Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation

Tural B., Akar O.

IEEE ACCESS, cilt.13, ss.89463-89480, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1109/access.2025.3571875
  • Dergi Adı: IEEE ACCESS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Sayfa Sayıları: ss.89463-89480
  • Anahtar Kelimeler: Solar energy, Solar radiation, Photovoltaic systems, Marine vehicles, Renewable energy sources, Production, Power generation, Electricity, Artificial intelligence, Artificial neural networks, marine vessels, PV simulation tools, PV systems, renewable energy
  • Marmara Üniversitesi Adresli: Evet

Özet

The need for clean energy has accelerated energy production by using Renewable Energy Sources (RES) in marine vessels. With the developments in solar energy technology, the use of various simulation programs to analyze the performance predicted of Photovoltaic (PV) systems is increasing. In this study, 12 month solar radiation data belonging to 12 different points in a specific region of the Marmara Sea were used for prediction. The Artificial Neural Network (ANN) model was trained by dividing it into training, validation and test data sets at a ratio of 70-15-15 and the performance of the model was obtained with average Mean Squared Error 0.00098 and Regression 0.99997. The predicted values were used in PV power system modeling for a marine vessel and the system performance was analyzed with HOMER, SAM, RETScreen, PVSOL, PVsyst, PVWatts and PVGIS simulation programs. 16.8 kW capacity PV power system was created for the optimum design. When the results are examined, it is seen that the maximum production is obtained from HOMER with 23193 kW, but it is the most expensive in terms of cost, and it is determined that an average of 20771 kW of energy is produced throughout the year from the simulation programs, an annual decrease of 45.01 kg in SO2 emissions and 18166 kg in CO2 emissions is achieved. In addition, a decrease of 0.2542 USD is observed in energy costs. This study contributes to the literature in optimizing the use of RES in moving platforms and comparing the programs.