Search

In this study, some of the commonly used daily global solar radiation decomposition models are improved by considering ambient temperature, relative humidity, and air pressure to estimate hourly global solar irradiance from measured daily global solar radiation in Eskişehir, Turkey. Accordingly, the identified functions of the considered parameters are integrated into the selected daily global solar radiation decomposition models. The accuracy of the improved models is evaluated based on the measured monthly average hourly global solar irradiance values. In addition, the monthly average power values provided by the original and improved models are compared with the measured power output values. The results indicate that the improved models have significantly higher performance in the accuracy of both global solar radiation estimation and power output forecasting in a specific time interval. Therefore, the proposed methodology can be used to improve any global solar radiation decomposition model based on locally measured data for different regions. [ABSTRACT FROM AUTHOR]

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, unit commitment problem which is an important subject in power system optimization, is solved by using dynamic programming, Lagrange relaxation, and simulated annealing methods. Dynamic programming method evaluates possible unit commitment schedules associated with decision made in the proceeding step by considering all constraints before searching for a schedule that yields the minimum cost. Lagrangian relaxation method, which is based on mathematical optimization, presents a solution for unit commitment problem. Simulated annealing is a method which refers to the process of heating up a solid to a high temperature followed by slow cooling achieved by decreasing the temperature of the environment in steps and gives feasible solutions for optimization problems. In the simulations made by using MATLAB®, the operation conditions and total costs of the units are found by using three different solving methods. The solutions are given in the tables and methods used are compared. Four-unit in Tuncbilek thermal plant which is in Kutahya region, Turkey, are used as an example for the unit commitment problem. The data used in this paper is taken from (TEPC) Turkish Electric Power Company and (EGC) Electricity Generation Company. [ABSTRACT FROM AUTHOR]