2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)最新文献

An Improving Efficiency MPPT in PV Systems with a Modified Voltage Regulator 改进电压调节器的光伏系统效率MPPT

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502234

Widjonarko, S. Bukhori, Arzoga Putra Pratama

{"title":"An Improving Efficiency MPPT in PV Systems with a Modified Voltage Regulator","authors":"Widjonarko, S. Bukhori, Arzoga Putra Pratama","doi":"10.1109/ISITIA52817.2021.9502234","DOIUrl":"https://doi.org/10.1109/ISITIA52817.2021.9502234","url":null,"abstract":"The hybrid renewable energy system is a breakthrough that can manage energy for consumer needs. In this system, the energy source of PV is apriority. On the other hand, PV is strongly influenced by environmental factors to produce maximum electrical energy. MPPT is a tracking technique that forces solar cells to work at their maximum working point. In this study, the algorithm applied to the SEPIC-type DC-DC system was P&O. The MPPT technique is able to increase the power that goes into the converter, but a problem is the efficiency of the input power and the output power of the PV that goes to the converter which in several previous studies has not been maximized. Therefore a voltage regulator system is given which functions to control the output voltage of the MPPT system so that it is able to be constant, this is also a solution to maximize the efficiency of PV. Based on the experiment, the voltage regulator's system work is to cut the output voltage from the DC Converter side with a duty ratio of about 20% to increase the MPPT system's efficiency with a value ranging from 80 - 95% at different irradiation variations.","PeriodicalId":161240,"journal":{"name":"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123581232","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}

引用次数: 0

MPPT of 1.5 kW Wind Turbine With Pitch and Voltage Control Based on Artificial Neural Network 基于人工神经网络的1.5 kW风力发电机组俯仰电压最大功率控制

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502257

F. Pamuji, Muhammad Ulil ‘Azmi, D. Riawan

{"title":"MPPT of 1.5 kW Wind Turbine With Pitch and Voltage Control Based on Artificial Neural Network","authors":"F. Pamuji, Muhammad Ulil ‘Azmi, D. Riawan","doi":"10.1109/ISITIA52817.2021.9502257","DOIUrl":"https://doi.org/10.1109/ISITIA52817.2021.9502257","url":null,"abstract":"This research contains the MPPT design on a PMSG wind turbine with a pitch and voltage controller using ANN. There are 3 models in this research, ANN-based settings with only pitch control, only voltage controllers, and with both pitch and voltage controllers. Modeling is done using MATLAB software as tool for making ANN and simulation. The ANN input in pitch angle controller are Cpopt and TSR with reference pitch angle as output, voltage controller input are optimum voltage of wind and voltage of actual with duty cycle as output. Simulations are made in 4 conditions, increasing and decreasing speed in region 2 and 3 of wind turbine. The results are, wind turbine model with pitch controller has an efficiency of 62.8%-66.2% in region 2 and 53.4-53.7% and able to limit the output in region 3, in voltage controller only the system has 93.497% efficiency with ripple and spike and reach maximum power in region 2 but it can not limit the output in region 3, and turbine with pitch and voltage controller has an efficiency of 93.4-97% with ripple and spike in region 2 and can limit the output in region 3 with efficiency 94.6%-94.2% whilst attaining maximum power altogether.","PeriodicalId":161240,"journal":{"name":"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125297911","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}

引用次数: 1

[ISITIA 2021 Front cover] [ISITIA 2021年封面]

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/isitia52817.2021.9502190

引用次数: 0

A Data Chaining on Relational Database: A Case Study with Indonesian Genomics Information System 关系数据库的数据链:以印尼基因组学信息系统为例

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502249

I. Sulistyawan, A. Arifin, M. Fatoni

引用次数: 2

Analysis of EEG-Based Stroke Severity Groups Clustering using K-Means 基于脑电图的脑卒中严重程度组聚类分析

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502250

M. T. Sulistyono, Evi Septiana Pane, A. Wibawa, M. Purnomo

{"title":"Analysis of EEG-Based Stroke Severity Groups Clustering using K-Means","authors":"M. T. Sulistyono, Evi Septiana Pane, A. Wibawa, M. Purnomo","doi":"10.1109/ISITIA52817.2021.9502250","DOIUrl":"https://doi.org/10.1109/ISITIA52817.2021.9502250","url":null,"abstract":"Rehabilitation is the essential key to restore motoric function and brain activity for stroke patients. Electroencephalograph (EEG) has been used widely as an alternative tool to monitor the progress of stroke rehabilitation because EEG represents the motoric function during motion. Determining the stroke severity level is also important during rehabilitation program because it gives information to the clinicians before performing rehabilitation. Stroke severity level will determine which rehabilitation programs the patient should take. Therefore, this study aims to classify stroke severity level by using the EEG features which are the Relative Power Ratio Power Spectral Density (RPR-PSD) and Relative Power Ratio Power Percentage (RPR-PP). The data is collected through the collaboration process with Airlangga University Hospital Surabaya (RSUA). The classes of stroke severity level are defined as severe, moderate, and mild. The EEG frequency sub-bands that were analyzed are Alpha Low (8-9 Hz), Alpha High (9-13 Hz), Beta Low (13-17), and Beta High (17-30 Hz). K-Means clustering method is applied to classify the severity level. From the ANOVA significane value, it shows that all groups of severity level from all sub-bands in this study showed p-value <0.05. This means that each severity group can be classified with its characteristics. From the two features that we analyzed, RPR-PSD showed more suitable condition to differenciate group of severity levels among all EEG frequency sub-bands. Furthermore, Alpha High sub-band showed a better condition to be used as an indicator for monitoring rehabilitation process for stroke patients due to its variance value behaviour. The variance value is changing linearly with the change of severity level compared to other sub-bands.","PeriodicalId":161240,"journal":{"name":"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128514466","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}

引用次数: 2

Real-Time Monitoring of Dual-Axis PV System Based on Internet of Things 基于物联网的双轴光伏系统实时监控

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502207

D. F. U. Putra, Aji Akbar Firdaus, Riky Tri Yunardi, Machrus Ali, Andrea Praja Rosalino, N. Putra

{"title":"Real-Time Monitoring of Dual-Axis PV System Based on Internet of Things","authors":"D. F. U. Putra, Aji Akbar Firdaus, Riky Tri Yunardi, Machrus Ali, Andrea Praja Rosalino, N. Putra","doi":"10.1109/ISITIA52817.2021.9502207","DOIUrl":"https://doi.org/10.1109/ISITIA52817.2021.9502207","url":null,"abstract":"Photovoltaic (PV) is a device that converts sunlight into electrical energy. PV will produce electrical energy according to the amount of light intensity it receives from the sun’s rays. However, in general, PV applications are installed statically, only facing one direction. It means that the PV module cannot get the maximum light intensity throughout the day. One of the efforts that can be done so that the PV module gets the maximum sunlight intensity throughout the day is to place the PV module in a perpendicular position following the movement of the sun. This is behind the creation of real-time monitoring and power point tracking tools for solar cells. This tool uses a photoresistor (LDR) sensor as a sensor and a servo motor as the PV module position’s driving force. Sunlight hitting the LDR sensor changes its resistance so that it affects the voltage value that will be received by the microcontroller analog pin. The microcontroller processes the information received from the LDR sensor and gives commands to drive the servo motor which will drive the PV module, with two axes to follow the daily pseudo motion and annual pseudo motion of the sun. This real-time monitoring and power point tracking PV tool has been tested. This tool has been able to follow the movement of the sun from East to West, obtained power of 0.001 watts for the use of LED light loads and obtained a percentage of error on the voltage sensor of 4.19% and the current sensor of 1.19%. The results of making real time monitoring show that the performance is quite efficient than the method without tracking, with a power efficiency value of 0.00649 W and this tool can monitor real time data or retrieve data once every 1 hour and 3 hours.","PeriodicalId":161240,"journal":{"name":"2021 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124555161","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}

引用次数: 3

Battery Energy Storage System as Frequency Control at Substation based on Defense Scheme Mechanism 基于防御方案机制的变电站变频电池储能系统

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502263

Z. Arifin, Aditya Firmanto

引用次数: 1

Analyze the Datasets of Software Effort Estimation With Particle Swarm Optimization 用粒子群算法分析软件工作量估计数据集

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502208

Ahmad Setiadi, Wahyutama Fitri Hidayat, Ahmad Sinnun, Ade Setiawan, Muhammad Faisal, D. Alamsyah

引用次数: 2

[Copyright notice] (版权)

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/isitia52817.2021.9502252

引用次数: 0

H-Infinity Controller Design of Two-Wheeled Mobile Robot Under Disturbance 扰动下两轮移动机器人h∞控制器设计

2021 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2021-07-21 DOI: 10.1109/ISITIA52817.2021.9502218

M. Fikri, D. W. Djamari, Steven M. Levy

引用次数: 1