Department of Electrical and Electronics Engineering

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Author: search.filters.author.Mishra, PuneetHas files: No

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Now showing 1 - 10 of 54
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    Fuzzy-based fractional order control for effective frequency regulation
    (IEEE, 2025-05) Mishra, Puneet; Mathur, Hitesh Datt
    The objective of the presented work is to investigate the application of a fuzzy fractional order PID (fuzzy FOPID) controller in a two-area tied hybrid power system. This consists of integrating thermoelectric power plants that have been heated again, together with unpredictable renewable energy sources, inside a single control region. Additionally, there are hydropower plants in another control area. Renewable energy sources encompass wind power, solar thermal energy, and fuel cells. To simulate a realistic situation, the thermal and hydro systems are equipped with a generation rate constraint (GRC) and a governor dead band (GDB). Furthermore, the turbine incorporates boiler dynamics (BD), and both control regions experience a stochastic variation in load. Extensive simulations have shown that the Fuzzy FOPID control structure has superior performance compared to FOPID and PID controllers, as measured by the performance index. Robustness may be demonstrated by doing sensitivity analysis on system parameters, including the speed control parameter, GDB, GRC, and random load perturbation, for substantial changes. Moreover, the system’s performance has been assessed, considering the delay in communication, which significantly degrades the performance. Extensive simulations have shown that the fuzzy-based FOPID controller surpasses other controllers in terms of resilience and accuracy. Therefore, it may be considered a practical solution to the load frequency control problem.
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    Optimal scheduling of mobile and stationary electric vehicle charging stations in a distribution system with stochastic loading
    (Elsevier, 2025-07) Mishra, Puneet; Mathur, Hitesh Datt
    Due to surge in the use of electric vehicles (EVs), electric vehicle charging station (EVCS) load modelling emerges to be vital in designing or revamping existing EV charging facilities. The present work addresses this optimal scheduling problem by proposing a novel probabilistic model to predict the optimum demand at a charging station for fixed time duration and thereafter for variable durations using dynamic fault tree analysis considering the charging urgency of the vehicles. To cater to the increased load demand due to enhanced EV penetration and to mitigate its associated technical challenges, incorporation of Mobile Charging Station (MCS) is proposed in the present work. However, placement of MCS poses a significant challenge of their optimal siting and scheduling. This has been achieved by identifying priority areas for their positioning from a proposed Mobile Charging Station Allocation Indicator (MCSAI) computed based on escalated requirement at an EVCS. Extensive investigations have been conducted for placement of combination of fixed and mobile EVCS in a standard IEEE 33 and 85 bus distribution system and it is shown that the resultant hybrid system leads to a significant improvement of more than 5 %, 15 % and 25, 30 % respectively as measured by indices such as line loss reduction index voltage profile improvement index.
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    Performance assessment of a distribution system with electric vehicle charging station and forecasted loads
    (Springer, 2025-05) Mishra, Puneet; Mathur, Hitesh Datt
    A trend towards green transportation causes huge escalation in the use of electric vehicles. Therefore, proper evaluation of the burden on a charging changing station is immensely essential. This work propounds a novel technique based on probabilistic estimation of the total demand at an Electric Vehicle Charging Station (EVCS) for certain fixed hourly durations of time and then on the basis of vehicle categorisation dependent on the exigency of the vehicles. Based on the probabilistic estimation of EVCS loads, an optimum mix of charging stations is positioned strategically in an IEEE 33 bus distribution system designed on a methodology based on apparent power loss. The system with EVCS positioned at the optimal points is analysed with the help of two assessment indicators, namely line loss reduction index and voltage profile improvement index. The performance of the aforesaid system is strengthened by the addition of distributed generators at the aptly sited locations.
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    Performance Evaluation of Metaheuristic Algorithms for Optimal Exoskeleton Controller Design
    (Springer, 2022-05) Mishra, Puneet
    Exoskeletons are used for a wide variety of applications, with one of the most important being assistance and rehabilitation for those who have lost control of their limbs. Exoskeleton controllers must be robust and show stable behavior under varied conditions. Intelligent control schemes prove to be a good option for achieving this. However, there are no standard practices in literature to tune adaptive intelligent controllers which guarantee their performance. Keeping this in mind, an attempt has been made in this work to optimize the parameters of an adaptive fuzzy control scheme applied to a dynamic exoskeleton focusing on the knee and ankle joints. Three different algorithms, namely—Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimizer (GWO), and Moth-Flame Optimization (MFO) are used for this purpose. The performance of the tuned controllers has been investigated and thorough comparative studies have been drawn. Based on the integral time of absolute error values (ITAE), it is concluded that GWO shows an overall better performance over the other two.
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    Probabilistic Modeling and Outage Analysis for Smart Microgrid and Electric Vehicles Ecosystem
    (IEEE, 2023) Bitragunta, Sainath; Mishra, Puneet
    In this work, we propose a simple yet novel prob-abilistic model for a renewable smart-grid and electric vehi-cle (EV) ecosystem supported by cellular vehicle-to-grid (C- V2G) infrastructure. Our stochastic model accounts for two key energy components modeled as random variables: the energy available from renewable sources and energy consumed by the EV. We define novel performance measures, desire probability, and threshold for the ratio of two energy components for this stochastic model. For it, we develop an insightful analysis that includes mathematical derivations for obtaining a single integral expression for the desired probability for a stable green grid- EV ecosystem operation. We present various numerical plots with varying model parameters and obtain useful insights to understand the model and suggest the optimum threshold for stable and safe operation. The model and analysis we develop are useful as the theoretical benchmark for other learning-based practical approaches.
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    Unveiling the Sensing Capabilities of Multi-Walled Carbon Nanotubes for Urea Detection through Optical and Electrical Characterization
    (IEEE, 2024) Mishra, Puneet
    Detecting the nitrogen content present in urea is of utmost importance in determining its suitability for agricultural applications. This specific research paper explores a method that employs Multi-Walled Carbon Nanotubes (MWCNT) as the sensing material. The study revealed promising results, showcasing that the MWCNT-based sensor achieved its peak sensitivity, detecting urea concentrations with good precision. Specifically, it demonstrated a maximum sensitivity of 0.49% at a urea concentration of 10 mM. Moreover, the sensor exhibited impressive sensitivity, with a rapid response time of 46 seconds and an efficient recovery time of just above 7 minutes. The sensing mechanism was initially confirmed through analytical techniques such as Fourier Transform Infrared Spectroscopy (FTIR). By observing the change in intensity of the CO2 signal upon exposure to urea solution, the involvement of oxygen ions in the sensing process was validated. Furthermore, the confirmation of this mechanism was reinforced through detailed electrical characterization. Overall, the development of this sensing film represents a significant advancement in the field of urea detection as it offers a cost-effective solution that is non-enzymatic in nature, yet possesses good sensitivity. This breakthrough has the potential to greatly benefit agricultural practices by providing farmers and researchers with a reliable tool for assessing the quality of urea fertilizers efficiently and accurately.
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    Novel optimal energy management with demand response for a real-time community microgrid
    (IEEE, 2023) Mathur, Hitesh Datt; Mishra, Puneet
    Due to the uncertain nature of renewable sources (RS), microgrids (MGs) are becoming inefficient and unreliable. Further, battery energy storage systems (BESS) ensure uninterrupted power supply in MGs. However, integrating BESS can increase MG's operating costs and make the system uneconomical. This paper proposes an optimal energy management (OEM) algorithm that can minimize MG's operating and maintenance (O&M) cost and improve the system's efficiency. In addition, to improve the system's reliability, the demand response (DR) strategy is integrated with the proposed OEM, i.e., OEM-DR. This strategy focuses on maximizing the utilization of RS and minimizing the dependency of MG on a grid, along with fulfilling the objectives of OEM. The formulated objective function is solved using linear programming (LP). In order to evaluate the efficacy of these strategies, the analysis is performed with the real-time data of three seasons, i.e., summer, winter, and rainy. The real-time data is obtained by the MG installed at the commercial building of BITS, Pilani, India. It is found from the results that with the OEM-DR, a significant decrement in operating cost, as well as power imported from the grid, is achieved.
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    An improved nonlinear deloading approach based on the fuzzy controller for wind turbine generators in an islanded microgrid
    (Elsevier, 2023-11) Mishra, Puneet; Mathur, Hitesh Datt
    The wind turbine generators (WTG’s) incapability of primary frequency support during system contingencies due to its decoupled nature from the system frequency causes profound integration and stability issues. The present study focuses on resolving such issues by enabling the WTGs to participate in long-term frequency support under the derated operation of WTGs. The deloading operation of WTGs can provide a specific reserve power margin by reducing its rotor speed, which can be utilized during system contingencies. In literature, linear and quadratic deloading techniques have been proposed but these fail to replicate the nonlinear characteristics of the WTG accurately, thereby making deloading ineffective. To effectively implement the deloading, this work uses a more-accurate higher-order Newton’s interpolation polynomial (HNIP), to cope with the highly nonlinear characteristics of WTG. The proposed deloading approach is also augmented with a fuzzy-based intelligent supplementary control structure to handle the inherent and incorporated nonlinearities in WTG. The microgrid system, consisting of a conventional energy source with WTG, has been considered as system under investigation. The integral time absolute error for step wind profile and variable speed wind profile was found to be improved by 97.65% and 97.29%, respectively, with the proposed novel deloading technique with fuzzy-PID compared to PID. Further, to ensure the implementation viability of the proposed control scheme, real-time validation of the same is carried out on OPAL-RT 4510, having a Xilinx Kintex-7 FPGA board. It was found that for all the scenarios considered for real-time digital simulation purposes, the results unerringly matched with MATLAB/Simulink.
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    Chemiresistive urea sensor based on a composite film of Activated charcoal and Zinc Oxide
    (IEEE, 2024) Mishra, Puneet; Gupta, Navneet; Panwar, Jitendra; Mathur, Hitesh Datt
    Detection of nitrogen content in the form of urea is essential as it confirms its fertility for agricultural practices. Herein, a report on a simple microwave decomposition method for the synthesis of hybrid nanomaterial (Zinc Oxide and Activated Charcoal) that shows a maximum sensitivity of ~87% at 100mM urea concentration with response time and recovery time of 6 min and 80 min, respectively. The urea sensing mechanism with pre-adsorbed oxygen ions on the surface of the composite was verified by measuring the change in intensity of CO2 signal upon exposure to urea solution using FTIR. Thus, the composite film acts as a low-cost non-enzymatic chemiresistive urea sensor with good sensitivity and reproducibility.
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    Improved Energy Management Strategy for Prosumer Buildings with Renewable Energy Sources and Battery Energy Storage Systems
    (IEEE, 2024-03) Mathur, Hitesh Datt; Mishra, Puneet
    The concept of utilizing microgrids (MGs) to convert buildings into prosumers is gaining massive popularity because of its economic and environmental benefits. These pro-sumer buildings consist of renewable energy sources and usually install battery energy storage systems (BESSs) to deal with the uncertain nature of renewable energy sources. However, because of the high capital investment of BESS and the limitation of available energy, there is a need for an effective energy management strategy for prosumer buildings that maximizes the profit of building owner and increases the operating life span of BESS. In this regard, this paper proposes an improved energy management strategy (IEMS) for the prosumer building to minimize the operating cost of MG and degradation factor of BESS. Moreover, to estimate the practical operating life span of BESS, this paper utilizes a non-linear battery degradation model. In addition, a flexible load shifting (FLS) scheme is also developed and integrated into the proposed strategy to further improve its performance. The proposed strategy is tested for the real-time annual data of a grid-tied solar photovoltaic (PV) and BESS-powered AC-DC hybrid MG installed at a commercial building. Moreover, the scenario reduction technique is used to handle the uncertainty associated with generation and load demand. To validate the performance of the proposed s trategy, the results of IEMS are compared with the well-established energy management strategies. The simulation results verify that the proposed strategy substantially increases the profit of the building owner and operating life span of BESS. Moreover, FLS enhances the performance of IEMS by further improving the financial profit of MG owner and the life span of BESS, thus making the operation of prosumer building more economical and efficient.