Akademik Veri Yönetim Sistemi
Ay İ., Karabulut Ş., Kademli M.
Erasmus Projesi, 2020 - 2022
The aim of our project is to develop solar energy systems repair and maintenance curriculum for the electrical and electronics and energy systems departments of vocational and
technical education schools, to predict and prevent solar energy systems (SES) failures with artificial intelligence methods.
The most important energy source in the world is the sun. Radiation energy of the sun is the main energy source affecting the physical formations in the earth and atmosphere system.
Material and energy flow in the world is possible thanks to solar energy. With the latest energy production and consumption methods, our energy resources, which cannot be replaced,
are consumed, as a result of which irreversible damage is caused by nature and environmental pollution is created. Renewable energy sources, including solar energy, contain these
opportunities and are the only energy sources waiting to be developed. Solar energy has an opportunity to become more widespread compared to other renewable energy sources
with its potential and ease of use. The potential is already available in Turkey and with the solar generation should be used effectively and sufficiently widely (Varınca and Gönüllü,
2006). According to the Solar Energy Potential Atlas (SEPA) of our country, the total annual sunbathing time is 2737 hours. It is possible to use solar energy efficiently in almost every
region of our country. Today, the use of solar water heating systems in buildings in Turkey and often are used as support in case of need to meet the heating needs. In recent years,
solar energy systems that provide heating support have become more common (Kılıç, 2015).
According to the International Energy Agency (IEA), the sunlight that hits the earth in 90 minutes is enough to meet the world's annual energy needs. IEA predicts that 11% of global
electricity generation will be provided by solar energy in 2050, and by 2030, it reports that renewable energy sources will be the fastest-growing energy sources with an annual growth
rate of 7.6% (Kılıç, 2015). Many countries in the world increase their investments in SES and also train qualified personnel for the sustainability of this energy. Along with its growth
potential, the need for maintenance and repair of these systems and the need for technical personnel also increases. The need for technicians in our country is mostly met with
students who graduate from vocational high schools affiliated with the Ministry of National Education. Industrial maintenance and repair technicians, electrical installations and panel
assembly technicians are graduated from fields such as electric-electronic technology field and renewable energy technologies field within the vocational high schools. The need to
train technical staff needed for SES, which has become widespread with changing and developing technologies, has also increased. Although maintenance and repair of these
systems are important, predictive maintenance is vital for these systems. Thus, the system can be healthy for a long time by predicting possible system errors and prevent them before
they occurred. The uninterrupted operation of SES and continuous energy production are very important both by the enterprises and the users. Predictive maintenance applications have become possible thanks to artificial intelligence algorithms and machine learning applications developing today.
The simultaneous transfer of technological innovations to education and training environments directly affects the education levels and development levels of the countries. Since the
2000s, significant developments have occurred in the field of Artificial Intelligence and it has started to be mentioned with many disciplines. Within the scope of the project, to train
qualified trainers for predictive breakdown maintenance of SES, to integrate SES and Artificial Intelligence discipline and to produce solutions for current practices and to reach the
purpose of the project;
• The research will be conducted on Solar Energy Systems and a report will be prepared on the potential, as well as on breakdown, maintenance and repair costs.
• SES repair and maintenance module will be prepared for use in vocational and technical education.
• Software infrastructure will be prepared for failure prediction and preventive maintenance.