scholarly journals Linear Array Synthesis for Wireless Power Transmission Based on Brain Storm Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Guang Xu Liu ◽  
Qin Qin ◽  
Qing He Zhang
Keyword(s):  
Optimization Algorithm ◽  
Power Transmission ◽  
Linear Array ◽  
Collection Efficiency ◽  
Linear Antenna ◽  
Wireless Power ◽  
Optimization Constraints ◽  
Brain Storm Optimization ◽  
Simulation Results ◽  
The Brain

Based on the brain storm optimization algorithm, this paper proposed a new method to optimize the beam collection efficiency of the linear antenna array. In the process of optimization, constraints such as aperture size and minimum antenna spacing are considered. In this paper, the optimization with different antenna apertures, different antenna angles, and different array numbers are studied. A series of representative data and simulation results are given and the superiority of the brainstorming algorithm is demonstrated by comparing with the genetic algorithm.

scholarly journals Shrinkage of Real Power Loss by Enriched Brain Storm Optimization Algorithm

2019 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Human Being ◽  
New Approach ◽  
Real Power ◽  
Brain Storm Optimization ◽  
Course Of Action ◽  
Simulation Results ◽  
Power Problem

<p class="Author">This paper proposes Enriched Brain Storm Optimization (EBSO) algorithm is used for soving reactive power problem. Human being are the most intellectual creature in this world. Unsurprisingly, optimization algorithm stimulated by human being inspired problem solving procedure should be advanced than the optimization algorithms enthused by collective deeds of ants, bee, etc. In this paper, we commence a new Enriched brain storm optimization algorithm, which was enthused by the human brainstorming course of action. In the projected Enriched Brain Storm Optimization (EBSO) algorithm, the vibrant clustering strategy is used to perk up the k-means clustering process. The most important view of the vibrant clustering strategy is that; regularly execute the k-means clustering after a definite number of generations, so that the swapping of information wrap all ideas in the clusters to accomplish suitable searching capability. This new approach leads to wonderful results with little computational efforts. In order to evaluate the efficiency of the proposed Enriched Brain Storm Optimization (EBSO) algorithm, has been tested standard IEEE 118 &amp; practical 191 bus test systems and compared to other standard reported algorithms. Simulation results show that Enriched Brain Storm Optimization (EBSO) algorithm is superior to other algorithms in reducing the real power loss.</p>

scholarly journals A performance predictor of beamforming versus time-reversal based far-field wireless power transfer from linear array

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hong Soo Park ◽  
Sun K. Hong
Keyword(s):  
Time Reversal ◽  
Power Transmission ◽  
Linear Array ◽  
Wireless Power Transfer ◽  
Far Field ◽  
Power Transfer ◽  
Wireless Power ◽  
Dynamic Propagation ◽  
Received Power ◽  
Indoor Scenarios

AbstractFor far-field wireless power transfer (WPT) in a complex propagation environment, a time-reversal (TR) based WPT that can overcome the drawbacks of conventional beamforming (BF) by taking advantage of multipath has been recently proposed. However, due to the WPT performance of BF and TR depending on the complexity of the propagation environment, the performance prediction between BF versus TR would be required. We present a detailed and generalized analysis of the recently proposed performance metric referred to as the peak received power ratio (PRPR) for linear array-based WPT. Here, the effectiveness of PRPR is verified via measurement for free space and indoor scenarios. The results demonstrate that PRPR is directly related to the complexity of the propagation environment and the corresponding power transmission capability of BF and TR. That is, the higher the complexity, the greater the value of PRPR and TR outperforms BF with higher peak power given the same average transmit power and vice versa. The mode decision between BF and TR based on PRPR potentially promises efficient far-field WPT even in a dynamic propagation environment.

scholarly journals REDUCTION OF TRUE POWER LOSS BY IMPROVED ALGORITHM

2018 ◽  
Vol 6 (8) ◽  
pp. 105-113
Author(s):  
K. Lenin
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
New Approach ◽  
Real Power ◽  
Brain Storm Optimization ◽  
Course Of Action ◽  
Simulation Results ◽  
Power Problem

This paper proposes Improved Brain Storm Optimization (IBSO) algorithm is used for solving reactive power problem. predictably, optimization algorithm stimulated by human being inspired problem-solving procedure should be highly developed than the optimization algorithms enthused by collective deeds of ants, bee, etc. In this paper, a new Improved brain storm optimization algorithm defined, which was stimulated by the human brainstorming course of action. In the projected Improved Brain Storm Optimization (IBSO) algorithm, the vibrant clustering strategy is used to perk up the k-means clustering process & exchange of information wrap all ideas in the clusters to accomplish suitable searching capability. This new approach leads to wonderful results with little computational efforts. In order to evaluate the efficiency of the proposed Improved Brain Storm Optimization (IBSO) algorithm, has been tested standard IEEE 30 bus test system and compared to other standard reported algorithms. Simulation results show that Improved Brain Storm Optimization (IBSO) algorithm is superior to other algorithms in reducing the real power loss.

Design and Analysis of a Single-Band Printed Rectenna Circuit at WiFi Frequency for Microwave Power Transmission

2019 ◽  
Vol 15 (2) ◽  
pp. 33-39
Author(s):  
Ahmad Salih ◽  
Abdulkareem Abdullah
Keyword(s):  
Power Transmission ◽  
Impedance Matching ◽  
Input Power ◽  
Single Band ◽  
Wireless Power ◽  
Question Mark ◽  
Software Packages ◽  
Maximum Conversion ◽  
Maximum Conversion Efficiency ◽  
Simulation Results

In this paper, a single-band printed rectenna of size (45×36) mm2 has been designed and analyzed to work at WiFi frequency of 2.4 GHz for wireless power transmission. The antenna part of this rectenna has the shape of question mark patch along with an inverted L-shape resonator and printed on FR4 substrate. The rectifier part of this rectenna is also printed on FR4 substrate and consisted of impedance matching network, AC-to-DC conversion circuit and a DC filter. The design and simulation results of this rectenna have been done with the help of CST 2018 and ADS 2017 software packages. The maximum conversion efficiency obtained by this rectenna is found as 57.141% at an input power of 2 dBm and a load of 900 Ω.

scholarly journals Analysis and design of a class E current-driven rectifier for 1 MHz wireless power transfer system

2019 ◽  
Vol 70 (1) ◽  
pp. 58-63
Author(s):  
Krystian Rybicki ◽  
Rafał M. Wojciechowski
Keyword(s):  
Power Transmission ◽  
Transmission System ◽  
Design Stage ◽  
Operating Efficiency ◽  
Wireless Power ◽  
Wireless Power Transmission ◽  
Power Transmission System ◽  
Simulation Results ◽  
Selection Of ◽  
Class E

Abstract The paper presents the design of the class E current-driven rectifier, which is intended for operation in the wireless power transmission system, as well as the concept of selection of the rectifier parameters which allows the operation with high efficiency. The selection of the rectifier parameters was performed with a view to the use of the existing wireless power transmission (WPT) system. The procedure for selection of the rectifier parameters has been proposed to enable its optimal use in reference to the system parameters given already at the design stage, ie; load resistance and the coil magnetic coupling factor (distance between coils). In order to verify the correctness of the procedure for selection of the parameters, the numerical model of the system which consists of the class E resonance inverter, the air-core transformer and the designed E class rectifier system was developed in the LTspice environment. Simulation tests and analysis of the obtained calculation results were performed. Based on the simulation results, a prototype of the class E rectifier system which cooperates with the existing wireless power transmission system supplied from the class E inverter was developed. The obtained results of laboratory measurements demonstrated a high compliance with the simulation results, thus, confirming the correctness of the proposed design procedure and the high operating efficiency of the rectifier system.

scholarly journals A Wirelessly Powered Implantable CMOS Neural Recording Sensor Array using Pulse-based Neural Amplifier

2019 ◽  
Author(s):  
Geoffrey Mulberry ◽  
Kevin A. White ◽  
Brian N. Kim
Keyword(s):  
Power Transmission ◽  
Neural Recording ◽  
In Vivo Studies ◽  
Wireless Power ◽  
Wireless Data ◽  
Electrical Measurements ◽  
Wireless Data Transmission ◽  
Delta Modulation ◽  
The Brain

AbstractThe most important organ in the human body is unquestionably the brain. Yet, despite its importance, it is one of the least well understood organs. One reason for this lack of understanding of the brain is the lack of data available to researchers from in vivo studies. Historically, collecting measurements from the brain has been difficult due to the high risk to the patient. Recently technology has been developed to allow electrical measurements to be taken from the brain directly, however most systems involve non-permanent sensors because of the requirement for transcranial wiring for power and data. Developments in the field of CMOS circuit design, wireless power transmission, and wireless data transmission have enabled the creation of implantable neural recording devices as a combination of these technologies. The implant designed in this paper is ∼15 mm in diameter and 2 mm at its thickest point on a flexible polyamide PCB. The flexible nature of the implant allows for the implant to conform to the surface of the brain. The implant requires no transcranial orifice since it is powered wirelessly and transmits data wirelessly via Bluetooth low energy. The CMOS neural amplifier chip on the implant utilizes an enhanced form of delta modulation to remove the requirement for large ADCs to be present on the die, saving space and enabling 1024 amplifiers and electrodes to be present on the chip. The implant is capable of measuring, modulating, and wirelessly transmitting a millivolt order signal to a PC for demodulation and analysis.

An Optimization Algorithm Based on Brainstorming Process

2013 ◽  
pp. 137-166
Author(s):  
Yuhui Shi
Keyword(s):  
Optimization Algorithm ◽  
Information Entropy ◽  
The Other ◽  
Future Research ◽  
Brain Storm Optimization ◽  
Cluster Distance ◽  
Simulation Results ◽  
Better Than

In this paper, the human brainstorming process is modeled, based on which two versions of Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II, performs better than the other BSO algorithm, BSO-I, in general. Furthermore, average inter-cluster distance Dc and inter-cluster diversity De are defined, which can be used to measure and monitor the distribution of cluster centroids and information entropy of the population over iterations. Simulation results illustrate that further improvement could be achieved by taking advantage of information revealed by Dc and/or De, which points at one direction for future research on BSO algorithms.

An Optimization Algorithm Based on Brainstorming Process

2015 ◽  
pp. 1-35 ◽  
Author(s):  
Yuhui Shi
Keyword(s):  
Optimization Algorithm ◽  
Information Entropy ◽  
The Other ◽  
Future Research ◽  
Brain Storm Optimization ◽  
Cluster Distance ◽  
Simulation Results ◽  
Better Than

In this chapter, the human brainstorming process is modeled, based on which two versions of a Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II, performs better than the other BSO algorithm, BSO-I, in general. Furthermore, average inter-cluster distance Dc and inter-cluster diversity De are defined, which can be used to measure and monitor the distribution of cluster centroids and information entropy of the population over iterations. Simulation results illustrate that further improvement could be achieved by taking advantage of information revealed by Dc, which points at one direction for future research on BSO algorithms.

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