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  4. Establishment of a framework for the design of robotic photovoltaic cleaning systems
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Establishment of a framework for the design of robotic photovoltaic cleaning systems

Date Issued
November 6, 2022
Author(s)
Christoforou, Eftychios G.  
Avgousti, Sotiris  
Kalogirou, Soteris A.  
Mavros, Michals  
Abstract
Given the prominent role of solar energy among the other clean energy sources, the increase of
photovoltaic (PV) systems efficiency becomes crucial. A problem that was recognized to degrade
the performance of photovoltaic panels is related to the accumulation of dust (soiling) on their
surface. In general, the common practice of manual cleaning of PV systems is not efficient. For
this reason, it has emerged the need for automatic cleaning procedures. Automated solutions
include integrated cleaning systems and robotized solutions.
From a robot design perspective there exist a plethora of issues to be considered, including its
energy autonomy but also the employment of appropriate path planning and control
methodologies. The available cleaning methods have to be assessed in regard to their suitability
for a robotized solution and the corresponding operation parameters have to be optimized.
A monitoring system can assist in targeted cleaning beyond the scheduled routine cleaning
operations. Towards that direction a suitable concept may integrate intelligent monitoring of a
solar photovoltaic power plant using autonomous drones. An effective robotic cleaning solution
can be further enhanced using other modern technologies including advanced image processing,
artificial intelligence (AI), machine learning and internet of things (IoT).
The objective of this work is to provide a general perspective of the problem. The motivation for
the development of robotized PV cleaning solutions is justified and the application requirements
are identified. A general framework for the design of PV cleaning robots is established. Relevant
works are reviewed, already proposed systems are categorized and research challenges are
identified.
Subjects

Solar energy

Photovoltaic

Robotic systems

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Avgousti.pdf

Size

98.71 KB

Format

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Checksum (MD5)

44b83cadc3e1946004738d1bde03f7cf

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