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Distributed resource scheduling in smart grid with electric vehicle deployment using fireworks algorithm

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Journal of Modern Power Systems and Clean Energy 2016年第2期4卷 188-199页

作者： K.Srikanth REDDY Lokesh Kumar PANWAR Rajesh KUMAR Bijaya Ketan PANIGRAHI IIT Delhi New DelhiIndia mnit jaipur JaipurRajasthanIndia

Global warming and climate change are two key probing issues in the present *** electricity sector and transportation sector are two principle entities propelling both these *** from these two sectors can be offset by switching to greener ways of transportation through the electric vehicle (EV) and renewable energy technologies (RET).Thus,effective scheduling of both resources holds the key to sustainable *** paper presents a scheduling scenario-based approach in the smart *** formulation with dual objective function including both emissions and cost is developed for conventional unit commitment with EV and RET *** this work,the scheduling and commitment problem is solved using the fireworks algorithm which mimics explosion of fireworks in the sky to define search space and the distance between associated sparks to evaluate global ***,binary coded fireworks algorithm is developed for the proposed scheduling problem in the smart ***,possible scenarios inconventional as well as smart grid are put *** that,the proposed methodology is simulated using a test system with thermal generators.

关键词： Unit commitment problem(UCP) Binary fireworks algorithm(BFWA) Constrained optimization Renewable energy technologies(RETs) Plug-in electric vehicle(PEV)

Role of NiMn_(9.3)Al_(4.0)Co_(14.1)Fe_(3.6)alloy on dehydrogenation kinetics of MgH_(2)

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Journal of Magnesium and Alloys 2018年第3期6卷 318-325页

作者： Priyanka Meena Ramvir Singh V.K.Sharma I.P.Jain Centre for Non-Conventional Energy Resources University of RajasthanJaipurIndia Metallurgical and Material Engineering Department MNITJaipurIndia Physics Department University of RajasthanJaipurIndia

Hydriding and dehydriding properties of MgH_(2)-x wt.%NiMn_(9.3)Al_(4.0)Co_(14.1)Fe_(3.6)(x=10,25,50)nanocomposites have been investigated in present *** alloy was prepared by arc melting method and ball milled with MgH_(2)to get *** temperature as low as 180℃was observed for MgH_(2)-50 wt%system which is 80℃lower than the as-milled MgH_(2)giving 131.34 KJ/mol activation *** analysis shows tetragonal,orthorhombic and monoclinic phases for MgH_(2),Al_(60)Mn_(11)Ni_(4)and Mg_(2)NiH_(4).Morphology by SEM were undertaken to investigate the effect of hydrogenation on nanostructured *** studies show a single broad exothermic peak in the temperature range 48℃-353℃after alloy addition in MgH_(2).These results indicate that the hydrogenation properties of MgH_(2)nanocomposite have been improved compared to the as-milled MgH_(2).

关键词： Hydrogen storage Activation energy Mg based nanocomposites Phase structure TGA

Kinematic Modeling for Biped Robot Gait Trajectory Using Machine Learning Techniques

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Journal of Bionic Engineering 2022年第2期19卷 355-369页

作者： Bharat Singh Ankit Vijayvargiya Rajesh Kumar Department of Electrical Engineering Malaviya National Institute of TechnologyJaipur 302017India

This paper presents the predictive models for biped robot trajectory *** models are parametrizing as a continuous function of joint angle *** a previous work,the authors had collected the human locomotion dataset at RAMAN Lab,mnit,jaipur,*** mnit gait dataset consists of walking data on a plane surface of 120 human subjects from different age groups and ***-two machine learning models(linear,support vector,k-nearest neighbor,ensemble,probabilistic,and deep learning)trained using the collected *** addition,two types of mapping,(a)one-to-one and(b)many-to-one,are presented for each *** mapping models act as a reference policy for the control of joints and prediction of state for the next time instant in advance if the onboard sensor *** show that the deep learning and probabilistic learning models perform better for both types of ***,the probabilistic model outperforms the deep learning-based models in terms of maximum error,because the probabilistic model effectively deals with the prediction *** addition,many-to-one outperforms the one-to-one mapping because it captures the correlation between knee,hip,and ankle ***,this study suggests a many-to-one mapping using the probabilistic model for biped robot trajectory generation.

关键词： Kinematic Locomotion Machine learning Prediction Regression

A Multiple Emission Constrained Approach for Self-scheduling of GENCO Under Renewable Energy Penetration

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CSEE Journal of Power and Energy Systems 2017年第1期3卷 63-73页

作者： Srikanth Reddy Konda Lokesh Kumar Panwar Bijaya Ketan Panigrahi Rajesh Kumar Department of Electrical Engineering IIT DelhiIndia Center for Energy and Environment MNIT JaipurRajasthan 302017India

The electric sector contributes substantially to both greenhouse gas(GHG)and non-greenhouse gas(NGHG)emissions,which means that both conventional and thermal generation companies(GENCOs)must follow certain environmental guidelines to address various emission *** paper presents a methodology to investigate the feasibility of both GHG and NGHG emission reduction in a deregulated electricity *** proposed model takes into consideration the effect of NGHG emission cost constraints in conjunction with classical GHG emission constraints for the scheduling aspects of GENCO.A profit based self-scheduling problem with conventional fossil fueled generators and renewable energy technologies(RETs)is formulated including emission penalties and avoidance costs of GHG and NGHG emissions,***,a set of pareto solutions is evaluated for different possible scheduling scenarios.A simple,effective optimality criteria is also postulated to identify the tradeoff ***,a sensitivity analysis of various technical,environmental,as well as economic aspects is presented to examine the effect of NGHG consideration and RET inclusion in *** simulation results are presented and discussed in detail to examine the effect of NGHG consideration in self-scheduling practices of GENCO in the electricity market,thus reflecting the benefits of the proposed approach over classical emission handling approaches.

关键词： Greenhouse gases(GHG) GENCO selfscheduling independent system operator(ISO) non-greenhouse gas(NGHG) renewable energy technologies(RETs) weight factor

Thermal Comfort Analysis of Personalized Conditioning System and Performance Assessment with Different Radiant Cooling Systems

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Energy and Built Environment 2023年第1期4卷 111-121页

作者： Vaibhav Rai Khare Ravi Garg Jyotirmay Mathur Vishal Garg Malaviya National Institute of Technology JaipurIndia International Institute of Information Technology HyderabadIndia

The radiant systems consume less energy and provide better thermal comfort as compared to the conventional system,but the main drawback of radiant technology is inability to cater the latent load and *** problem has engaged researchers to push their emphasis on Personalized Conditioning System(PCS).It forms a micro-climate region near the *** study is aimed at PCS combined with a radiant conditioning system,which evaluates the performance of the PCS and compares it with different radiant cooling systems.A radiant cubicle was used to investigate the performance of the PCS for both heating&cooling *** heating mode,the Standard Effective Temperature(SET)was calculated with the help of thermal comfort surveys which were in a range of 23.4℃ to 27.3℃.For cooling mode,four different cases compared the performance of the system which are:Conventional Air Conditioning System(CACS),Radiant Cooled Ceiling System(RCCS),Personalized Radiant Conditioning System(PRCS),and both PRCS-RCCS *** was observed that PRCS alone reaches the thermal comfort criteria with low energy *** energy-saving of RCCS-PRCS was achieved 38%when compared with *** can be concluded that PRCS is a new step in the field of thermal comfort.

关键词： Radiant cooling system Personalized cooling system Thermal comfort Standard effective temperature

Catalytic Cracking of Waste Polypropylene in a Nitrogen Fluidized Bed Reactor

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Journal of Geoscience and Environment Protection 2016年第4期4卷 20-25页

作者： Anil Vyas Suresh Kumar Singh Komal Sharma Sukhwant Singh Chemical Engineering Department Jai Narain Vyas University Jodhpur India Civil Engineering Department Jai Narain Vyas University Jodhpur India Chemical Engineering Department MNIT Jaipur India

Polypropylene (PP) is rated first as volume leader in the plastic sector. Its non-biodegradable property poses serious environmental problem in case of disposal. The catalytic cracking of PP was performed with various catalysts i.e. ZSM-5, Zeolite, RB and SPS. The cracking was observed under different feed to catalyst ratio i.e. 1:1 to 5:1. The fluidized bed reactor was fabricated with arrangement to measure the temperature ranging from 100。C to 800。C. The effective of feed to catalyst ratio was found 3:1 at a temperature range of 420。C - 510。C and catalyst ZSM-5 gives maximum liquid conversion of waste PP. Conversion of PP to liquid fuel will not only resolve the problem of disposal of waste polypropylene plastic but also give a value aided product.

关键词： Waste PP Pyrolysis Catalytic Cracking ZSM-5 Zeolite Liquid Fuel