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Öğe ADAPTIVE ENERGY MANAGEMENT FOR THE SMART HOME(ST JOHN PATRICK PUBL, 2017) Bakir, Hale; Kulaksiz, Ahmet Afsin[Abstract not Available]Öğe ANFIS-based estimation of PV module equivalent parameters: application to a stand-alone PV system with MPPT controller(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, 2013) Kulaksiz, Ahmet AfsinThe performance and system cost of photovoltaic (PV) systems can be improved by employing high-efficiency power conditioners with maximum power point tracking (MPPT) methods. Fast implementation and accurate operation of MPPT controllers can be realized by modeling the characteristics of PV modules, obtaining equivalent parameters. In this study, adaptive neuro-fuzzy inference systems (ANFISs) have been used to obtain 3 of the parameters in a single-diode model of PV cells, namely series resistance, shunt resistance, and diode ideality factor. The input parameters of ANFISs are a material-type of PV modules, short circuit current, open circuit voltage, and unit area under the I-V curve of the PV module. The advantage of the proposed method is that the equivalent parameters can be obtained for a wide range of PV modules of different types (monocrystalline, multicrystalline, and thin-film) using easily obtainable electrical parameters. To demonstrate the accuracy of the proposed model, MPPT control is implemented in a PV system with a battery charge application for 3 different types of PV modules. The obtained results suggest that the ANFIS model appears to be a useful tool for estimating the equivalent parameters of PV modules.Öğe A genetic algorithm optimized ANN-based MPPT algorithm for a stand-alone PV system with induction motor drive(PERGAMON-ELSEVIER SCIENCE LTD, 2012) Kulaksiz, Ahmet Afsin; Akkaya, RamazanArtificial neural network (ANN) based maximum power point tracking (MPPT) algorithm makes use of the advantages of ANNs such as noise rejection capability and not requiring any prior knowledge of the physical parameters relating to PV system. This paper proposes a genetic algorithm (GA) optimized ANN-based MPPT algorithm implemented in a stand-alone PV system with direct-coupled induction motor drive. The major objective of this design is to eliminate dc-dc, converter and its accompanying losses. Implementing offline ANN in DSP needs optimization of ANN structure to obtain an ideal size. GA optimization was used in this study to determine neuron numbers in multi-layer perceptron neural network. Another objective of this work is to prevent the necessity of the trade-off between the tracking speed and the oscillations around the maximum power point. Hence, varying step size is used in MPPT algorithm and PI-controller is adopted for simple implementation. Simulation and experimental results have been used to demonstrate effectiveness of the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.Öğe Performance investigation of a new solar desalination unit based on sequential flat plate and parabolic dish collector(TAYLOR & FRANCIS INC, 2017) Argun, Mehmet Emin; Kulaksiz, Ahmet AfsinA new systemcomposed of a sequential flat plate and parabolic dish solar collector was applied to enhance the solar desalination productivity. Heated saline water was desalinated using the evaporation/condensation principle and an effort was made to achieve higher distillate production compared to previous studies. Desalination efficiency values were calculated between 23% and 57%. Maximum desalinated water productions were obtained as 1,038mL/m(2). h in autumn and 1,402 mL/m(2). h in summer. The cost of solar desalination system was found as economically feasible with 3 years' payback period and the producedwater cost of 0.014 $/L. Physicochemical analyses revealed that as a result of the desalination process, salinity level decreased from 35.6% to 0.0-0.1%, chloride concentration decreased from 21,407 mg/L to 10 mg/L, and electrical conductivity decreased from 53.1 mS/cm to 0.11 mS/cm.Öğe Stability analysis of sensorless speed control of IPMSM(WILEY, 2017) Altaey, Abdulhasan; Kulaksiz, Ahmet AfsinIn the speed control of an interior permanent magnet synchronous motor (IPMSM), for stability reasons, the closed-loop pole positions should be on the left-hand side of the S-plane, and for fast response requirements these poles should have a small time constant. Unfortunately, the motor poles have a very long time constant, which makes the system response very slow. To solve this problem, the zeros of PI controllers are used to compensate the motor poles. As the motor operates, the temperature increases, which changes the parameters of the motor and, accordingly, the motor poles change their position so the PI controller cannot compensate these poles. To solve this problem, many parameter estimation algorithms have been used to detect new parameter values and adapt the PI controller gains so that to compensate the motor poles continually. These parameter estimation algorithms complicate and add cost to the system. This paper demonstrates that, for a temperature up to 70 degrees C, the system is capable of giving fast response and stable operation by using a good design of the PI controller regardless of the parameter changes. (C) 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
