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In recent years, it has been aimed to increase diversity of energy having a positive relationship with environment and minimize damage to environment and use water potential of country more effectively. Therefore, hydroelectric energy plants have become the most important sources used for energy production. In these energy plants, issues such as the amount of water used for energy and net drop, and pre-determination of energy output are very important in terms of energy planning. Moreover, approximate estimation of energy value to be generated in future by using estimation models is also very important for energy planning. Therefore, in this study is to estimate prospective energy which will be generated in two hydroelectric energy plants in Sakarya Basin of Turkey (Adasu Regulator and Hydroelectric Energy Plant and Pamukova Hydroelectric Energy Plant) in short and long term. Artificial Neural Networks Method was used to make short-term estimation analyzes and Innovative Sen Method, one of trend analysis methods was used to make long-term estimation analyzes. Data to be used in study (Daily Generated Energy, Daily Average Net Drop, and Daily Average Flow) were obtained from Hydroelectric Energy Plant Operation Directorate. As a result of study, value of energy to be generated by 2030 with Artificial Neural Networks model formed by these data was prediction with numerical data. In addition, long-term estimations were made with Innovative Sen Method, which is one of Trend Analysis Methods.

Short- and long-term prediction of energy to be produced in hydroelectric energy plants of Sakarya Basin in Turkey