Engineering Commons^™

การวิเคราะห์ความคุ้มค่าของการป้องกันอัคคีภัยกับระบบผลิตไฟฟ้าพลังงานแสงอาทิตย์บนหลังคา, อัยลดา วาปีทำ

Chulalongkorn University Theses and Dissertations (Chula ETD)

บ้านอยู่อาศัยในประเทศไทยเริ่มมีความสนใจในการติดตั้งระบบผลิตไฟฟ้าพลังงานแสงอาทิตย์เพิ่มมากขึ้น ซึ่งการติดตั้งระบบผลิตไฟฟ้าฯ ในหลายประเทศได้เกิดปัญหาการเกิดอัคคีภัยสร้างความเสียหายทั้งทรัพย์สิน และชีวิต ในพื้นที่เกิดอัคคีภัยนักดับเพลิงจะมีความเสี่ยงอันตรายจากแรงดันกระแสไฟฟ้าที่สูงจึงเป็นที่มาของงานวิจัยนี้ โดยศึกษาความคุ้มค่าของการติดตั้งอุปกรณ์หยุดทำงานฉุกเฉินและไมโครอินเวอร์เตอร์ ขนาด 5 kWp 1 Phase ในพื้นที่ภาคกลาง โดยจำลองการติดตั้งระบบผลิตไฟฟ้าฯ 3 กรณี ได้แก่กรณีที่ 1 ติดตั้งระบบผลิตไฟฟ้าพลังงานแสงอาทิตย์บนหลังคา แบบทั่วไป กรณีที่ 2 ติดตั้งระบบผลิตไฟฟ้าพลังงานแสงอาทิตย์ แบบติดตั้งอุปกรณ์หยุดทำงานฉุกเฉิน และกรณีที่ 3 ติดตั้งระบบผลิตไฟฟ้าพลังงานแสงอาทิตย์ แบบติดตั้งไมโครอินเวอร์เตอร์ จากนั้นทำการสำรวจข้อมูล ราคาบ้านที่ติดตั้งไม่รวมทรัพย์สินภายในบ้านและราคาที่ดิน ราคาหลังคาบ้านที่ติดตั้ง ราคาระบบที่ติดตั้ง พื้นที่บ้านที่ติดตั้ง และนำข้อมูลที่ได้มาทำการหาราคาเฉลี่ย เมื่อได้ข้อมูลเบื้องต้นแล้วนำแต่ละระบบมาเปรียบเทียบค่าพลังงานที่ผลิตได้ โดยโปรแกรม PVSyst ค่าพลังงานที่ผลิตได้ตลอดระยะเวลาโครงการ 25 ปี เท่ากับ 160,380, 165,481 และ 168,961 kWh ตามลำดับ นำข้อมูลที่ได้ทำการคำนวณทางด้านเศรษฐศาสตร์ เพื่อหาความคุ้มค่าของโครงการ มูลล่าปัจจุบันสุทธิ (NPV) เท่ากับ 55,434.83, 42,531.10 และ -44,171.64 ตามลำดับ อัตราผลตอบแทนภายใน (IRR) เท่ากับ 17.96%, 16.46% และ 10.67% ตามลำดับ ระยะเวลาคืนทุนเท่ากับ 5.27, 5.79 และ8.52 ปี ตามลำดับ ต้นทุนต่อหน่วยไฟฟ้าตลอดอายุโครงการ (LCOE) 1.53, 1.61 และ 2.03 บาทต่อหน่วย จำลองเหตุการณ์การเกิดอัคคีภัยใน 3 เหตุการณ์ ได้แก่ เหตุการณ์ที่ 1 เกิดอัคคีภัยความเสียหายเพียงแค่ระบบผลิตไฟฟ้าฯ บนหลังคา เหตุการณ์ที่ 2 เกิดอัคคีภัยความเสียหายในบริเวณหลังคาบ้านอยู่อาศัยทั้งหมด และเหตุการณ์ที่ 3 เกิดอัคคีภัยความเสียหายทั้งอาคารบ้านอยู่อาศัย สืบค้นข้อมูลการเกิดอัคคีภัยในประเทศไทยพบว่ามีการเกิดอัคคีภัยระบบผลิตไฟฟ้าพลังงานแสงอาทิตย์เพิ่มขึ้นทุกๆปี จึงทำการสอบถามกับผู้เชี่ยวชาญถึงมาตรฐานที่ใช้นิยมใช้ มาตรฐานวสท. และข้อกำหนดของการไฟฟ้า ปัจจัยเสี่ยงที่ทำให้เกิดอัคคีภัยที่พบมากที่สุดคือ อุปกรณ์เชื่อมต่อ (MC4) และอุณหภูมิแวดล้อมพื้นที่ติดตั้ง ผลการวิจัยพบว่าหากพิจารณาความคุ้มค่าทางด้านเศรษฐศาสตร์ในการติดตั้งกรณีที่ …

Deep Iterative Convolutional Neural Network For Face Image Super-Resolution, Hein Htet Aung

Chulalongkorn University Theses and Dissertations (Chula ETD)

Face images are often used today for many purposes, including facial identification and recognition. Face identification is used in security to trace crimes. The face application performs poorly due to the camera's low quality and environmental degradation issues. In this thesis, we explore face image super-resolution, which raises low-resolution to high resolution images. We proposed a deep iterative convolutional neural network using attention mechanisms and spatial feature transformation for face super-resolution. The input low-resolution image is enlarged into a super-resolution face image. Then, the image has repeatedly estimated the alignment to enhance the super-resolution image. The experiment was conducted on …

Diabetic Retinopathy Severity Classification Using Convolutional Neural Network Withtransfer Learning, Pranajit Kumar Das

Chulalongkorn University Theses and Dissertations (Chula ETD)

Diabetic Retinopathy is a common retina disease caused by diabetes that is very difficult to diagnose initially because of its asymptomatic nature, which leads to permanent vision loss. Early and accurate detection of diabetic retinopathy is an effective way to prevent blindness. While screening programs are the most effective means of detecting diabetic retinopathy, it has various limitations like time consuming, laborious tasks, require a lot of expert ophthalmologists and technicians with standardized medical equipment. Automatic diabetic retinopathy classification using artificial intelligence and computer vision techniques mostly overcome the above-mentioned limitations despite it still being a challenging task. In this …

Artificial Intelligence-Powered Chronic Wound Management System: Towards Human Digital Twins, Salih Sarp

Theses and Dissertations

Artificial Intelligence (AI) has witnessed increased application and widespread adoption over the past decade. AI applications to medical images have the potential to assist caregivers in deciding on a proper chronic wound treatment plan by helping them to understand wound and tissue classification and border segmentation, as well as visual image synthesis.

This dissertation explores chronic wound management using AI methods, such as Generative Adversarial Networks (GAN) and Explainable AI (XAI) techniques. The wound images are collected, grouped, and processed. One primary objective of this research is to develop a series of AI models, not only to present the potential …

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

Smart City Management Using Machine Learning Techniques, Mostafa Zaman

Theses and Dissertations

In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …

Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng

Electronic Theses and Dissertations

Convolutional Neural Network (CNN) is a neural network developed for processing image data. CNNs have been studied extensively and have been used in numerous computer vision tasks such as image classification and segmentation, object detection and recognition, etc. [1] Although, the CNNs-based approaches showed humanlevel performances in these tasks [2], they require heavy computation in both training and inference stages, and the models consist of millions of parameters. This hinders the development and deployment of CNN-based models for real world applications. Neural Network Pruning and Compression techniques have been proposed [3, 4] to reduce the computation complexity of trained CNNs …

Examining The Size Of The Latent Space Of Convolutional Variational Autoencoders Trained With Spectral Topographic Maps Of Eeg Frequency Bands, Taufique Ahmed, Luca Longo

Articles

Electroencephalography (EEG) is a technique of recording brain electrical potentials using electrodes placed on the scalp [1]. It is well known that EEG signals contain essential information in the frequency, temporal and spatial domains. For example, some studies have converted EEG signals into topographic power head maps to preserve spatial information [2]. Others have produced spectral topographic head maps of different EEG bands to both preserve information in The associate editor coordinating the review of this manuscript and approving it for publication was Ludovico Minati . the spatial domain and take advantage of the information in the frequency domain [3]. …

A Risk-Averse Mechanism For Suicidality Assessment On Social Media, Ramit Sawhney, Atula Tejaswi Neerkaje, Manas Gaur

Publications

Recent studies have shown that social media has increasingly become a platform for users to express suicidal thoughts outside traditional clinical settings. With advances in Natural Language Processing strategies, it is now possible to design automated systems to assess suicide risk. However, such systems may generate uncertain predictions, leading to severe consequences. We hence reformulate suicide risk assessment as a selective prioritized prediction problem over the Columbia Suicide Severity Risk Scale (C-SSRS). We propose SASI, a risk-averse and self-aware transformer-based hierarchical attention classifier, augmented to refrain from making uncertain predictions. We show that SASI is able to refrain from 83% …

Process Knowledge-Infused Learning For Suicidality Assessment On Social Media, Kaushik Roy, Manas Gaur, Qi Zhang, Amit Sheth

Publications

Improving the performance and natural language explanations of deep learning algorithms is a priority for adoption by humans in the real world. In several domains, such as healthcare, such technology has significant potential to reduce the burden on humans by providing quality assistance at scale. However, current methods rely on the traditional pipeline of predicting labels from data, thus completely ignoring the process and guidelines used to obtain the labels. Furthermore, post hoc explanations on the data to label prediction using explainable AI (XAI) models, while satisfactory to computer scientists, leave much to be desired to the end users due …

The Lognometer: A New Normalized And Computerized Device For Assessing The Neurodevelopment Of Fine Motor Control In Children, Christian O'Reilly, Rejean Plamondon, Nadir Faci

Publications

Motor skills are fundamental for the development of children. Neurodevelopmental tests currently used by professionals for measuring motor control maturity exhibit several limitations. To address some of these, we have designed the Lognometer, a tablet-based device that can run computerized neuromotor tests. To normalize this tool against a representative population, we collected handwritten triangles from 780 children. We used the Sigma-Lognormal model and a prototype-based parameter estimation algorithm to analyze these movements. To ensure clinical acceptance, we developed an explainable solution relying on statistical regression. We evaluated how well the proposed lognormal decomposition captures the motor control maturation between 6 …

Comparing Symbolic And Connectionist Algorithms For Correlating The Age Of Healthy Children With Sigma-Lognormal Neuromuscular Parameters, Zigeng Zhang, Christian O'Reilly, Rejean Plamondon

Publications

It is important to accurately evaluate the motor control maturity to help physicians diagnose delayed or abnormal motor development in children. Traditionally, it has been challenging to design assessment methods that are practical and accurate at the same time. This study aims to develop an effective algorithm to predict motor control maturity based on the Kinematic Theory of rapid human movements. We used handwritten pen strokes made on an electronic tablet by 513 children (5.5 to 13 years of age). We considered two types of movements: a single stroke and a triangle drawing test. For the analysis, Sigma-Lognormal parameters were …

Ksat: Knowledge-Infused Self Attention Transformer - Integrating Multiple Domain-Specific Contexts, Kaushik Roy, Yuxin Zi, Vignesh Narayanan, Manas Gaur, Amit P. Sheth

Publications

Domain-specific language understanding requires integrating multiple pieces of relevant contextual information. For example, we see both suicide and depression related behavior (multiple contexts) in the text “I have a gun and feel pretty bad about my life, and it wouldn’t be the worst thing if I didn’t wake up tomorrow”. Domain specificity in self-attention architectures is handled by fine-tuning on excerpts from relevant domain specific resources (datasets and external knowledge - medical textbook chapters on mental health diagnosis related to suicide and depression). We propose a modified self-attention architecture Knowledge infused Self Attention Transformer (KSAT) that achieves the integration of …

Wise Causal Models: Wisdom Infused Semantics Enhanced Causal Models - A Study In Suicidality Diagnosis, Kaushik Roy, Yuxin Zi, Vignesh Narayanan, Manas Gaur, Sanjay Chandrasekar, Amit Sheth

Publications

The COVID-19 Pandemic has highlighted the gap between the number of mental health care seekers and care providers. Netizens have taken to internet-based platforms such as Reddit to express their experiences. Mental illness diagnosis processes have clinically accepted causal interpretations and semantics. Curiously, mental illness diagnosis accuracy is low relative to similar well-studied illnesses. Motivated by this discrepancy, we propose Wisdom Infused Semantics Enhanced (WISE) causal models, inspired by the wisdom of the crowd idea that learns from a collective agreement among causal models and their semantics for mental illness diagnoses. We use suicidality diagnosis task descriptions, datasets, and baseline …

Recent Advancements In Electrochemical Conversion Of Carbon Dioxide, Nandan Nag, Amit Kumar, Sumit Sharma, Sandeep Kumar, Amit K. Thakur

Civil & Environmental Engineering Faculty Publications

Electrochemical reduction of carbon dioxide into eco-friendly and clean products is a promising approach to eradicate pollution. Although carbon dioxide emission is inhibited by the advent of renewable sources of energy, it is present in the atmosphere and needs to be cleaned. The reduction of carbon dioxide from atmospheric gases can be accomplished by its adsorption and subsequent transportation to electrolytic chambers, where it is reduced to hydrocarbons, organic acids or carbonates. This review focuses on developing a three compartment electrochemical cell to reduce carbon dioxide used as a catholyte. Various factors affecting the electrochemical reduction of carbon dioxide and …

Analysis Of Electromagnetic Interference Problems Causedbyhigh-Speed Multiplayer Boards With Split Referenceplane, Xin Fang

Masters Theses

"Digital/Analog ground partitioning has been used to isolate noisy digital and power current from sensitive analog currents in high-speed multiplayer printed circuit boards. The through-hole signal via enables convenient routing and component placement on the PCB and is used for signal interconnections when the signal traces are changing the layers. This design, however, breaks the current return path for signal traces that cross the two separated grounds, which causes undesired effects such as signal distortion and radiated emission.

Electromagnetic mechanism associated with them needs to be understood to control and suppress these undesired effects. In this paper, we have investigated …

Quantum Mechanics And Control Using Fractional Calculus: A Study Of The Shutter Problem For Fractional Quantum Fields, Jonathan Blackledge

Articles

The ‘diffraction in space’ and the ‘diffraction in time’ phenomena are considered in regard to a continuously open, and a closed shutter that is opened at an instant in time, respectively. The purpose of this is to provide a background to the principal theme of this article, which is to extend the ‘quantum shutter problem’ for the case when the wave function is determined by the fundamental solution to a partial differential equation with a fractional derivative of space or of time. This involves the development of Green’s function solutions for the space- and time-fractional Schrödinger equation and the time-fractional …

Electrooptic, Pyroelectric And Dielectric Spectroscopic Studies Of Nematic And Twist Bend Nematic Phases Of Achiral Hockey-Shaped Bent-Core Liquid Crystal, Sithara P. Sreenilayam, Neelam Yadav, Yuri Panarin, G. Shanker, J.K. Vij

Articles

Experimental and theoretical investigations of the twist-bend nematic (NTB) phase in liquid crystals have recently received significant attention for reasons of unusual and interesting characteristics of the NTB. Though NTB was predicted to exist for rigid bent-core LCs by Ivan Dozov in 2001, nevertheless it has unambiguously been proven to exist only in a few bent-core systems so far. Here the characteristics of both the nematic (N) and NTB phases are investigated for a hockey shaped achiral rigid bent-core LC, called BCI, in planar and homeotropic aligned cells, using polarizing optical microscopy, electro-optics, pyroelectricity and wide band dielectric spectroscopy. Spontaneous …

Hosting A Community-Based Local Electricity Market In A Residential Network, Aziz Saif, Shafi K. Khadem, Michael Conlon, Brian Norton

Articles

This paper presents the potential of building a local electricity market (LEM) to boost the deployment of the local energy communities, centred around active customers with distributed energy resources (DERs). To conduct a comprehensive and detailed study on different cases with reduced computational burdens, this paper adopts a simplified modelling approach where the market and network model simulations are performed in a cascaded, decoupled fashion. This allows achieving the optimal LEM output for the energy community with different DER assets that are not bounded by the network constraints. The investigation involves quantifying the benefits brought by LEM to energy communities …

Designing A Robust Decentralized Energy Transactions Framework For Active Prosumers In Peer-To-Peer Local Electricity Markets, Mehdi Mehdinejad, Heidar Ali Shayanfar, Behnam Mohammadi-Ivatloo, Hamed Nafisi

Articles

In this paper, a fully decentralized local energy market based on peer-to-peer(P2P) trading is proposed for small-scale prosumers. In the proposed market, the prosumers are classified as buyers and sellers and can bilaterally engage in energy trading (P2P) with each other. The buyer prosumers are equipped with electrical storage and can participate in a demand response (DR) program while protecting their privacy. In addition to bilateral negotiating with the local sellers, these players can compensate for their energy deficiency from the upstream market as the retail market at hours without local generation. In this paper, the retail market price is …

Spontaneous Symmetry Breaking And Linear Electrooptic Response In The Achiral Ferronematic Compound, Neelam Yadav, Yuri Panarin, Wanhe Jiang, Georg H. Mehl, J.K. Vij

Articles

A compound with the constituent non-chiral molecules, DIO, known to exhibit three nematic subphases namely N, Nx and NF, is studied by polarizing microscopy as function of the alignment layers on one of the substrates, no alignment on any of the substrates, alignment layer on both substrates with parallel and antiparallel rubbing, different cell spacings. The cell with one alignment layer is also studied by electro-optics. N is found to be a conventional nematic phase, but it shows two additional unusual features: chiral domains of opposite chirality and the linear EO response to the applied signal under certain experimental conditions. …

Two Mechanisms For Formation Of Ferronematic Phase Studied By Dielectric Spectroscopy, Neelam Yadav, Yuri Panarin, J.K. Vij, Wanhe Jiang, Georg H. Mehl

Articles

A non-chiral ferroelectric nematic compound DIO was studied by dielectric spectroscopy in the frequency range 0.01 Hz to 10 MHz over a wide range of temperatures. The compound exhibits three nematic phases on cooling from the isotropic phase, viz. the ordinary paraelectric nematic N; intermediate nematic NX and ferroelectric NF phases. The lower frequency relaxation process P1 is similar to those observed in other ferronematic compounds. It is a continuation of the molecular flip-flop mode in the isotropic phase and corresponds to the collective movement of dipoles which are strongly coupled with splay fluctuations in the nematic phases. In addition …

Dynamic Effect Of Disintegrated Energy Consumption And Economic Complexity On Environmental Degradation In Top Economic Complexity Economies, Tomiwa Sunday Adebayo, Mehmet Altuntaş, Sanjar Goyibnazarov, Ephraim Bonah Agyekum, Hossam Zawbaa, Salah Kamel

Articles

The current paper explores the influence of disintegrated energy and economic complexity on CO2 emissions (CO2) in the top economic complexity economies. The model also incorporates other drivers of CO2, such as technological innovation and economic growth. The current research utilizes data stretching from 1993 to 2018. The research employed Westerlund cointegration, fully modified OLS (FMOLS), dynamic OLS (DOLS), and method of moments quantile regression (MMQR) to evaluate these interconnections. The outcomes of the slope heterogeneity and cross-sectional dependence affirmed the use of second-generation techniques. The study confirmed the long-run association between CO2 and the regressors. The results of the …

Heat Transfer And Friction Factor Correlations Development For Double Pass Solar Air Heater Artificially Roughened With Perforated Multi-V Ribs, Varun Pratap Singh, Siddharth Jain, Ashish Karn, Gaurav Dwivedi, Ashwani Kumar, Sachin Mishra, Naveen Kumar Sharma, Hossam Zawbaa, Salah Kamel

Articles

Thermo-hydraulic performance of a Double Pass Parallel Flow Solar Air Heater (DPPFSAH) roughened with perforated multi-V ribs has been studied experimentally in a prior study and the effect of variation in open area ratio and change in relative roughness width has been analysed and reported. The current work builds upon the aforementioned earlier study by discussing in detail the methodology and various steps involved in the development of a correlation for variable parameters with Nusselt number and friction factor for DPPFSAH. The outcomes show that perforations in the multi-V ribs lead to a considerable rise in the Nusselt number, a …

Optimization Based On Movable Damped Wave Algorithm For Design Of Photovoltaic/ Wind/ Diesel/ Biomass/ Battery Hybrid Energy Systems, Mohammed Kharrich, Salah Kamel, Mamdouh Abdel-Akher, Ahmad Eid, Hossam Zawbaa, Jonghoon Kim

Articles

The actual energetic situation has several challenges such as pollution, the rarefaction of fossil fuel and the dangers of nuclear. Renewable sources are proposed as a solution and suggested, such as a cost-effectiveness system. The paper deals with the problem of feeding a domestic load with electricity which should respect the ecologies factors, so this work is a design problem of the hybrid renewable energy systems; PV/biomass, PV/diesel/battery, PV/wind/diesel/battery, and wind/diesel/battery to choose the best one of them which feed the load with the lowest cost. The study’s goal is to design a microgrid system by the minimization of the …

Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Hoda Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado

Articles

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank units (HT), and Fuel Cell (FC) system. A recent optimization algorithm, namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The …

Formation Of Gold Nanoparticle Self-Assembling Films In Various Polymer Matrices For Sers Substrates, Ksenia A. Maleeva, Ilia E. Kaliya, Anton P. Tkach, Anton A. Babaev, Michail Baranov, Kevin Berwick, Tatiana S. Perova, Alexander V. Baranov, Kirill V. Bogdanov

Articles

Surface-enhanced Raman spectroscopy (SERS) is regarded as a versatile tool for studying the composition and structure of matter. This work has studied the preparation of a SERS substrate based on a self-assembling plasmonic nanoparticle film (SPF) in a polymer matrix. Several synthesis parameters for the SPF are investigated, including the size of the particles making up the film and the concentration and type of the self-assembling agent. The result of testing systems with different characteristics is discussed using a model substance (pseudo isocyaniniodide). These models can be useful in the study of biology and chemistry. Research results contain the optimal …

A Hybrid Machine Learning Technique For Feature Optimization In Object-Based Classification Of Debris-Covered Glaciers, Shikha Sharda, Mohit Srivastava, Hemendra Singh Gusain, Naveen Kumar Sharma, Kamaljit Singh Bhatia, Mohit Bajaj, Harsimrat Kaur, Hossam Zawbaa, Salah Kamel

Articles

Object-based features like spectral, topographic, and textural are supportive to determine debris-covered glacier classes. The original feature space includes relevant and irrelevant features. The inclusion of all these features increases the complexity and renders the classifier’s performance. Therefore, feature space optimization is requisite for the classification process. Previous studies have shown a rigorous exercise in manually selecting the best combination of features to define the target class and proven to be a time consuming task. The present study proposed a hybrid feature selection technique to automate the selection of the best suitable features. This study aimed to reduce the classifier’s …

Analysis Of Power Quality Issues Of Different Types Of Household Applications, T.M. Thamizh Thentral, R. Palanisamy, S. Usha, Mohit Bajaj, Hossam Zawbaa, Salah Kamel

Articles

Most of the loads used in our day-to-day life are non-linear in nature. To investigate the performance of various non-linear loads, a laboratory setup on different load combinations such as light, fan and drive system in this work. The unbalance in supply voltages, supply current and frequency, reduction in power factor and total harmonic distortion for current and voltages are monitored through this lab setup and also the results obtained from these systems are discussed in this paper. To check the nature of voltage, current, reactive power and power factor in real-time systems, a turret punch machine incorporated with several …

Optimal Allocation Of Distributed Generation With The Presence Of Photovoltaic And Battery Energy Storage System Using Improved Barnacles Mating Optimizer, Ali Selim, Salah Kamel, Hossam Zawbaa, Baseem Khan, Francisco Jurado

Articles

This paper proposes an improved version of Barnacles mating optimizer (BMO) for solving the optimal allocation problem of distribution generator (DGs) in radial distribution systems (RDSs). BMO is a recent bioinspired optimization algorithm that mimics the intelligence behavior of Barnacles' mating. However, like with any metaheuristic optimization approach, it may face issues such as local optima trapping and low convergence rate. Hence, an improved BMO is adopted based on the quasi oppositional (QOBMO) and the chaos maps theories (CQOBMO). The two improvement methods are applied to increase the convergence performance of the conventional BMO. To prove the efficiency of the …