Adnan Ibrahim

Outdoor Performance Evaluation of Building Integrated Photovoltaic Thermal (BIPVT) Solar Collector with Spiral Flow Absorber Configurations

Received May 21, 2018 Revised Aug 30, 2018 Accepted Sep 13, 2018 This paper presents a novel Stator Current based Model Reference Adaptive System (SC_MRAS) speed observer for high-performance Six Phases Induction Motor (SPIM) drives using linear neural network. The article aim is intended to improve performance of an SC_MRAS observer, which were presented in the literature. In this proposed scheme, the measured stator current components are used as the reference model of the MRAS observer to avoid the use of a pure integrator and reduce the influence of motor parameter variation. The adaptive model uses a two-layer Neural Network (NN) to estimate the stator current, which has been trained online by means of a Least Squares (LS) algorithm instead of uses a nonlinear Back Propagation Network (BPN) algorithm to reduce the complexity and computational burden, it also help to improve some disadvantages cause by the inherent nonlinearity of the BPN algorithm as local minima, two heuristically chosen parameters, initialization, and convergence problems, paralysis of the neural network. The adaptive model of the proposed scheme is employed in prediction mode, not in simulation mode as is usually the case in the literature, this made the proposed observer operate better accuracy and stability. In the proposed observer, stator and rotor resistance values are estimated online, these values thereafter were updated for the current observer and rotor flux identifier to enhance the accuracy, robustness and insensitivity to parameters variation for the proposed observer. The proposed LS SC_MRAS observer has been verified thought the simulation and compared with the BPN MRAS observer. The simulation results have proven that the speed is estimated a consequent quicker convergence, do not need the estimated speed filter, lower estimation errors both in transient and steady state operation, better behavior in low and zero speed operation. Keyword:Received Jun 7, 2018 Revised Jul 8, 2018 Accepted Sep 13, 2018 Experiments confirmed that Transformerless Inverters (TIs) deliver more reliability and higher energy efficiency. Nonetheless, one of the shortcomings of TIs is the leakage current that occurs between the photovoltaic (PV) string terminals and the ground. Such a drawback is justified by the non-galvanic isolation caused by the transformer being omitted. As such, this study is intended to develop a novel TI inverter topology for solar PV systems. The latter is meant to remove the leakage current and enhance the operating system of the entire PV conversion as well. Added to its null zero-crossing distortion and capability regarding energy efficiency, the developed TI, being validated by simulation and experiment, eradicated the leakage current. Keyword:Now a day’s renewable energy sources became an interesting area of research of which fuel cells are emerged as an alternative source for producing electricity to meet the energy crisis. This led to a research on power conditioning systems through which fuel cell is interfaced to the utility. Of the different converter topologies Isolated full bridge boost converter (IFBC) topology is most suitable for fuel cell applications. In this paper a Predictive Switching Modulator (PSM) Control is proposed for the converter topology and its performance is compared with Linear Peak Current Mode control (LPCM), Non-Linear Carrier Control (NLC).Received May 2, 2018 Revised Aug 23, 2018 Accepted Sep 14, 2018 Recently of the main topic of research is the sensorless vector control of induction motor drive, In this paper presents the predictive model reference adaptive system (PMRAS) rotor speed observer, This observer developed from the classical MRAS rotor flux scheme associated with predictive adaptation mechanism designed from the Finite Control Set Model Predictive Control (FCS–MPC) by using a search optimization algorithm for calculate the rotor position which guarantee a minimum speed tuning error signal at each sampling period. The effectiveness of the proposed observer proved with the simulation results, show high dynamic performance speed and position observed in sensorless vector control process at low and zero speed as well robustness against motor parameter variation with different loading conditions. Keyword: