Mangi Shetti Harsha Vardhan, S. Maddilety, D. S. Babu
{"title":"An Advanced Power Flow Control in Small Scale DC Power Structure by Using Multilevel Converter","authors":"Mangi Shetti Harsha Vardhan, S. Maddilety, D. S. Babu","doi":"10.55529/ijrise.26.1.8","DOIUrl":"https://doi.org/10.55529/ijrise.26.1.8","url":null,"abstract":"Because they combine outstanding harmonic performance with low switching frequencies, multilevel transforms are attractive options in Small-Scale DC Power Ne2rks. High dependability can also be obtained by including redundant submodules into the cascaded transform chain. DC microgrids are developing as the next generation of smallscale electric power structures, with very low line impedance. This phenomena creates high currents in microgrids even with little voltage changes; hence, a power flow controller must have quick transient reaction and accurate power flow management. Multi-level transforms are used as power flow controllers in this work to provide high speed and high accuracy power flow management in a dc microgrid. Because a multi-level transform is employed, the output filter can be tiny. The linear controller, such as PI or PID, is established and widely used in the power electronics sector, but its performance degrades as system parameters change. In this paper, a neural structure (NN) based voltage management technique for a DC-DC transform is developed. This project also shows how to construct the output LC filter of a multi-level transform to meet a current ripple requirement. In comparison to typical 2-level transforms, we can demonstrate that a multilevel transform with a smaller filter may provide high-speed and high-precision power flow management for low line impedance situations. MATLAB/Simulink Simulation results are used to evaluate the control performance of each output current in the step response while accounting for transient variations in the power flow.","PeriodicalId":263587,"journal":{"name":"International Journal of Research In Science & Engineering","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131184758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Abubakar, Zahra Soltanifar, Y. Luka, Eme William Udoh, M. Hamadou
{"title":"Analysis of Microbial Growth Models for Microorganisms in Chicken Manure Digester","authors":"A. Abubakar, Zahra Soltanifar, Y. Luka, Eme William Udoh, M. Hamadou","doi":"10.55529/ijrise.12.1.24","DOIUrl":"https://doi.org/10.55529/ijrise.12.1.24","url":null,"abstract":"Several microorganisms are there in chicken manure (CM) but Salmonella, Cryptosporidium and Escheridia coli are the most identified. Objective of this research includes, carrying out microbial count in the CM substrate for 40 days retention time in a digester, uterlizing kinetic expressions satisfying the process and fitting results obtained with 26 existing microbial growth kinetic models. Results shows that microbes inside the CM slurry, survived for a full period of 37 days divided into 7 days of acclimatization, 23 days of growth and another 7 days of equal rate of death and multiplication. Findings shows that the maximum specific growth rate, ????????????????, estimated from the basic Monod equation, of the organisms is 0.0076hr-1 and the half-saturation constant, ????????, is ????. ???????????? × ???????????? mg/l which indicates how sufficient the substrate concentration is for the bacteria to feed on. Not all 26 growth kinetic models found in the literature fit the measured experimental data. However, Monod with decay rate, Wayman and Tseng, Han and Levenspiel, Luong and Moser models fit the Monod values after regressing with POLYMATH 6.10 Educational Release.","PeriodicalId":263587,"journal":{"name":"International Journal of Research In Science & Engineering","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126106993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Network Management Model for Device-To-Device\u0000Communication in 5G Networks","authors":"","doi":"10.55529/ijrise.11.13.27","DOIUrl":"https://doi.org/10.55529/ijrise.11.13.27","url":null,"abstract":"The fifth generation (5G) cellular wireless communication paradigm is expected to encompass many new technologies, including device-to-device (D2D) wireless communication. In D2D communication, two user devices can communicate directly, without the involvement of a network. Such communication has several advantages, including improved spectral efficiency and user experience. However, for such communication to be an integral part of the 5G network, efficient network management is essential. This paper presents a network management model for D2D communication in 5G networks. The proposed model comprises two parts: the D2D link management (DLM) and the resource management (RM). DLM is responsible for D2D link establishment, monitoring, and optimization. RM is responsible for the allocation of resources among multiple users and services. The model is based on a distributed architecture, with the base station acting as a resource management node. The system performance of the proposed model is evaluated through extensive simulation. The simulation results show that the proposed model can effectively manage D2D links and resources in 5G networks.","PeriodicalId":263587,"journal":{"name":"International Journal of Research In Science & Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126517406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}