Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862474
Subhashis Dey, Shamik Dasadhikari, Cherosree Dolui, Debabrata Roy
Iron-gallium alloys, known as Galfenol, can generate electrical energy from ambient vibrations. The device consists of a strip of Magnetostrictive Material Galfenol combined with a stainless-steel frame, copper coil, bias magnet, and soft iron to hold the bias magnet together. The total length of the energy harvester is 120 mm and a sinusoidal force is provided at the tip of the energy harvester. This paper deals with the experimental output of coil voltage obtained by varying the size of Galfenol and bias magnet (up to a possible range). The Magnetostrictive material (Galfenol) is varied from a length of 26 mm to 48 mm, similarly, these bias magnets are also varied from a length of 6 mm each to 11.5 mm each. Different values of coil voltage are obtained from different values of the length.
{"title":"Effect on Coil Voltage by Varying the Size of Galfenol in Magnetostrictive Energy Harvester","authors":"Subhashis Dey, Shamik Dasadhikari, Cherosree Dolui, Debabrata Roy","doi":"10.1109/ICICCSP53532.2022.9862474","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862474","url":null,"abstract":"Iron-gallium alloys, known as Galfenol, can generate electrical energy from ambient vibrations. The device consists of a strip of Magnetostrictive Material Galfenol combined with a stainless-steel frame, copper coil, bias magnet, and soft iron to hold the bias magnet together. The total length of the energy harvester is 120 mm and a sinusoidal force is provided at the tip of the energy harvester. This paper deals with the experimental output of coil voltage obtained by varying the size of Galfenol and bias magnet (up to a possible range). The Magnetostrictive material (Galfenol) is varied from a length of 26 mm to 48 mm, similarly, these bias magnets are also varied from a length of 6 mm each to 11.5 mm each. Different values of coil voltage are obtained from different values of the length.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133517510","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862482
K. Sameer, K. Haritha, N. Ramchander, B. Reddy, K. Rayudu, K. R. Reddy
Renewable energy is being produced through various resources, mostly natural and abundantly available, such as wind, solar, and geothermal. Solar PV technology is a novice alternate renewable energy system which is becoming popular during 21st century. In Solar Photovoltaic (SPV) power systems, the major component are polycrystalline PV modules which have a shelf-life of around 25 years, as claimed by most of the PV module producers. Most of the installations started 10 years ago and there is a need to investigate the ageing upshot or digression of PV modules. To this end, a seven-year-old large-scale PV plant is considered for case study. Field experiments are conducted to know the power output of these modules and the manufactures claim of 25 years life with indicated digression is validated with the field values. Also, machine learning technique is used to derive an empirical relation for the power output of age old PV modules. Finally, conclusions are drawn with respect to ageing upshot and life predictions of PV Modules.
{"title":"Field Investigation of Solar Photovoltaic Modules Digression Against Manufacture's Claim and Application of Machine Learning Model in Life Prediction: A Case Study","authors":"K. Sameer, K. Haritha, N. Ramchander, B. Reddy, K. Rayudu, K. R. Reddy","doi":"10.1109/ICICCSP53532.2022.9862482","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862482","url":null,"abstract":"Renewable energy is being produced through various resources, mostly natural and abundantly available, such as wind, solar, and geothermal. Solar PV technology is a novice alternate renewable energy system which is becoming popular during 21st century. In Solar Photovoltaic (SPV) power systems, the major component are polycrystalline PV modules which have a shelf-life of around 25 years, as claimed by most of the PV module producers. Most of the installations started 10 years ago and there is a need to investigate the ageing upshot or digression of PV modules. To this end, a seven-year-old large-scale PV plant is considered for case study. Field experiments are conducted to know the power output of these modules and the manufactures claim of 25 years life with indicated digression is validated with the field values. Also, machine learning technique is used to derive an empirical relation for the power output of age old PV modules. Finally, conclusions are drawn with respect to ageing upshot and life predictions of PV Modules.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134136459","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862353
Radharani Panigrahi, N. Patne, Sumanth Pemmada, Ashwini D. Manchalwar
This paper emphasizes the capability of Deep Learning (DL) models to conquer the Demand Response (DR) inherent when predicting the Electric Energy Consumption (EEC) of an office building. The prediction of EEC plays a key role in DR programs in a smart grid environment. In this study, historical energy consumption and ambient temperature data of three different climatic days (summer, winter, and cloudy days) of an office building located in Portugal at 10 seconds intervals are taken. A DL technique-based Deep Neural Network model is proposed for the prediction of future EEC. In this paper predictability of EEC of the whole office building has been analyzed. This study describes an evince DL application for commercial energy consumption prediction at 10 seconds intervals and performed precursory success. Moreover, two conventional Machine Learning (ML) models i.e., Support Vector Regressor (SVR) and Random Forest (RF) are developed and analyzed. Furthermore, the proposed DL model is compared with SVR and RF in terms of performance evaluation parameters such as Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). All the models are developed and executed on TensorFlow deep learning platform. The proposed model defeats SVR by 91.65%and RF by 87.38% on a summer day, similarly defeats SVR by 93.85% and RF by 91.68% on a winter day and defeats SVR by 95.63% and RF by 92.67% on a cloudy day in terms of MSE.
{"title":"Prediction of Electric Energy Consumption for Demand Response using Deep Learning","authors":"Radharani Panigrahi, N. Patne, Sumanth Pemmada, Ashwini D. Manchalwar","doi":"10.1109/ICICCSP53532.2022.9862353","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862353","url":null,"abstract":"This paper emphasizes the capability of Deep Learning (DL) models to conquer the Demand Response (DR) inherent when predicting the Electric Energy Consumption (EEC) of an office building. The prediction of EEC plays a key role in DR programs in a smart grid environment. In this study, historical energy consumption and ambient temperature data of three different climatic days (summer, winter, and cloudy days) of an office building located in Portugal at 10 seconds intervals are taken. A DL technique-based Deep Neural Network model is proposed for the prediction of future EEC. In this paper predictability of EEC of the whole office building has been analyzed. This study describes an evince DL application for commercial energy consumption prediction at 10 seconds intervals and performed precursory success. Moreover, two conventional Machine Learning (ML) models i.e., Support Vector Regressor (SVR) and Random Forest (RF) are developed and analyzed. Furthermore, the proposed DL model is compared with SVR and RF in terms of performance evaluation parameters such as Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). All the models are developed and executed on TensorFlow deep learning platform. The proposed model defeats SVR by 91.65%and RF by 87.38% on a summer day, similarly defeats SVR by 93.85% and RF by 91.68% on a winter day and defeats SVR by 95.63% and RF by 92.67% on a cloudy day in terms of MSE.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130314212","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862341
Narayan Nahak, R. Singh, S. Parida, Samarjeet Satapathy, P. Nayak
This work proposes an optimal fractional power system stabilizer control action to improve dynamic stability of grid integrated micro grid system. A fractional PID controller-based PSS has been implemented here whose gains are optimized by sailfish algorithm. The solar and wind generations in the micro grid are varied in step and random manner creating disturbances which is variation in angular frequency of power system. By proposed sailfish algorithm tuned PSS action this variation in angular frequency is heavily damped that has been compared with PSO & DE algorithms. System Eigen analysis has been performed to validate proposed optimal control action. The system eigen distributions and results analysis predict that proposed action is more efficient and is simple to implement for a micro grid system.
{"title":"Dynamic stability improvement of a micro grid system by optimized PSS controller","authors":"Narayan Nahak, R. Singh, S. Parida, Samarjeet Satapathy, P. Nayak","doi":"10.1109/ICICCSP53532.2022.9862341","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862341","url":null,"abstract":"This work proposes an optimal fractional power system stabilizer control action to improve dynamic stability of grid integrated micro grid system. A fractional PID controller-based PSS has been implemented here whose gains are optimized by sailfish algorithm. The solar and wind generations in the micro grid are varied in step and random manner creating disturbances which is variation in angular frequency of power system. By proposed sailfish algorithm tuned PSS action this variation in angular frequency is heavily damped that has been compared with PSO & DE algorithms. System Eigen analysis has been performed to validate proposed optimal control action. The system eigen distributions and results analysis predict that proposed action is more efficient and is simple to implement for a micro grid system.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130365147","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862331
S. Anbuselvi, R. Devi, R. Brinda
With the advancement in battery technology and power electronic converters, there is a massive increase in the use of Electric Vehicles (EV). Huge penetration of power electronic devices into the grid reduces the rotational inertia of the power system and compromise on the frequency stability. In order to reduce frequency error and the Rate of Change of Frequency (ROCOF) in low inertia power system, inertia support needs to be provided. Various methods are employed to provide grid frequency support by regulating the power exchange between the grid and grid tied inverter. In case of EV integration, virtual inertia can be obtained from two sources: one from the energy stored in dc link capacitors of the grid tied VSC and the other from the battery charging points. Coordinated control from the VSC and EV charging ports provide frequency support to the grid on an event of disturbance. This paper proposes a coordinated droop control strategy to mitigate the frequency stability issues.
{"title":"Coordinated Control of EV Charging stations for Grid Frequency Support","authors":"S. Anbuselvi, R. Devi, R. Brinda","doi":"10.1109/ICICCSP53532.2022.9862331","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862331","url":null,"abstract":"With the advancement in battery technology and power electronic converters, there is a massive increase in the use of Electric Vehicles (EV). Huge penetration of power electronic devices into the grid reduces the rotational inertia of the power system and compromise on the frequency stability. In order to reduce frequency error and the Rate of Change of Frequency (ROCOF) in low inertia power system, inertia support needs to be provided. Various methods are employed to provide grid frequency support by regulating the power exchange between the grid and grid tied inverter. In case of EV integration, virtual inertia can be obtained from two sources: one from the energy stored in dc link capacitors of the grid tied VSC and the other from the battery charging points. Coordinated control from the VSC and EV charging ports provide frequency support to the grid on an event of disturbance. This paper proposes a coordinated droop control strategy to mitigate the frequency stability issues.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125096986","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862457
Smarak Pani, Sarita Samal, B. Nayak, Babita Panda, A. Mohapatra, P. K. Barik
The main objective of this study is to mitigate the current harmonic issues with the help of a suitable controller-based shunt active power filter (SAPF) in hybrid renewable energy system i.e., solar photovoltaic (SPV) and wind energy system-based distribution generation system. The SAPF is designed by using a synchronous reference frame (SRF) technique for reference current generation, a hysteresis current controller (HCC) technique for switching pulse generation and fuzzy logic controller (FLC) for DC-link voltage regulation. The suggested model of SAPF is developed in MATLAB/Simulink, and the results show that the filter performs remarkably well in supressing harmonics under different loading conditions. It is capable of providing fast corrective action under dynamic conditions and outperforms previous methods in terms of harmonic mitigation and dc-link voltage stabilization. The control techniques are compared on the basis of parameters such as harmonic compensation and dc link voltage ripple reduction capability under dynamically changing nonlinear load. The results obtained through simulation represents the validity of the performance of the filter.
{"title":"Fuzzy-HCC based shunt active power filter integrated hybrid energy system for compensation of harmonics","authors":"Smarak Pani, Sarita Samal, B. Nayak, Babita Panda, A. Mohapatra, P. K. Barik","doi":"10.1109/ICICCSP53532.2022.9862457","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862457","url":null,"abstract":"The main objective of this study is to mitigate the current harmonic issues with the help of a suitable controller-based shunt active power filter (SAPF) in hybrid renewable energy system i.e., solar photovoltaic (SPV) and wind energy system-based distribution generation system. The SAPF is designed by using a synchronous reference frame (SRF) technique for reference current generation, a hysteresis current controller (HCC) technique for switching pulse generation and fuzzy logic controller (FLC) for DC-link voltage regulation. The suggested model of SAPF is developed in MATLAB/Simulink, and the results show that the filter performs remarkably well in supressing harmonics under different loading conditions. It is capable of providing fast corrective action under dynamic conditions and outperforms previous methods in terms of harmonic mitigation and dc-link voltage stabilization. The control techniques are compared on the basis of parameters such as harmonic compensation and dc link voltage ripple reduction capability under dynamically changing nonlinear load. The results obtained through simulation represents the validity of the performance of the filter.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134083508","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862402
Snehashis Ghoshal, Sumit Banerjee, Sweta, Rakesh Maji, Nehal Akhter, C. K. Chanda
Minimizing the emission of greenhouse gases attained significant concern during last century. Eco-friendly energy extraction has been a matter of great concern due to the finite and polluting nature of fossil fuel-based resources. In view of this, fuel cell possesses an important part. A fuel cell generally converts chemical energy embedded within fuel into electricity without any combustion as well as through more efficient way. With the advancement in polymer technology, different fuel cells have been fabricated and proton exchange membrane fuel cell (PEMFC) has found efficient in most of the applications now-a-days. In this study, the objective was to analyze the performance of a PEM fuel cell in small scale DC system using a boost converter. The converter is actuated by a Fuzzy logic controller (FLC). The simulation was done in MATLAB/Simulink environment. Such a system can be used to implement small DC charging stations in view of charging electric vehicles.
{"title":"Modeling and Performance Analysis of a Closed Loop PEMFC in Small Scale Stand Alone DC System","authors":"Snehashis Ghoshal, Sumit Banerjee, Sweta, Rakesh Maji, Nehal Akhter, C. K. Chanda","doi":"10.1109/ICICCSP53532.2022.9862402","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862402","url":null,"abstract":"Minimizing the emission of greenhouse gases attained significant concern during last century. Eco-friendly energy extraction has been a matter of great concern due to the finite and polluting nature of fossil fuel-based resources. In view of this, fuel cell possesses an important part. A fuel cell generally converts chemical energy embedded within fuel into electricity without any combustion as well as through more efficient way. With the advancement in polymer technology, different fuel cells have been fabricated and proton exchange membrane fuel cell (PEMFC) has found efficient in most of the applications now-a-days. In this study, the objective was to analyze the performance of a PEM fuel cell in small scale DC system using a boost converter. The converter is actuated by a Fuzzy logic controller (FLC). The simulation was done in MATLAB/Simulink environment. Such a system can be used to implement small DC charging stations in view of charging electric vehicles.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133544825","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862384
R. R. Karasani, Abhiram Tikkani
A single phase cascaded modular multilevel inverter is derived from further modified H-bridge module (FMHB). The principle of self-balancing is explained for proposed 5-level basic module. The attractive feature of this topology is its capability to function under both symmetrical and asymmetrical modes with less power switches. The propounded multilevel inverter can synthesize levels according to the magnitude of DC voltage sources employed in each module. The inter and intra module configurations are analyzed. The comparative analysis is done with classical cascaded H-bridge (CHB) and recently reported multilevel inverters. The pulse sequence is generated by Nearest Level Control (NLC) technique. The simulations are performed in MATLAB/SIMULINK under dynamic transition of cascade connections. Experimental results are presented by cascading two FMHB modules to affirm simulation results.
{"title":"A Generalized Single Phase Cascaded Modular Multilevel Inverter based on Inter and Intra Module Configurations","authors":"R. R. Karasani, Abhiram Tikkani","doi":"10.1109/ICICCSP53532.2022.9862384","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862384","url":null,"abstract":"A single phase cascaded modular multilevel inverter is derived from further modified H-bridge module (FMHB). The principle of self-balancing is explained for proposed 5-level basic module. The attractive feature of this topology is its capability to function under both symmetrical and asymmetrical modes with less power switches. The propounded multilevel inverter can synthesize levels according to the magnitude of DC voltage sources employed in each module. The inter and intra module configurations are analyzed. The comparative analysis is done with classical cascaded H-bridge (CHB) and recently reported multilevel inverters. The pulse sequence is generated by Nearest Level Control (NLC) technique. The simulations are performed in MATLAB/SIMULINK under dynamic transition of cascade connections. Experimental results are presented by cascading two FMHB modules to affirm simulation results.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133965515","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}
Pub Date : 2022-07-21DOI: 10.1109/iciccsp53532.2022.9862336
{"title":"ICICCSP 2022 Reviewers","authors":"","doi":"10.1109/iciccsp53532.2022.9862336","DOIUrl":"https://doi.org/10.1109/iciccsp53532.2022.9862336","url":null,"abstract":"","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"72 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131626729","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}
Pub Date : 2022-07-21DOI: 10.1109/ICICCSP53532.2022.9862383
Achhi Pradyumna, Sai Madhav Kuthadi, A. A. Kumar, N. Karuppiah
The electrical grid connects all the generating stations to supply uninterruptible power to the consumers. With the advent of technology, smart sensors and communication are integrated with the existing grid to behave like a smart system. This smart grid is a two-way communication that connects the consumers and producers. It is a connected smart network that integrates electricity generation, transmission, substation, distribution, etc. In this smart grid, clean, reliable power with a high-efficiency rate of transmission is available. In this paper, a highly efficient smart management system of a smart grid with overall protection is proposed. This management system checks and monitors the parameters periodically. This future technology also develops a smart transformer with ac and dc compatibility, for self-protection and for the healing process.
{"title":"IoT Based Smart Grid Communication with Transmission Line Fault Identification","authors":"Achhi Pradyumna, Sai Madhav Kuthadi, A. A. Kumar, N. Karuppiah","doi":"10.1109/ICICCSP53532.2022.9862383","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862383","url":null,"abstract":"The electrical grid connects all the generating stations to supply uninterruptible power to the consumers. With the advent of technology, smart sensors and communication are integrated with the existing grid to behave like a smart system. This smart grid is a two-way communication that connects the consumers and producers. It is a connected smart network that integrates electricity generation, transmission, substation, distribution, etc. In this smart grid, clean, reliable power with a high-efficiency rate of transmission is available. In this paper, a highly efficient smart management system of a smart grid with overall protection is proposed. This management system checks and monitors the parameters periodically. This future technology also develops a smart transformer with ac and dc compatibility, for self-protection and for the healing process.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132228039","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}
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