A Novel Model Predictive Control for Stability Improvement of Small Scaled Zero-inertia Multiple DGs Micro-grid

A zero-inertia micro-grid is a power system consisting of multiple renewable energy power sources and energy storage systems without the presence of conventional synchronous generators. In such a system, a large variation of the load or source sides during the islanded mode of operation extremely degrades the micro-grid's voltage and frequency stability. This study presents a virtual inertia-based predictive control strategy for a small-scale zero-inertia multiple distributed generators (DGs) micro-grid. In islanded mode, Voltage Model Predictive Control (VMPC) was implemented to control and maintain the voltage and frequency of the micro-grid. However, instabilities in frequency and voltage may rise at the Point of Common Coupling (PCC) due to large variations at both source and load sides. Therefore, the proposed virtual inertia loop calculates the amount of active power to be delivered or absorbed by each DG, and its effect is reflected in the estimated d current component of the VMPC, thus providing better frequency regulation. In grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. The control approach also enables the DG plug and play characteristics. The performance of the control strategy was investigated and verified using the PSCAD/EMTDC software platform.

Study the Effect of Water Content on the Structure of Electrochemically Prepared TiO2 Nanotubes

In this research, the pure titanium foil was treated in glycerol base electrolyte with 0.7 wt.% NH4F and a small amount of H2O at 17 V for 2 hours by electrochemical anodization process in order to prepare Titania nanotube arrays at room temperature (~25 ºC), different water content was added to the electrolyte as a tube enhancing agent. The high density uniform arrays are prepared by using organized and well aligned these tubes. The average size of tube diameter, ranging from 57 to 92 nm which found it increases with increasing water content, and the length of the tube ranging from 2.76 to 4.12 µm, also found to increase with increasing water content and ranging in size of wall thickness from 23 to 35 nm. A possible growth mechanism is presented. The X-ray diffraction (XRD), atomic force microscopy (AFM), and scanning electron microscopy (SEM) were utilized to study the structure and morphology of the Titania films.

Economic Assessment of Power Grid Development Using Artificial Bee Colony Algorithm

The electricity system is generally rapidly developing for covering various power demands with requiring a reliable and safe supply where the substructures are expanding further in generation systems, transmission systems, and distribution systems. However, the system must be run economically to access energy at a cost-effective level related to existing energy enterprises and energy consumption in the load which is represented periodically in the total costs of operations for all operating units. As a basis for its determination, the transmission of economic power within the technical limits applicable is taken into consideration. Environmental factors, on the other hand, are also an impediment to technical limitations. As a result, the operation's economic measure is expressed in the process of providing and selling energy to customers. These works use the Artificial Bees Colony algorithm to determine the scheduling of generating units using the basic principle of optimization to describe its relationship as an economic function. The IEEE-30 bus system is used as a basic model for system development. The analysis' findings show that the weighting factor scheme has an impact on the minimum total cost and that the combination of the electricity distribution process and environmental factors has implications for the operational financial condition and electricity production. The power output, in particular, is proportional to the cost of each generating unit.

Improved Backstepping Control of a DFIG based Wind Energy Conversion System using Ant Lion Optimizer Algorithm

In this paper, an improved Backstepping control based on a recent optimization method called Ant Lion Optimizer (ALO) algorithm for a Doubly Fed Induction Generator (DFIG) driven by a wind turbine is designed and presented. ALO algorithm is applied for obtaining optimum Backstepping control (BCS) parameters that are able to make the drive more robust with a faster dynamic response, higher accuracy and steady performance. The fitness function of the ALO algorithm to be minimized is designed using some indexes criterion like Integral Time Absolute Error (ITAE) and Integral Time Square Error (ITSE). Simulation tests are carried out in MATLAB/Simulink environment to validate the effectiveness of the proposed BCS-ALO and compared to the conventional BCS control. The results prove that the objectives of this paper were accomplished in terms of robustness, better dynamic efficiency, reduced harmonic distortion, minimization of stator powers ripples and performing well in solving the problem of uncertainty of the model parameter.

Efficient Transmission of 2D Chaotic Maps Encrypted Images with DWT-Based SC-FDMA LTE System

The single-carrier frequency division multiple access (SC-FDMA) is a promising technique that has been adopted as an uplink transmission scheme in the long-term evolution (LTE) cellular system. This is attributed to its advantages such as the low peak-to-average power ratio (PAPR) and the utilization of frequency-domain equalizers to resolve the problem of inter-symbol interference (ISI). In this paper, a Discrete Wavelet Transform (DWT) based SC-FDMA system is proposed for the effective transmission of encrypted images. The 2D Chaotic baker map encryption algorithm has been used to encrypt images to enhance their security during transmission via SC-FDMA- based systems. The performance of the process of encrypted image transmission using the 2D Chaotic baker map algorithm with wavelet transform-based SC-FDMA (DWT SC-FDMA) system is evaluated in terms of different performance metrics, with comparison to Discrete Fourier Transform SC-FDMA (DFT SC-FDMA) and, Discrete Cosine Transform SC-FDMA (DCT SC-FDMA) systems. The viability of the proposed scheme was tested with different wireless channel models and different subcarriers mapping schemes. Experimental results show that the proposed method of the encrypted image transmission via the DWT SC-FDMA system provides a remarkable performance gain compared to the other versions of the SC-FDMA system in terms of the PSNR, and the BER metrics in the wireless channel models. It also demonstrates the effectiveness of the proposed scheme and adds a degree of encryption to the transmitted images through the wireless channels.

Investigation of SVPWM Based Sliding Mode Control Application on Dual-Star Induction Motor and Dual Open-End Winding Induction Motor

The present paper deals with a comparative study of the Sliding Mode Control (SMC) technique application on three-phase Dual Star Induction Motor (DSIM) topology and the Dual Open-End Winding Induction Motor (DOEWIM). Where, in these two topologies the Space Vector Pulse Width Modulation (SVPWM) has been used for the control of the two two-level inverters and the four two-level inverters, which have been used to power the two motors under application respectively. The main objective of this study is to demonstrate the higher performances of the DOEWIM under the application of SMC combined with SVPWWM, which aims to overcome the main drawbacks faced when using the conventional topology DSIM in industrial applications. Especially in terms of decreasing the harmonics content in the stator current, reducing the overall ripples of the developed electromagnetic torque, the elimination of the common mode voltage and increasing the robustness against the load torque variation and speed reverse. The obtained simulation results show clearly the main advantages of using the topology of DOEWIM compared to the DSIM topology which present a very promising application especially in heavy industrial requiring high power motors.

Extreme Value Analysis for Time-variable Mixed Workload

Proper timeliness is vital for a lot of real-world computing systems. Understanding the phenomena of extreme workloads is essential because unhandled, extreme workloads could cause violation of timeliness requirements, service degradation, and even downtime. Extremity can have multiple roots: (1) service requests can naturally produce extreme workloads; (2) bursts could randomly occur on a probabilistic basis in case of a mixed workload in multiservice systems; (3) workload spikes typically happen in deadline bound tasks.Extreme Value Analysis (EVA) is a statistical method for modeling the extremely deviant values corresponding to the largest values. The foundation mathematics of EVA, the Extreme Value Theorem, requires the dataset to be independent and identically distributed. However, this is not generally true in practice because, usually, real-life processes are a mixture of sources with identifiable patterns. For example, seasonality and periodic fluctuations are regularly occurring patterns. Deadlines can be purely periodic, e.g., monthly tax submissions, or time variable, e.g., university homework submission with variable semester time schedules.We propose to preprocess the data using time series decomposition to separate the stochastic process causing extreme values. Moreover, we focus on the case where the root cause of the extreme values is the same mechanism: a deadline. We exploit known deadlines using dynamic time warp to search for the recurring similar workload peak patterns varying in time and amplitude.

Improved Runtime for the Synchronous Multi-door Filling

In this paper, a particular type of dispersion is further investigated, which is called Filling. In this problem, robots are injected one by one into an a priori not known area and have to travel across until the whole area is covered. The coverage is achieved by a robotic team whose hardware capabilities are restricted in order to maintain low production costs. This includes limited viewing and communication ranges. In this work, we present an algorithm solving the synchronous Filling problem in O((k + ∆)·n) time steps by n robots with a viewing range of 1 hop, where k is the number of doors, n is the number of vertices of the graph, and ∆ is the maximum degree of the graph. This improves the best previously known running time bound of O(k · ∆ · n). Furthermore, we remove the constraint from the previous algorithm that the door vertices need to have a degree of 1.

Proposed Hybrid Power Optimization for Wind Turbine/Battery System

This paper contributes to the feasibility of a wind turbine/battery system with a hybrid power optimization controller. The proposed method is based on a mathematical optimization approach and allows to achieve an efficient operation of the maximum power point tracking (MPPT) algorithms to obtain an optimal performance level of the wind system and a minimal stress on the battery storage. The different powers have been controlled by a power management control (PMC) method. The objectives of the PMC based are, in first part to satisfy the load power demand and in second part to maintain the state of charge of the battery bank to prevent blackout and to extend the batteries life. A measurement of wind speeds was made during a whole day using a data acquisition system at the laboratory. Also, the different wind turbine parameters were identified at the same Laboratory. All these parameters have been used in simulation models in order to obtain the most realistic mathematical models that are close to the experiment. Real time simulation is performed using RT LAB simulator and the obtained results were matching those obtained in numerical simulation using Matlab/Simulink. The obtained results under two different wind speed profile, with the different comparisons are presented to show the feasibility and the improvement of the proposed study in terms of power, efficiency, time response and effect on battery state of charge under two different wind speeds profile.

Patch Antenna Based on MUC for Wi-Fi and 5G

This communication reported the patch antenna working at Wi-Fi and 5G bands. To acquire compactness the side lengths of the patch are taken based on upper-frequency band (3.3 GHz). Dual-band operation (lower resonating band) is realized by loading the Mushroom Unit Cell (MUC) along the bottom right corner of the patch. To obtain Circular Polarization (CP) at the 5G band the conventional patch is modified with fractal boundary. This blend of the Double Negative Transmission Lines metamaterials (DNG TL), as well as fractal concepts yielded good compactness suitable for ultra-thin portable gadgets. Measured results have good correlation with simulated data from HFSS. The obtained bandwidths at the lower and upper bands are 2.51 % and 6.23 % when the Poly fractal curves are introduced. CP bandwidth of the proposed antenna at 5G band obtained from the measured data is 2.35 % which is the highest to the best of authors' knowledge for this type of thin antennas.