Prajna Paramita Dash

Dynamic Modeling and Performance Analysis of a Grid-Connected Current-Source Inverter-Based Photovoltaic System

Voltage-source inverter (VSI) topology is widely used for grid interfacing of distributed generation (DG) systems. However, when employed as the power conditioning unit in photovoltaic (PV) systems, VSI normally requires another power electronic converter stage to step up the voltage, thus adding to the cost and complexity of the system. To make the proliferation of grid-connected PV systems a successful business option, the cost, performance, and life expectancy of the power electronic interface need to be improved. The current-source inverter (CSI) offers advantages over VSI in terms of inherent boosting and short-circuit protection capabilities, direct output current controllability, and ac-side simpler filter structure. Research on CSI-based DG is still in its infancy. This paper focuses on modeling, control, and steady-state and transient performances of a PV system based on CSI. It also performs a comparative performance evaluation of VSI-based and CSI-based PV systems under transient and fault conditions. Analytical expectations are verified using simulations in the Power System Computer Aided Design/Electromagnetic Transient Including DC (PSCAD/EMTDC) environment, based on a detailed system model.

Harmonic elimination in a multilevel Current-Source Inverter-based grid-connected photovoltaic system

Multilevel inverters have received considerable attention for their capability to realize high power ratings and high-quality waveforms, at low switch stress and losses. Multilevel inverter based on Voltage-Source Inverter (VSI) topology is more thoroughly researched when compared to Current-Source Inverter (CSI)-based multilevel inverter. In this paper, a multilevel structure based on CSI topology is presented. Each inverter unit in the multilevel structure is equipped with its own Maximum Power Point Tracker (MPPT) and DC-side current controller. On the AC-side, a combined dq-frame current controller is adopted. Operation of the multilevel structure is investigated under equal and unequal irradiation level conditions. From the simulation results, it is observed that, when PV arrays of different inverters in the multilevel structure are exposed to unequal insolation levels, unequal step sizes are generated in the multilevel currents on the AC-side. This, in turn, leads to the generation of low-order harmonics in the current that is injected into the grid. A modified control structure is implemented to eliminate the low-order harmonics, which is verified through simulation in PSCAD/EMTDC environment.

A multilevel current-source inverter based grid-connected photovoltaic system

This paper proposes a grid-connected Photovoltaic (PV) system based on a multilevel Current Source Inverter (CSI) topology. The topology proposed here consists of parallel-connected CSI modules operating at a very low switching frequency. For n number of inverter modules, 2n+1 current levels are resulted in the output. In the multilevel inverter topology, each inverter module has its own PV source, Maximum Power Point Tracking (MPPT) unit, and DC-link current controller. Unlike earlier proposed multilevel CSI topologies, the proposed topology has a single AC-side current controllers, lowering the requirements for AC-side sensors and filters. To demonstrate the performance of the multilevel inverter based on CSI, two inverter units are considered in this study. The simulation studies are carried out in PSCAD/EMTDC environment.

Study of islanding behavior of a grid-connected photovoltaic system equipped with a feed-forward control scheme

One of the main issues related to the integration of Distributed Generation (DG) in the utility grid is safety. The protection schemes of distribution systems are usually designed under the assumption that power flows from distribution system to end users. If a fault takes place and a breaker opens, all circuits downstream will be deenergized. However, this is not the case when a DG is used, and it is possible that an Island with power generation and consumption is created, thus raising concerns with respect to equipment and personnel safety. During islanding, a portion of the utility system which contains both load and generation is isolated from the remainder of the system and continues to operate, a condition that is not desirable. Therefore, a DG interfaced with the utility system must be equipped with an anti-islanding scheme to ensure personnel safety and acceptable power quality. Performance of an anti-islanding scheme is usually evaluated by inspecting the corresponding Non Detection Zone (NDZ). It has been reported in past studies that DGs control scheme has an impact on the NDZ. This paper studies the impact of control structure on NDZ is studied in a grid-connected PV system equipped with a feed-forward control scheme.

An energy efficient real-time vehicle tracking system

Internet of Things (IoT) is a growing technology that combines and connects a variety of devices to generate more beneficial information. In this paper, an example of IoT portable system has been built and tested, which is called Smart Vehicle System (SVS). SVS includes three main parts: the Tracking Unit, Cloud, and Android application. The Tracking Unit is positioned inside a vehicle to sense the vehicles temperature, speed, and location then uploads them to the cloud via a GSM network. Components and communication of the SVS are described in detail. constraints are included in the system to notify the administrator and the driver of certain events. SVS is a portable system, whose operation depends on batteries; therefore, a power reduction algorithm is proposed and examined. We have performed 19 different experiments, before and after applying the proposed algorithm, four of them are dynamic and 15 are at a fixed location. With the power reduction algorithm, we are able to reduce the energy consumption of the tracking unit by up to 17%.

VeNICE: A very deep neural network approach to no-reference image assessment

Image Quality Assessment (IQA) remains a complex and challenging problem that has garnered great interest by the research community as well as industry. A majority of no-reference IQA metrics leverage handcrafted features which discriminates distortions from true image structures. Recently, deep neural networks (DNN) has been successfully applied on local image patches to estimate image quality, However, existing patch-based IQA approaches require manual patch selection processes as well as possesses high computational complexity. To mitigate such issues, this paper introduces a very-deep no-reference image condition evaluator (VeNICE), which leverages the power of deep learning using very deep neural networks to model the complex relationship between visual content and the perceived quality in a more global manner compared to existing patched-based methods. VeNICE leverages a very deep convolutional neural network architecture with intrinsic image decomposition capabilities, and is trained to learn to assess image quality based on training samples consisting of different distortions and degradation such as blur, Gaussian noise, and compression artifacts. Experimental results using the TID-2008 and LIVE r2 benchmark image quality datasets demonstrates that VeNICE was able to achieve strong quality prediction performance, being able to achieve similar performance as full-reference IQA methods.

Sensitivity analysis of a current-source inverter-based three-phase grid-connected photovoltaic system

In this paper, first, a novel accurate small-signal model of a three-phase current source inverter (CSI)-based grid-connected photovoltaic (PV) system is derived. The model takes into account the nonlinear characteristics of PV arrays, as well as the controller and grid-side dynamics. Then, the developed small-signal model is employed to investigate the impact of different parameters on the stability of the CSI-based PV system, through sensitivity analysis. The sensitivity to variations of different parameters is assessed by tracking the positions of real parts of the eigenvalues corresponding to the dominant state variables in the s-plane. Insolation level, controller gains, and grid inductance are the parameters considered to study the sensitivity of state variables.

Impact of maximum power point tracking on grid-connected Photovoltaic system dynamics

This paper studies the performance of a single-stage, three-phase Photovoltaic (PV) system that is connected to a distribution network. The control is based on an outer voltage control loop and an inner current regulation loop. A Maximum Power Point Tracker (MPPT) based on Perturb & Observe (P&O) method is interfaced to outer voltage control loop. The outer voltage control loop is based on feed-forward compensation strategy to make the PV system dynamics immune to the PV array nonlinear characteristics. Through simulation and mathematical analysis, it has been shown in previous research work that in the absence of feed-forward compensation change in the operating condition causes oscillation with weather condition unchanged. This paper shows through simulation that incorporation of MPPT in the PV system under steady-state renders an optimal operating point which results in a stable operation irrespective of weather condition and without feed-forward compensation. Moreover, an eigen value analysis is carried out both with the MPPT and without the MPPT to verify the simulated results.