Intelligent Controller Design and Fault Prediction Using Machine Learning Model

Author:

Kumar Kailash1ORCID,Pande Suyog Vinayak2ORCID,Kumar T. Ch. Anil3,Saini Parvesh4ORCID,Chaturvedi Abhay5ORCID,Reddy Pundru Chandra Shaker6ORCID,Shah Krishna Bikram7ORCID

Affiliation:

1. College of Computing and Informatics, Saudi Electronic University, Riyadh 11673, Saudi Arabia

2. Department of Electronics and Telecommunication Engineering, Mukesh Patel School of Technology Management and Engineering, Shirpur Campus, Shirpur, Maharashtra, India

3. Department of Mechanical Engineering, Vignan’s Foundation for Science Technology and Research, Vadlamudi, Guntur, Andhra Pradesh 522213, India

4. Electrical Engineering, Graphic Era Deemed to Be University, Dehradun, India

5. Department of Electronics and Communication Engineering, GLA University, Mathura 281406, Uttar Pradesh, India

6. Department of Computer Science and Engineering, Geethanjali College of Engineering and Technology, Hyderabad, Telangana, India

7. Department of Computer Science and Engineering, Nepal Engineering College, Changunarayan, Bhaktapur, Nepal

Abstract

In a solar power plant, a solid phase transformer and an optimization coordinated controller are utilized to improve transient responsiveness. Transient stability issues in a contemporary electrical power system represent one of the difficult tasks for an electrical engineer due to the rise in uncertain renewable energy sources (RESs) as a result of the need for green energy. The potential for terminal voltage to be adversely impacted by this greater RES raises the possibility of electrical device damage. It is possible to use a solid state transformer (SST) or smart transformer to address a transient response issue. These devices are frequently employed to interact between RES and a power grid. SST features a variety of regulated converters to maintain the necessary voltage levels. This method can therefore simultaneously lessen power fluctuations and transient responsiveness. In order to improve the quality of RES power injections and the electrical system’s transient stability, this work provides a controller design for a solar photovoltaic (SPV) system that is connected to the grid by SST. The optimization of a controller model is proposed by modifying a PI controller taken from a commercial one. With the use of IEEE 39 standard buses, the proposed controller is tested. When evaluating the effectiveness of a suggested controller, it is important to take into account a variety of solar radiation patterns as well as a time delay uncertainty that can range from 425 ms to 525 ms. According to simulation results, the proposed controller can be employed to lessen power fluctuation brought on by unpredictable RES. Additionally, the proposed coordinated regulation of SPV and SST can prevent catastrophic damage in the event of substantial disturbances like a circuit breaker collapsing to expand a power line due to a fault by inhibiting significant voltage cycles within an electronic appliance’s rated voltage limit. The results indicate that a transitory stability issue in a modern power system caused by an unforeseen increase in RES may be addressed utilizing the suggested controllers as alternatives.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation

Cited by 43 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Intelligent Monitoring and Early Warning System for Electric Power Safety using Artificial Intelligence Approach;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

2. Brain Tumor Classification Using UNet Deep Neural Networks from 3D MRI Images;2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC);2024-05-02

3. A Novel Meta-Learning Ensemble Framework for Cancer Classification Using Convolution Neural Networks;2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC);2024-05-02

4. An Adaptive Intrusion Detection System in Industrial Internet of Things(IIoT) using Deep Learning;2024 1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics, and Smart Systems (ISTEMS);2024-04-26

5. Early Prediction and Diagnosis Cardiovascular Disease Using Deep Learning Models;2024 International Conference on Emerging Technologies in Computer Science for Interdisciplinary Applications (ICETCS);2024-04-22

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3