Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation
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 stu...
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2025-01-01
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| author | Batuhan Tural Onur Akar |
| author_facet | Batuhan Tural Onur Akar |
| author_sort | Batuhan Tural |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-21815b56d93c429daed31b68a3501b02 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-21815b56d93c429daed31b68a3501b022025-08-20T02:37:40ZengIEEEIEEE Access2169-35362025-01-0113894638948010.1109/ACCESS.2025.357187511007644Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation EstimationBatuhan Tural0https://orcid.org/0009-0002-1282-0500Onur Akar1https://orcid.org/0000-0001-9695-886XInstitute of Pure and Applied Sciences, Department of Electrical and Electronics, Marmara University, Istanbul, TürkiyeDepartment of Electronics and Automation, Marmara University, Istanbul, TürkiyeThe 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.https://ieeexplore.ieee.org/document/11007644/Artificial intelligencemarine vesselsPV simulation toolsPV systemsrenewable energy |
| spellingShingle | Batuhan Tural Onur Akar Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation IEEE Access Artificial intelligence marine vessels PV simulation tools PV systems renewable energy |
| title | Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation |
| title_full | Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation |
| title_fullStr | Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation |
| title_full_unstemmed | Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation |
| title_short | Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation |
| title_sort | design and economic analysis of marine vessel pv power system based on solar radiation estimation |
| topic | Artificial intelligence marine vessels PV simulation tools PV systems renewable energy |
| url | https://ieeexplore.ieee.org/document/11007644/ |
| work_keys_str_mv | AT batuhantural designandeconomicanalysisofmarinevesselpvpowersystembasedonsolarradiationestimation AT onurakar designandeconomicanalysisofmarinevesselpvpowersystembasedonsolarradiationestimation |