Prediction of Solar Energy Potential with Artificial Neural Networks

GÖKSU B., Bayraktar M., PAMIK M.

7th Global Conference on Global Warming (GCGW), İzmir, Turkey, 24 - 28 June 2018, pp.247-258 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1007/978-3-030-20637-6_13
  • City: İzmir
  • Country: Turkey
  • Page Numbers: pp.247-258
  • Keywords: Neural networks, Emissions, Energy saving, Solar energy, RADIATION, TEMPERATURE, HUMIDITY
  • Dokuz Eylül University Affiliated: Yes


The energy requirements have been met from fossil fuels since the early 1800s. Considering the environmental awareness and limited fossil resources, using renewable energy resources are compulsory to meet the increasing energy demand. Solar and wind energy, biofuels, and natural gas are leading ones. Solar energy is an effective and clean energy source compared in terms of sustainability, reliability, and economy. In the maritime sector, eco-friendly and sustainable qualities are sought in all of the efforts to reduce costs. Therefore, in many maritime fields, solar energy is used as an alternative energy source. The purpose of this study is achieving maximum efficiency from solar panels by using optimization technique. The energy estimation was performed by artificial neural networks method on solar panels based on weather changes in Izmir Gulf. The results are compared with the "Renewable Energy General Administration" data of Turkey. As a result, the obtained data will be informative to the researcher who will study solar energy's maritime applications. Besides, this study will be a possible source to make comparisons with similar solar energy studies.