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

作者： Manisha Kumari Chandan Kumar Smriti Srivastava Department of Electrical Engineering Netaji Subhas University of Technology New Delhi India Department of Electrical Engineering Indian Institute of Technology Kanpur Kanpur India Department of Control and Instrumentation Engineering Netaji Subhas University of Technology New Delhi India

For grid-connected photovoltaic (PV) systems, accurate solar irradiance forecasting is crucial, especially in cases of intermittent environmental conditions, in order to ensure grid operation, scheduling, and grid energy management. Solar irradiance, temperature, and other meteorological factors significantly influence PV generation and also make it intermittent in nature. Time series analysis provides an efficient way to map temporal patterns, like hourly, monthly, yearly, and seasonal variations, and within solar irradiance data. In this paper, time series forecasting of 24hourly future observations of global horizontal irradiance (GHI) is done using a multilayer perceptron (MLP) of deep learning framework. Different hyperparameters like hidden layers, hidden units of each layer, activation function, optimizer, and lag observations/steps are tuned to develop the best model that fits the GHI historical data. Further dropout regularization is used to avoid overfitting the model. The model is validated using validation data that the model has never seen before. RMSE, MSE, MAE, and NRMSE errors, aiming at minimizing forecasting errors on test data, are used to select the optimal value of hyperparameters.

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An IoT based Real-Time detection and Notification System for an Economical Solar MPPT Model 1

An IoT based Real-Time detection and Notification System for...

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1st International Conference on Industrial Electronics Research and Applications, ICIERA 2021

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

ISBN: (纸本)9781665435420

The intelligent solar photovoltaic (SPV) system, the reduced size and flexible applicability is highly required for the areas where per capita income is lower and cost becomes a crucial issue. Therefore, in this paper, an easier model of the internet of things (IoT) based SPV system is designed and proposed along with the application of basic maximum power point tracking (MPPT) methods. Consequently, a better time-response characteristics, accuracy, efficiency and economical value are obtained. To achieve this, firstly, a single-diode SPV system with boost converter topology is used that was previously designed in literature. Further, easy-structured perturb observe (PO) and incremental conductance (IC) MPPT methods are analyzed using a low-cost Arduino Uno board in Proteus software, where, these MPPT algorithms are executed under the convincing profiles of irradiance. Above all, the obtained PV power, PV voltage, humidity, air quality, rain, obstacle etc. are monitored using the particular sensors and displayed on the internet with the exact coordinates of the location. Based on the data sensed from the various sensors, an alert system via email is also developed that ensures the desired outcome along with reduced manpower for the system studied. © 2021 IEEE.

关键词： Internet of things

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A Novel PID-AW based MPPT technique for SPV system 4

A Novel PID-AW based MPPT technique for SPV system

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4th International Conference on Recent Developments in control, Automation and Power engineering, RDCAPE 2021

作者： Goswami, Yagyadatta Rana, K.P.S. Kumar, Vineet University Of Delhi Department Of Instrumentation And Control Engineering Netaji Subhas Institute Of Technology New Delhi India Department Of Instrumentation And Control Engineering New Delhi India

ISBN: (纸本)9781665414296

Various of MPPT (maximum power point tracking) techniques have been used to draw the maximum power output from solar photovoltaic (SPV) systems. Two popular classical MPPT techniques e.g. perturb and observe (PO) and incremental conductance (IC) have applied for best optimized results. Shortcoming of PO and IC is of oscillations around the maximum power point (MPP). A proportional integral derivative -based dp/dv with Anti-windup (PID-AW) controller is proposed to counter the oscillations around MPP. The proposed technique is based on the classical model of the PID controller that leads to integral saturation. PID controller requires anti-windup (AW) that limit the controller's integral action to avoid the undesirable windup phenomenon. The performance parameters of the PID-AW controller are ripples in power output, offset and ITAE under standard test conditions (STC). The proposed technique is used to strengthen the capability of classical PID, PO and IC algorithm. Presented MATLAB®/Simulink® based simulations proves the superiority of PID-AW MPPT technique in comparison to the classical PID, conventional PO and IC algorithm. © 2021 IEEE.

关键词： controllers

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System Dynamic Approach In Smart City For Optimal Energy Consumpsion

System Dynamic Approach In Smart City For Optimal Energy Con...

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Innovative Practices in technology and Management (ICIPTM), International Conference on

作者： Navita Mahajan Vandit Kapoor Sneha Mukhopadhyay Pritish Mahajan Amity International Business School Amity University Noida Uttar Pradesh India Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

The world’s non-renewable energy sources are finite, and Chandigarh is not an exception. Its energy sources for producing electricity are limited. It also lacks a power plant of its own. Finding alternate sources of electricity supply is vital since the population is growing and so is the need for electricity. As demonstrated in this study, Chandigarh’s population growth will increase the city’s demand for electricity. Even if the government of Chandigarh increases the capacity of the electricity supply, obtaining the necessary supply will be expensive, the plan is not sustainable. Therefore, Chandigarh is integrating renewable energy sources for its electrical supply in accordance with the global trend towards greater use of renewable energy sources. In addition to projecting Chandigarh’s population and electricity consumption for 15 years, until the year 2035, this study also looks at viable alternatives to electricity production in the city.

关键词： Renewable energy sources Accuracy System dynamics Electricity Sociology Government Machine learning

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Enhancing transparency in global horizontal irradiance estimation with tree based machine learning algorithms and Shapley additive explanations framework

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International Journal of Ambient Energy 2025年第1期46卷

作者： Gupta, Rahul Ganvir, Chaitanya Jha, S.K. Singh, Rahul Baghel, Raj Kumar Department of Electrical and Electronics Engineering G L Bajaj Institute of Technology and Management Greater Noida India Department of Instrumentation and Control Engineering Netaji Subhas University of Technology Dwarka India Department of Electrical Engineering Indian Institute of Technology Ropar Rupnagar India

The estimation of global horizontal irradiance (GHI) is crucial for assessing solar energy potential, especially for investment purposes in specific regions. This study employs two feature selection techniques such as recursive feature elimination (RFE) and least absolute shrinkage and selection operator (LASSO) to identify key variables from two datasets, which are then used to train four machine learning (ML) models such as Decision Tree (DT), Random Forest (RF), Extreme Gradient Boost (XGB), and Extra Trees (ET) regressors. The performance of these models is evaluated using three statistical metrics such as mean absolute error (MAE), root mean squared error (RMSE), and R-squared (R2). The results show that the ET regressor, when combined with LASSO, achieves the best predictive performance, with an MAE of 1.36 W/m² and an RMSE of 2.46 W/m2. The study further employs Shapley Additive Explanations (SHAP) to interpret the model, revealing that parameters like Diffuse Horizontal Irradiance, Solar Zenith Angle, and Direct Normal Irradiance significantly impact GHI prediction accuracy. The combination of feature selection, advanced ML models, and SHAP analysis offers a comprehensive and transparent framework for solar energy resource assessment, addressing the need for accuracy and interpretability in GHI estimation. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Solar irradiance

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Synergizing Renewable Distributed Generation Allocation with Demand Response for Enhanced Energy Efficiency

Synergizing Renewable Distributed Generation Allocation with...

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International Conference on control Computing Communication & Materials (ICCCCM)

作者： Praveen Kumar Anil Kumar Yadav Shyama Kant Jha Vivek Saxena Department of Electrical Enginneering Netaji Subhas University of Technology New Delhi India ABES Engineering College Ghaziabad India Department of Instrumentation & Control Engineering Dr. B.R. Ambedkar National Institute of Technology Jalandhar India Department of Instrumentation & Control Engineering Netaji Subhas University of Technology New Delhi India Department of Electrical & Electronics Enginneering ABES Engineering College Ghaziabad India

ISBN: (数字)9798350371680

ISBN: (纸本)9798350371697

The integration of distributed generation (DG) technology into distribution networks (DN) has garnered significant attention in recent years due to its potential to enhance system efficiency, reduce carbon emissions, and improve overall power system reliability. However, the complex interplay of factors such as load demand, renewable energy sources, and energy storage systems (ESS) complicates the determination of optimal DG system placement within DN. Demand response (DR) programs offer a promising avenue for improving DG system efficiency by enabling customers to adjust their energy consumption during peak hours, thereby alleviating strain on the grid. Recognizing the potential synergy between DR and solar photovoltaic (PV) systems, this study investigates their combined impact on DN efficiency. Utilizing a particle swarm optimization (PSO) method, this research addresses the challenge of maximizing DG distribution while coordinating with DR initiatives. The iterative nature of these optimizations ensures a comprehensive approach to system enhancement. Application of this methodology to the IEEE 33 bus system demonstrates significant improvements in power quality metrics. The proposed methodology not only enhances system efficiency and reliability but also effectively coordinates DG placement with DR strategies. The findings underscore the potential of DG and DR integration in addressing contemporary challenges faced by distribution networks, offering a pathway towards a more resilient and environmentally sustainable electricity grid.

关键词： Renewable energy sources Energy consumption Power quality Distribution networks Demand response Distributed power generation Power system reliability Planning Reliability Optimization

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Speed control of Hybrid Electric Vehicle using cascade control of Fractional order PI and PD controllers tuned by PSO 18

Speed Control of Hybrid Electric Vehicle using cascade contr...

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18th IEEE India Council International Conference, INDICON 2021

作者： Upadhyaya, Ashruti Gaur, Prerna Indian Insitute of Technology Electronic and Electrical Engineering Guwahati India Netaji Subhas University of Technology Instrumentation and Control Engineering New Delhi India

ISBN: (纸本)9781665441759

A nonlinear hybrid electric vehicle (HEV), taken as a challenge due to its uncertainty in speed control, is controlled using cascade control loop of FO-PI (Fractional order PI) and FO-PD (Fractional order PD) controllers in this research. HEVs have a combination of mechanical and electrical subsystems arranged in cascade configuration. Mechanical subsystem consists of dynamics of vehicles and electrical subsystem comprises of Electronic Throttle control System (ETCS). The other controllers evaluated are fractional order PID (FOPID), classical PID and PI cascaded with PD (PI-PD). The gains of the proposed and other controllers are tuned by Particle Swarm optimisation algorithm (PSO). Performance is examined for tracking of speed profile trajectory, rejection of disturbance phenomenon. Different performance parameters such as IAE (Integral of Absolute Error), OS (Overshoot), Rise time, Settling time are measured for examining behaviour of different controllers designed for controlling the speed of HEVs. The IAE of FOPI-FOPD tuned by PSO is 17.077 is least amongst the IAE of FOPID, PI-PD, PID tuned by PSO with values 22.771, 25.250, 29.134 respectively for set point tracking profile. The results show that FOPI-FOPD controller tuned by PSO has superior performance as compared to other competitive controllers in controlling the speed of HEVs. © 2021 IEEE.

关键词： controllers

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Optimization Algorithm-Based Artificial Neural Network control of Nonlinear Systems 3rd

Optimization Algorithm-Based Artificial Neural Network Contr...

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3rd International Conference on Innovative Computing and Communication, ICICC 2020

作者： Srivastava, Vishal Srivastava, Smriti Department of Instrumentation and Control Engineering Netaji Subhas Institute of Technology Sector-3 DwarkaNew Delhi India

ISBN: (纸本)9789811551123

For control of various nonlinear systems, many controllers have been developed over a period of time. Most of the plants are either nonlinear or their parameters vary with time. PID controller has limitations as it is unable to handle complex nonlinearities as well as parameter variations in plants. Therefore, a suitable controller needs to be designed for these plants. Artificial neural network (ANN) has capability to handle these complex issues. In this paper, teacher learning-based algorithm (TLBO) has been used with ANN which optimizes the controller parameters and adapts the nonlinearities present in the plants. To analyze the performance, TLBO with ANN controller is used on various systems, i.e., inverted pendulum and a plant discussed in [1]. The simulation results show the plant output versus mean square error (MSE). © 2021, Springer Nature Singapore Pte Ltd.

关键词： Neural networks

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Self-Balanced Twenty Five Level Switched Capacitor Multilevel Inverter with Reduced Switch Count and Voltage Boosting Capability

Self-Balanced Twenty Five Level Switched Capacitor Multileve...

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作者： Murshid, Shadab Tayyab, Mohammad Sarwar, Adil Tariq, Mohd Al-Durra, Ahmed Tomar, Anuradha Nanyang Technological University Singapore Department of Electrical Engineering ZHCET Aligarh Muslim University Aligarh India Department of Electrical and Computer Engineering Khalifa University of Science Technology Abu Dhabi United Arab Emirates Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi India

Multilevel inverters (MLI) are gaining wider popularity owing to their increasing power handling capability and improving power quality output. With an inclining trend towards renewable energy utilization, they find a vital application in wind and solar power generation systems. This article proposes a new multilevel dc-ac inverter. The proposed MLI produces a twenty five level output and offers an inherent capacitor self-balancing capability. The inherent self-balancing eliminates the requirement of auxiliary sensor circuit or capacitors voltage balancing algorithms. Dual asymmetric voltage sources and switched capacitors along with their proper charging/discharging pattern are utilized for the generation of output levels. A voltage gain of 2 and a total standing voltage (TSV) of 10 is achieved though the proposed inverter. In order to realize the merit of the proposed MLI over recently developed topologies, a comparative analysis in terms of system components such as numbers of power electronic switches, gate driver circuits, diodes, and capacitors as well as system parameters such as voltage gain, TSV and power loss is presented. The proposed MLI is developed in the laboratory and is controlled through the digital signal processor TMS320F28379D using nearest level control technique. The experimental results are acquired for different loads and under varying modulation index to validate the feasibility of the proposed inverter. © 1972-2012 IEEE.

关键词： Solar power generation

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Improvement in Voltage Profile of Grid Connected Fuel Cell

Improvement in Voltage Profile of Grid Connected Fuel Cell

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International Conference on Next Generation Intelligent Systems (ICNGIS)

作者： Purvaa Saxena S.K. Jha Instrumentation and Control Department Netaji Subhas University of Technology Delhi India

In this work, an electrical network connected to Proton-exchange membrane fuel cell (PEMFC) is considered. The voltage profile of the system is enhanced by connecting the fuel cell with the boost converter and an inverter. The traditional PID controller does not to responds to the non-linearities of the system. Hence, PID controller is dynamically tuned by the Improved Squirrel Search Algorithm (ISSA). The whole architecture is developed in SIMULINK. For testing the effectiveness of the proposed model, the transients are given to the system for short duration and the results are then compared. It is observed that the proposed model has improved voltage response during transients along with reduced harmonics. The analysis for the power quality enhancement is confirmed through Total Harmonic Distortion (THD).

关键词： Total harmonic distortion Heuristic algorithms Power quality Fuel cells Voltage Harmonic analysis Transient analysis

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