Yazar "Alparslan, N.C." seçeneğine göre listele

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    Comparison of real and mathematical model data of pv systems to monitor the performance with fuzzy logic
    (Institute of Electrical and Electronics Engineers Inc., 2019) Alparslan, N.C.; Kayabaşı, Ahmet; Rüşen, Selmin Ener
    Today, photovoltaic (PV) systems are widely used to produce electricity from the sun, which has the greatest potential among renewable energy sources. However, the mathematical correct modeling is very important to develop, plan and use under optimal conditions of green, long-lasting, high-efficiency and low-cost PV systems, which are alternatives to traditional energy generation methods. This project is based on the development of an autonomous system for the creation of a mathematical model of the electrical equivalent circuit of the prototype PV module and the instantaneously monitoring of the performance of this PV module. To test the mathematical model created in this project, the power values were obtained and compared for the reference PV module under laboratory conditions and the accuracy of the created model was tested. In this project, the warning mechanism has been developed in case of any problems with performance monitoring of the prototype PV module system installed by using fuzzy logic. The project aims to ensure that PV systems work in a long time with high efficiency and thus support our country's energy requirement. © 2019 IEEE.
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    Estimation of global solar radiation by using ANN and ANFIS
    (Institute of Electrical and Electronics Engineers Inc., 2019) Alparslan, N.C.; Kayabaşı, Ahmet; Rüşen, Selmin Ener
    Solar energy has the greatest potential among the energy sources available in the world and it is clean and universal energy source. The first parameter that should be determined carefully when planning systems based on solar energy is the solar radiation value. The solar radiation values obtained from ground observations can be estimated with various software models. Especially, estimation models designed using emerging computer technology have ease of use and accuracy. In this study, the well-known artificial intelligence techniques such as artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used to estimate solar radiation. The analysis of solar radiation requires complex, lengthy and time consuming procedures and artificial intelligence techniques such as ANN and ANFIS eliminate great effort and time. A system that measures atmospheric data such as light, temperature and humidity using sensors is designed and for this study, measurements were made for over a month. The atmospheric data obtained from the climatic conditions of the province of Karaman and the surface solar radiation values measured using the Pyranometer are utilized to construct these models. As a result of testing the constructed models, the ANFIS model is found to be more successful than ANN. © 2019 IEEE.