مهدی احسانیان

Power decoupling of pulsating grid side power from constant source side power is one of the paramount issues in single phase-phase grid-connected renewable systems. The principal aim of such systems is the decrease of the capacitance of the decoupled capacitor. However, this causes some problems such as an increase in the total harmonic distortion (THD) of injected current to the grid and bus voltage fluctuations. By considering the aforementioned explanation, utilizing control strategies is critical to modify system performance. The voltage controller is responsible for adjusting the bus voltage, suppressing the second-order harmonic, and providing a trade-off between system cost and total harmonic distortion as well as bus voltage fluctuations. This paper presents a digital notch filter in order to improve the system transient response and remove the harmonic ripples. The relations between system cost, THD, and bus voltage fluctuations have been described completely. Moreover, the mathematical expressions of the proposed digital notch filter have been provided. The analyzed system is 250 W PV panel connected to a 220 V RMS, 50 HZ grid. The THD of injected current to the grid is approximately 0.6%.

Phase, frequency, and amplitude of grid voltage are important information in grid-connected photovoltaic systems. For proper and stable operation of a system, a fast and correct estimation of grid information under grid variations and disturbances is very crucial. In this paper, an adaptive phase-locked loop (PLL) structure is proposed which tracks the phase jumps of grid voltage fast and smoothly. If a jump occurs in grid voltage phase transient state at the frequency estimation of frequency lock loop (FLL) will be almost zero. The settling times of the estimated phase, frequency, and amplitude of the proposed PLL are also slightly low. The proposed PLL consists of the second-order generalized integrator (SOGI) and frequency locked loop (FLL). The whole system has been simulated in MATLAB/Simulink. The settling time of estimated frequency and amplitude for proposed PLL are 0.023 and 0.024 s, respectively.

The robust carrier tracking is defined as the ability of a receiver to determine the phase and frequency of the input carrier signal in unusual conditions such as signal loss, input signal fading, high receiver dynamic, or other destructive effects of propagation. An implementation of tight tracking can be understood in terms of adopting a very narrow loop bandwidth that contradict with the requirements for tracking high user dynamics. Such a trade-off becomes the critical point and the main limitation of robust carrier tracking, since both noise rejection (and equivalently, recovery of the lost signal power) and agile carrier tracking must be appropriately balanced to avoid penalizing the performance criteria of the specific application under analysis. In practice, bandwidth must be adaptive so that with respect to input noise and dynamic values, optimal bandwidth could be chosen. In this article, first different carrier tracking systems is reviewed and their related features and applications are studied and determined. Then, with comparing existing methods it is shown that, the proposed intelligent type-2 neuro-fuzzy controllers in tracking system provide results that are more acceptable than others because of overcoming the uncertainties in the received carrier signal and environmental conditions.

In this paper we address the problem of automatic arrangement of cameras in a 3D system to enhance the performance of depth acquisition procedure. Lacking ground truth or a priori information, a measure of uncertainty is required to assess the quality of reconstruction. The mathematical model of iso-disparity surfaces provides an efficient way to estimate the depth estimation uncertainty which is believed to be related to the baseline length, focal length, panning angle and the pixel resolution in a stereo vision system. Accordingly, we first present analytical relations for fast estimation of the embedded uncertainty in depth acquisition and then these relations, along with the 3D sampling arrangement are employed to define a cost function. The optimal camera arrangement will be determined by minimizing the cost function with respect to the system parameters and the required constraints. Finally, the proposed algorithm is implemented on some 3D models. The simulation results demonstrate significant improvement (up to 35%) in depth uncertainty in the achieved depth maps compared with the traditional rectified camera setup.