Data Supported Decision-Making for Renewable Energy Solutions

Cay D., Karabece K., GÜRBÜZ T.

World Congress on Engineering and Computer Science, San-Francisco, Costa Rica, 21 - 23 October 2015, pp.477-482 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • City: San-Francisco
  • Country: Costa Rica
  • Page Numbers: pp.477-482


This study describes how data science can be used in decision-making for renewable energy production. You will attain an example for how climatic datasets can be used in decision process of renewable energy investments. Under the light of three decision criteria, "metrics", which will be used to measure efficiency of alternative solutions, are specified. Datasets from satellite records are used for generating scores of the metrics. TOPSIS, ADP, Engineering Economics, Six Sigma Quality Control methods and applications are used during consideration of datasets. Final decisions are diversified by weights considering various political points of views for optimum decision.