managing Decentralized Solar PV Systems Considering Uncertain Weather Conditions

Abstract

Solar power is a promising source of energy that is environmentally friendly, sustainable, and renewable. One of the most common ways to harness solar energy is through the use of photovoltaic (PV) panels. Unfortunately, these panels are prone to the accumulation of dust, which can have a significant impact on their efficiency. To maintain the panels' effectiveness, regular cleaning is necessary. This study aimed to identify the best cleaning method for PV panels using multiple criteria decision-making (MCDM) techniques. This thesis evaluated eight cleaning methods based on several criteria of which are cost, performance, resource requirement and safety. The results revealed the three most effective cleaning methods for cleaning PV panels are natural cleaning, manual cleaning, and surface coatings. Natural cleaning involves the use of rainwater to remove dirt and dust, while manual cleaning requires the use of cleaning agents and a wiping cloth. Surface coatings involve applying a layer of hydrophobic material to the panels to repel dust. Although the study provides valuable insights into the best cleaning methods for PV panels, the findings are limited by the small number of experts involved in the evaluation. Therefore, future studies with a larger number of experts are recommended to better evaluate the effectiveness of these cleaning methods. Ultimately, identifying the most effective cleaning methods for PV panels can ensure optimal efficiency recovery at the least costs and resources.

Date of Award	Aug 2023
Original language	American English
Supervisor	Ahmad Mayyas (Supervisor)