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您的检索式：作者名="M.Vijayakumar"
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| 1 | Enhanced Perturb and Observe Control Algorithm for a Standalone Domestic Renewable Energy System显示文摘The generation of electricity,considering environmental and eco-nomic factors is one of the most important challenges of recent years.In this article,a thermoelectric generator(TEG)is proposed to use the thermal energy of an electric water heater(EWH)to generate electricity independently.To improve the energy conversion efficiency of the TEG,a fuzzy logic con-troller(FLC)-based perturb&observe(P&O)type maximum power point tracking(MPPT)control algorithm is used in this study.An EWH is one of the major electricity consuming household appliances which causes a higher electricity price for consumers.Also,a significant amount of thermal energy generated by EWH is wasted every day,especially during the winter season.In recent years,TEGs have been widely developed to convert surplus or unused thermal energy into usable electricity.In this context,the proposed model is designed to use the thermal energy stored in the EWH to generate electricity.In addition,the generated electricity can be easily stored in a battery storage system to supply electricity to various household appliances with low-power-consumption.The proposed MPPT control algorithm helps the system to quickly reach the optimal point corresponding to the maximum power output and maintains the system operating point at the maximum power output level.To validate the usefulness of the proposed scheme,a study model was developed in the MATLAB Simulink environment and its performance was investigated by simulation under steady state and transient conditions.The results of the study confirmed that the system is capable of generating adequate power from the available thermal energy of EWH.It was also found that the output power and efficiency of the system can be improved by maintaining a higher temperature difference at the input terminals of the TEG.Moreover,the real-time temperature data of Abha city in Saudi Arabia is considered to analyze the feasibility of the proposed system for practical implementation. | N.Kanagaraj Obaid Martha Aldosary M.Ramasamy M.Vijayakumar | 2023 | Intelligent Automation & Soft Computing2023，37，8： | 0 |
| 2 | Optimization of Cognitive Femtocell Network via Oppositional Beetle Swarm Optimization Algorithm显示文摘In past decades,cellular networks have raised the usage of spectrum resources due to the victory of mobile broadband services.Mobile devices create massive data than ever before,facing the way cellular networks are installed pre-sently for satisfying the increased traffic requirements.The development of a new exclusive spectrum offered to meet up the traffic requirements is challenging as spectrum resources are limited,hence costly.Cognitive radio technology is pre-sented to increase the pool of existing spectrum resources for mobile users via Femtocells,placed on the top of the available macrocell network for sharing the same spectrum.Nevertheless,the concurrent reuse of spectrum resources from Femto networks poses destructive interference on macro networks.To resolve this issue,this paper introduces an optimal channel allocation model using the Oppo-sitional Beetle Swarm Optimization Algorithm(OBSOA)to allocate the channel with interference avoidance.A new OBSOA is derived in this paper by the inclu-sion of opposition-based learning(OBL)in BSOA.This algorithm allocates the channels used by PUs(PUs)to the secondary users(SUs)in such a way that inter-ference is minimized.This proposed approach is implemented in the MATrix LABoratory(MATLAB)platform.The performance of this proposed approach is evaluated in terms of several measures and the experimental outcome verified the superior nature of the OBSOA-based channel allocation model.OBSOA mod-el has resulted in a maximum signal-to-interference-plus-noise ratio value of 86.42 dB. | K.Rajesh Kumar M.Vijayakumar | 2023 | Intelligent Automation & Soft Computing2023，，4： | 0 |
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