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2nd International Conference on Signals, machines, and Automation, SIGMA 2022

作者： Bhardwaj, Vivek Sharma, Rajneesh Shikhola, Tushar Department of Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi India Delhi Metro Rail Corporation Limited Delhi India

ISBN: (纸本)9789819909681

In a smart grid, photovoltaic system integration is becoming crucially influential. However, the system faces nonlinear characteristics, which causes difficulty in obtaining maximum power. To obtain maximum power from the PV system, numerous methods are employed to track the maximum power point (MPP), and these methods are called maximum power point tracking methods. The proposed work contains a comparative analysis between two conventional algorithms, namely, perturb and observe (P&O) and incremental conductance (INC), and an intelligent algorithm fuzzy logic control (FLC), under dynamic environmental conditions. For performance analysis, simulation is employed on MATLAB/SIMULINK software, where FLC showed a superior result in tracking MPP when compared with both conventional techniques INC and P&O. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy logic

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Improvement in Voltage Profile of Grid Connected Fuel Cell 2

Improvement in Voltage Profile of Grid Connected Fuel Cell

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2nd International Conference on Next Generation Intelligent Systems, ICNGIS 2022

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

ISBN: (纸本)9781665467926

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). © 2022 IEEE.

关键词： Particle swarm optimization (PSO)

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A Fuzzy-Based Buck-Boost Photovoltaic Inverter for Voltage Stabilization During Mismatched Environmental Conditions 2nd

A Fuzzy-Based Buck-Boost Photovoltaic Inverter for Voltage S...

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2nd Electric Power and Renewable Energy Conference, EPREC 2021

作者： Bhardwaj, Varun Gaur, Prerna Instrumentation and Control Engineering Department Netaji Subhas University of Technology New Delhi India

ISBN: (纸本)9789811692383

This paper proposed a buck-boost operating inverter with two photovoltaic arrays generating power at different levels of voltages because of shading conditions. The introduced buck-boost inverter with two series-connected photovoltaic arrays is interconnected to a single-phase grid with maximum power injection. The inverter can work in both modes, i.e., buck mode and boost mode depending on the voltage amplitude produced by the photovoltaic arrays. This makes the inverter draw the largest power from the photovoltaic arrays during different solar irradiation conditions on the panels. The inverter is controlled by a feedback loop control system with a reduction in leakage currents in the photovoltaic arrays. The control structure is further updated with the FIS module for better stability of the inverter. The comparison of conventional and FIS control structures is represented using MATLAB/Simulink software. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Solar cells

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Drug Scheduling in Chemotherapeutic Treatment using Multi-objective Optimization based 2DOF PID Cascade control Scheme 2

Drug Scheduling in Chemotherapeutic Treatment using Multi-ob...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Mondal, Disha Rani, Asha Singh, Vijander Netaji Subhas University of Technology Department of Instrumentation and Control Engineering New Delhi India

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

This study aims to present the drug optimization in the chemotherapeutic treatment of cancer for the eradication of cancerous cells with minimum toxic effect on the patient's body. The drug scheduling has been studied for a period of 84 days. A cascade control mechanism using two 2DOF PID is employed to regulate the optimal concentration of drug and toxicity level of the body while killing the maximum possible cancerous cells. Multi-objective optimization techniques like MOPSO., NSGA-2., MOGA are used to optimize the controllers. A comparative analysis of NSGA-2., MOGA and MOPSO tuned 2DOF PID and its single degree of freedom counterpart is carried out. It is observed that NSGA-2 2DOF PID gives the best possible results in terms of cancerous cells remaining after the treatment and the peak toxicity level of the body. © 2022 IEEE.

关键词： Three term control systems

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Structural Design & Energy Balance Conceptualization for PV Based Protective Environment controlled Farming

Structural Design & Energy Balance Conceptualization for PV ...

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2022 IEEE International Conference on "Power Electronics, Smart Grid, and Renewable Energy", PESGRE 2022

作者： Tomar, Anuradha Department of Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi 110078 India

ISBN: (纸本)9781665448376

Protective environment-controlled farming is a good alternative of conventional or open land farming as it reduces farmer's dependencies on external atmospheric conditions and allows to grow the crop as per their choice. However, for farmers living in remote/isolated regions availability of electricity is a major concern in order to implement such protective environment-controlled farming systems in absence/non-connectivity with the National grid. Further, it becomes more difficult for the farmers with farms in hilly regions. To address these issues, in this paper structural design and energy balance conceptualization of a photovoltaic (PV) energy based protective environment-controlled farming system is presented. The proposed PV based protective environment-controlled farming (PV_PECF) system have added advantages like it is movable/transportable and thus is suitable for hilly regions too. Further, it has PV as a source of energy for its operational power demands and thus no dependency on utility grid. The scope of this paper is limited towards design and conceptualization of energy in PV-PECF system. Further, other operational aspects and obtainable results would be presented as a part of future work. © 2022 IEEE

关键词： Structural design

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Probabilistic routing protocol with firefly particle swarm optimisation for delay tolerant networks enhanced with chaos theory

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International Journal of Innovative Computing and Applications 2021年第2-3期12卷 123-133页

作者： Banyal, Siddhant Bhardwaj, Kartik Krishna Sharma, Deepak Kumar Department of Instrumentation and Control Netaji Subhas University of Technology New Delhi India Netaji Subhas Institute of Technology India Department of Information Technology Netaji Subhas University of Technology New Delhi India

In this paper, we propose a proactive routing paradigm for delay tolerant networks (DTN) using probabilistic routing implemented via firefly particle swarm optimisation and optimised by chaos maps. DTN is a specific class of networks where there is absence of an end to end connectivity among nodes and are characterised by long or variable delays, asymmetric data rates and high error rates. The routing scheme considers the constrained environment of DTN nodes and implements a meta-heuristic paradigm to facilitate data transfer. The chaos maps further enhance the probabilistic routing parameters controlling brightness and ageing by randomising them. The protocol is implemented on ONE simulator and its performance is compared with traditional DTN routing schemes across delivery probability, average latency, overhead ratio and buffer utilisation. The simulation results show that our proposed protocol performs better than its contemporary ant PRoPHET protocol across the various performance metrics. © 2021 Inderscience Enterprises Ltd.

关键词： Delay tolerant networks

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EV Integrated PV Water Pumping System with Priority-Based control 3

EV Integrated PV Water Pumping System with Priority-Based Co...

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3rd IEEE International Conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

作者： Tomar, Anuradha Netaji Suhas University of Technology Department of Instrumentation & Control Engineering Delhi India

ISBN: (纸本)9798350319972

Solar photovoltaic-based water pumping system (PVWPS) is emerging as a promising solution for addressing the water needs in rural/remote regions. However, there is a need to increase the utilization of installed PV capacity in such PVWPS as water pumping is required only a few hours a week. To address this issue, in this paper an electric vehicle integrable PVWPS with priority-based control is proposed. It will enable alternative utilization of installed PV capacity and thus would result in improved return on investment. The proposed system is validated through MATLAB simulation. The satisfactory performance of the proposed system has been observed under various operating scenarios. The proposed PVWPS with optimized configuration and design parameters could be further explored in future. © 2023 IEEE.

关键词： Investments

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Optimization of environmental impact inclusive cost for sustainable distributed energy resources in distribution system

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Neural Computing and Applications 2024年 1-13页

作者： Firdous, Aaquib Tyagi, Arjun Tyagi, V.V. Kumar, Bhavnesh Centre for Energy & amp Environment Malaviya National Institute of Technology Rajasthan Jaipur302017 India Department of Electrical Engineering Faculty of Technology University of Delhi Delhi110007 India School of Energy Management Shri Mata Vaishno Devi University Jammu & Kashmir Katra182320 India Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi110078 India

The proliferation of renewable energy (RE) and increasing electrical demand stress the existing generation and transmission systems. Moreover, due to environmental concerns, the proper utilization of small-scale renewable distributed energy resources (DERs) has become essential. DERs can play a pivotal role in evolving grids by reducing emissions and improving energy delivery by providing system services like voltage maintenance. Optimal sizing and sitting of these DERs into the distribution system promise various benefits and a viable solution to overcome the limitations of large transmission and conventional generation systems and provide better voltage maintenance. Besides, utilizing realistic data generation from working plants and varying load patterns allows for better insights into power system operations under growing RE. This work presents a profit-based optimal sizing and sitting of DERs into the distribution system while considering environmental costs. An improved Harmony Search algorithm has been applied to optimize the proposed cost-based objective function, which consists of various costs in generating distributed energy while simultaneously considering the environmental expenses incurred due to the release of different pollutant gasses. Also, the generation data of working solar and wind plants and realistic varying loads across seasons, weekdays, and weekend days have been considered to explore real operating scenarios. Efficacy has been verified from the optimization results that illustrate its capability to allocate DERs in conjunction with reduced costs and emissions, facilitating optimal system operations. The algorithm has been tested for two standard distribution systems focusing on reducing overall generation costs, social costs labelled due to emissions, improvement in voltage profile, and reduction in overall losses of the system. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Distributed energy

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Comparative Analysis Between Bi-LSTM and Uni-LSTM Algorithms for Wind Speed Estimation 7

Comparative Analysis Between Bi-LSTM and Uni-LSTM Algorithms...

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7th International Conference on Computer Applications in Electrical engineering-Recent Advances, CERA 2023

作者： Singh, Sarvendra Kumar Jha, Shyama Kant Gupta, Rahul Netaji Subhas University of Technology Instrumentation and Control Engineering New Delhi India G L Bajaj Institute of Technology and Management Electrical and Electronics Engineering Greater Noida India

ISBN: (纸本)9798350305005

The integration of sustainable energy sources into the conventional power grid depends on accurate wind speed estimates since it affects grid operations, stability, and overall planning. Owing to its advantages for the environment and ability to lessen dependency on fossil fuels, wind power is highly valued. Accurate wind speed prediction enables grid managers to estimate energy generation and make in-the-moment changes to ensure a steady and dependable power supply. It is becoming increasingly important to comprehend and utilize wind power's potential as the globe moves toward a more sustainable energy future. The use of deep learning algorithms like Unilateral Long Short-Term Memory (Uni-LSTM), Bilateral Long Short-Term Memory (Bi-LSTM), and Gated Recurrent Unit (GRU) networks is one of the novel ways being investigated in research to improve wind speed forecasts. These algorithms examine past wind speed data and forecast future wind speeds by utilizing their innate memory and flexibility. This study focuses on the Jaisalmer area in Rajasthan, India, where the energy mix may be considerably influenced by wind power. To ensure the data is properly scaled for input into the deep learning models, a preprocessing step is conducted using the Min-Max scaler approach on a dataset downloaded from the NASA website. The analysis shows that the GRU model outperforms the Uni-LSTM and Bi-LSTM models. The 'RELU' activation function is used in these models. The model's performance is analyzed by comparing MAE and RMSE error values with R2 accuracy values. The GRU model gives rich R2 value performances better than other models. © 2023 IEEE.

关键词： Long short-term memory

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Harnessing the Power of Advanced Deep Learning Algorithms for Foretelling Wind Speed

Harnessing the Power of Advanced Deep Learning Algorithms fo...

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Silchar Subsection Conference (SILCON), IEEE

作者： Sarvendra Kumar Singh Shyama Kant Jha Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

ISBN: (数字)9798331540821

ISBN: (纸本)9798331540838

Wind speed estimation is crucial for the stability and long-term planning of the electrical grid. Wind power has positive environmental effects and allows grid operators to anticipate energy generation trends and make real-time adjustments. This study investigates four deep learning algorithms for predicting wind speed: K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) networks. The LSTM model shows the best R2 value and the lowest RMSE value, demonstrating its better predictive ability. These models capture complex temporal correlations in wind speed data, demonstrating their utility as reliable time-series analysis tools. The recognition of LSTM networks as the best wind speed predictors paves the way for cutting-edge forecasting techniques and a robust energy infrastructure that can meet the demands of a changing energy landscape.

关键词： Deep learning Wind speed Time series analysis Nearest neighbor methods Wind power generation Prediction algorithms Stability analysis Convolutional neural networks Reliability Long short term memory

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