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A Transfer Function Approach to Modeling of Thermostatically controlled Loads for the Power System Frequency Regulation

A Transfer Function Approach to Modeling of Thermostatically...

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International Conference on Power Energy, Environment and Intelligent control (PEEIC)

作者： Sweta Gupta V S K V Harish Rajneesh Sharma Department of Electrical Engineering Netaji Subhas University of Technology New Delhi Department of Instrumentation and Control Engineering Netaji Subhas University of Technology NewDelhi

To keep the balance between generation and consumption power, frequency regulation plays a significant role. The Thermostatically controlled Loads (TCLs), like heating systems, refrigerators, and air conditioning units can be employed as the regulation tool to address the problem of distribution system fluctuation since these loads can be managed without compromising customer comfort due to their flexible operation. The task of research is to create a suitable controller by regulating the combined TCLs to work with conventional generators to maintain the consistency in the frequency of a single area system and then by using the model of proportional-integral (PI) control method, a transfer function approach must be formulated. The simulated results show that the suggested approach and models are adequate for providing frequency control to enable higher renewable energy penetrations and could be done by analyzing and comparing the system frequency response.

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Smart MPPT Approach using Prominent Metaheuristic Algorithms for Solar PV Panel

Smart MPPT Approach using Prominent Metaheuristic Algorithms...

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2022 IEEE Delhi Section Conference, DELCON 2022

作者： Katyal, Aanchal Pathak, Diwaker Gaur, Prerna Netaji Subhas University of Technology Instrumentation and Control Engineering Department Dwarka Sector-3 New Delhi India Sandip University Electrical Engineering Department Madhubani847235 India

ISBN: (纸本)9781665458832

Under standard climatic circumstances, solar PV systems track maximum power point (MPP) using classic hill-climbing approaches such as perturb and observe (PO) and incremental conductance (INC). Traditional algorithms, suffer difficulties in dynamic and unpredictable environments, such as excessive voltage and current ripple and becoming trapped on local minima. Metaheuristic optimization strategies are used to solve the aforementioned challenge. Therefore, the purpose of this study is to compare several metaheuristic optimization methods for MPP tracking, such as grey wolf optimization (GWO), grasshopper optimization algorithm (GOA), whale optimization algorithm (WAO), and hybrid particle swarm optimization with GWO (PSO-GWO) (MPPT). The performance of algorithms has been observed using the experimental evaluation on standard benchmark functions. Based on the performance of these MPPT algorithms, tracking efficiency is investigated thoroughly for a mathematically modelled solar PV module. Furthermore, the best-performing algorithm's data is sent to an internet of things (IoT) cloud for monitoring and creation of a dataset for smart controller which may learn from every best performing algorithm. © 2022 IEEE.

关键词： Particle swarm optimization (PSO)

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Brain Tumor Detection and Classification by MRI Using Hybrid Techniques with SVM Classifiers

Brain Tumor Detection and Classification by MRI Using Hybrid...

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International Conference on control and Robots (ICCR)

作者： Shiv Sagar Singh Rajneesh Sharma Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

A brain tumor is a rare occurrence where abnormal cells within the brain replicate and grow uncontrollably. This mass of tissue starts to form inside the skull, disrupting the normal functioning of the brain. It is crucial to detect these tumors early on, as they have the potential to develop into cancer. Diagnosis at an early stage is essential, and this is typically achieved through the use of MRI or CT scanned pictures. By detecting the tumor when it is as small as possible, medical professionals can initiate appropriate treatment and management strategies to mitigate any potential risks and complications associated with the tumor's growth. This research primarily focuses on finding and localizing tumor regions in the brain using MRI scans from patients. Pre-processing, segmentation, and classification are the three steps of the suggested approach. The pre-processing stage comprises converting the original image to grayscale and removing any noise that has snuck in. Segmentation process after pre-processing detect the tumor region in the MRI images. Feature extraction gives prominent attribute of the images which is used for classification purpose.

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PID control using Metaheuristics for Binary Distillation Column

PID Control using Metaheuristics for Binary Distillation Col...

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Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON), International Conference on

作者： Vikas Yadav Vritank Yadav Amar Nath Jha Sarthak Tanwar Nishant Singh Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

The purpose of this work is to study and compare various tuning techniques for multi-input multi-output systems for binary distillation column. In this work Wood and Berry’s model is considered for binary distillation column. This model of distillation column separates water and methanol. Classical PID controller is used to control the MIMO system. For tuning the parameters of PID controllers, various metaheuristics algorithms are applied such as Artificial Bee Colony (ABC), Cuckoo Search, Multi-Verse Optimization (MVO), Big Bang Big Crunch (BB-BC), Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA), Bat Algorithm and Particle Swarm Optimization (PSO). The tuning parameters are calculated for all the algorithms by minimizing a common objective function and same number of particles and iterations for all algorithms. A comparative study is conducted on system characteristics which includes settling time, maximum peak overshoot, objective function value and rise time after applying a step input signal for all the algorithms.

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Non-Cascading Structure based Bi-Quadratic Step-Down Converter: Analysis and Design 14

Non-Cascading Structure based Bi-Quadratic Step-Down Convert...

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14th International Conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2023

作者： Kumar, Sunil Rana, K.P.S. Kumar, Vineet Department of Electronics and Communication Engineering J. B. Institute of Technology Uttarakhand Dehradun248197 India Division of Instrumentation and Control Engineering Netaji Subhas University of Technology Sector-3 Dwarka New Delhi110078 India

In the present paper, a step down converter employing combination of Flyback and Forward converters, using a non-cascading scheme, is presented. The voltage conversion ratio in a bi-quadratic converter depends on bi-quadratic power of the duty cycle. Due to this effect, the range of obtainable output voltages has become wider. This means the difference of any two consecutive output realizable voltages becomes narrower than that achieved by using relatively lower power of the duty cycle. Here, for stepping up the output voltage, the outputs of the flyback and forward sub-converters are combined in series with each other. Due to such configuration, a larger output voltage is obtained. A comparison is given to indicate the extension in voltage conversion ratio as the duty cycle is raised to higher power. For validation, a converter of 24 V, 24 W rating is presented. © Grenze Scientific Society, 2023.

关键词： bi-quadratic discontinuous conduction mode intermediate capacitor non-cascading structure switching cycle voltage conversion ratio

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An improved Alternate-Odd-Even (AOE) reconfiguration technique for performance enhancement of SPV arrays

An improved Alternate-Odd-Even (AOE) reconfiguration techniq...

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Power, instrumentation, Energy and control (PIECON), International Conference on

作者： Mirza Tabish Shah Beg K. P. S. Rana Vineet Kumar Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

The paper deals with an Alternate-Odd-Even (AOE) static reconfiguration technique for the power enhancement and performance improvement of the solar photovoltaic (SPV) array under partial shading conditions (PSC). The modules of the chosen 4×4 SPV array are connected electrically in a total-cross-tied (TCT) but repositioned in the SPV array using the proposed AOE reconfiguration technique. The proposed scheme is analyzed and compared with the primary 4×4 SPV array topologies, namely the total-cross-tied (TCT), honeycomb (HC), bridge-link (BL), and series-parallel (SP) for the performance analysis. This technique leads to the redistribution of shade throughout the SPV array. Due to the lower current and voltage outputs, the simple series and parallel configurations have not been considered for this analysis. The proposed technique gives an enhanced performance of the SPV array in terms of higher peak power, lower losses due to shading, improved fill factor and execution ratio, and smooth output characteristics. The proposed technique allows the researchers to design a less complex controller for tracking peak power for the SPV array under PSCs.

关键词： Measurement Fill factor (solar cell) Instruments Voltage Topology Performance analysis

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NARX Model Based Estimation of State of Charge of Lithium-Ion Batteries in Electric Vehicles under Varying Temperature Ranges

NARX Model Based Estimation of State of Charge of Lithium-Io...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Swapnil Tiwari Bhavnesh Kumar Arjun Tyagi Department of Electrical Engineering Netaji Subhas University of Technology Delhi India Department of Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi India

Lithium-ion batteries are a viable option for automotive applications due to their high energy density and low self-discharge rate. The device's longevity and security may be estimated based on its state of charge, which reflects the available energy. A Dynamic Nonlinear Auto-Regressive model with Exogenous Input Neural Network (NARX) Model is proposed and tested to estimate and predict the state of charge (SOC) of the Lithium-Ion Battery, which affects EV performance, range, and safety. In this research, we examine the efficacy of several model-training techniques based on the input characteristics they utilize to build models. The NARX Model with 5 Input Features and Levenberg Marquardt Training (LM) algorithm is selected to train the given model with the least Mean Square Error (MSE) of 1.79E-06 with 606 epoch value.

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MIMO DC-DC Converter-based Photovoltaic Water Pumping System

MIMO DC-DC Converter-based Photovoltaic Water Pumping System

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International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

作者： Abhishek Bharti Aayush Aggarwal Bhavesh Tondwal Sunil Yadav Anuradha Tomar Department of Electrical Engineering Netaji Subhas University of Technology Delhi India Department of Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi India

Globally the problem of diesel prices increasing substantially and the undersupply of electricity due to technicalreasons are major concerns for a water pumping system. If lookover India, diesel supply and price are affected by variousnational and international causes, but the shortage of electricity is linked to coal supplies and lack of funds in DISCOMs. The photovoltaic-based water pumping system (PVWPS) is a viable solution because it is essential to daily requirements and agricultural activities. However, because it uses less installed PV capacity than necessary, such PVWPS have a low return on investment. In order to solve this issue, a multi-input multi-output (MIMO) converter for PVWPS is suggested in this work. These features are included in the proposed MIMO converter: (i) multi-level voltage at multi-output terminals enables connection of diverse types of loads like three-phase AC load, single-phase AC load, and DC loads; (ii) capability to integrate multiple PV inputs and thus minimizing the power loss due to mismatching issues. A model of the MIMO-based PVWPS has been validated through MATLAB simulation and a satisfactory performance has been observed.

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Sensitivity Analysis of Generic PEMFC to Operating Temperature and Load Variations

Sensitivity Analysis of Generic PEMFC to Operating Temperatu...

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Power, instrumentation, Energy and control (PIECON), International Conference on

作者： Kundan Anand Alok Prakash Mittal Bhavnesh Kumar Electrical Engineering Department Netaji Subhas University of Technology Delhi India Instrumentation and Control Engineering Department Netaji Subhas University of Technology Delhi India

This paper investigates the effects of load and operating temperature variation on fuel cell voltage, current, hydrogen consumption and efficiency using a generic PEMFC of 1.26kW capacity. Based on the obtained results, it is clear that the efficiency of the generic PEMFC is highest at a constant operating temperature i.e. 101.86°. The nominal efficiency of generic PEMFC i.e. 50%, can be enhanced to a maximum and minimum of 79% and 69% respectively depending on the load connected to PEMFC. Sensitivity analyzer tool has been used in for sensitivity analysis and MATLAB Simulink has been used for the simulation of generic PEMFC model.

关键词： Temperature sensors Analytical models Sensitivity analysis Software packages Instruments Load management Mathematical models

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An NFNet-Based Approach for Enhanced Bearing Fault Classification Using Vibrational Signal Analysis

An NFNet-Based Approach for Enhanced Bearing Fault Classific...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Vidhi Jain Mayank Dixit Vihaan Misra Geetansh Bhutani Vijander Singh Department of Electrical Engineering Netaji Subhas University of Technology Delhi India Department of Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi India

The present work proposes a novel approach for detecting bearing faults in induction motors using vibrational signals. The proposed method employs a Normalizer-Free ResNet (NFNet) architecture to extract relevant features from 2D image representations of raw vibration data and a classification model to identify the presence of a fault. We convert the vibrational signals into 2D images by applying the Short-Time Fourier Transform (STFT) technique, which offers a time-frequency analysis of the signals. The proposed method improves accuracy over conventional approaches along with reduced computational overhead by using high-performance NFNet architecture for classification. The effectiveness of the proposed method is evaluated on the Case Western Reserve University (CWRU) and Intelligent Maintenance Systems (IMS) datasets of vibration signals from induction motors, experiencing various bearing faults. The results indicate that the suggested framework outperforms the existing methods in terms of accuracy and efficiency, achieving state-of-the-art results. This method can be used for real-time monitoring of induction motors to detect bearing faults and prevent potential equipment failures, making it highly useful for industrial applications.

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