Unlicensed renewable energy investment validation and decision support proposal via comparative data mining methods within the cities energy requirements of Turkey

Today it is nearly impossible to think a life without Energy. As widely acknowledged, production and consumption of the energy together is one of the most reliable indicators of the development and quality of life reached by a country so, for the sake of country the necessity of satisfying a forecasted energy demand, over a certain time period, is the basis of energy invesment decisions. These decisions have also direct and side effects on many other related areas like climate change, air pollution, social and cultural requirements, geographical and regional conditions and political decisions etc. As seen, this is a multi-discipline challenge and can be carried out by taking into account the historical data collected in the previous energy plans of the country, proactive approach, foreseen motivation and better usage of lesson learned analyzes. In this perspective, our study focuses on this challenge to safe increased future energy demand by analyzing renewable energy resources via using modern veri mining algorithms (K-Means, Self Organizing Maps ve Fuzzy C Means) with two different tools (MATLAB and Rapid Miner). The results of the study as developed model for supporting the decisions of creating new sister learned/teached cities are highly useful not only for decision makers but also for all energy-related stake holders from investors to any researchers in the wide cover.