A Deep Learning Based Enhancing the Power by Reducing the Harmonics in Grid Connected Inverters

Authors

  • Subramanya Sarma S Department of EEE Ramachandra College of Engineering Vatluru, Eluru-534007, Andhra Pradesh, India
  • K. Sarada Department of Electrical & Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India
  • P. Jithendar Department of Electrical and Electronics Engineering, MLR institute of Technology, Hyderabad, India
  • Telugu Maddileti Department of ECE, Malla Reddy Engineering College (A), Telangana-500100, India
  • G. Nanda Kishor Kumar Computer Science and Engineering, Malla Reddy University, Hyderabad, Telangana, India

DOI:

https://doi.org/10.13052/dgaej2156-3306.3916

Keywords:

RCNN, power, inverter, IEEE 1547

Abstract

The increasing use of renewable energy systems has led to a rise in the number of grid-connected inverters, which can have a detrimental effect on the superiority and constancy of grid electricity due to the injected current harmonics. In this study, the proportional integral (PI) and proportional resonant (PR) controllers have been investigated for their effectiveness in reducing harmonics in grid-connected inverters. The study also investigates the impact of harmonics compensators (HC) on the control strategies.

The results of the study suggest that the implementation of PI and PR controllers in the synchronous frame can effectively reduce the injected current harmonics in grid-connected inverters. The use of harmonics compensators can further enhance the performance of the controllers by reducing the distortion and improving the stability of the grid. The efficiency of the regulator strategies be contingent on the type and level of harmonics in the grid, as well as the design and tuning of the controllers and compensators.

The statement that the “PR+HC controller has a superior quality output current” is more specific and suggests that this control method may be more effective than the others in reducing harmonics and enlightening the value of the productivity current. The comparison of the IEEE 1547 standard by three viable inverters from diverse constructors is also noteworthy, as it can provide insights into the compatibility and performance of different types of inverters with the standard. The use of deep learning with the RCNN network for analyzing harmonics and providing information about power is an interesting application of machine learning in power systems research. This approach may have the probable to development the accuracy and competence of harmonics analysis as well as power monitoring in grid-connected inverters.

Overall, the study highlights the importance of effective control strategies for managing harmonics in grid-connected inverters, particularly in the context of the increasing usage of renewable energy systems. The findings of the study can inform the development of more efficient and reliable grid-connected inverters, which are essential for the incorporation of renewable energy systems into the power grid.

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Author Biographies

Subramanya Sarma S, Department of EEE Ramachandra College of Engineering Vatluru, Eluru-534007, Andhra Pradesh, India

Subramanya Sarma S is a Professor of ELECTRICAL AND ELECTRONICS ENGINEERING has been a full-time faculty member since 2008. He is currently holding the position of Dean (Academics) at RAMACHANDRA COLLEGE OF ENGINEERING (AUTONOMOUS), ELURU and is also a member of the Board of Governance of RCE. He is a unique amalgam of academics and research. He has professional experience of close to two decades. He earned his B.Tech in Electrical and Electronics Engineering from Jawaharlal Nehru Technological University, Hyderabad, his M.Tech in Electrical Power Systems from Jawaharlal Nehru Technological University, Anantapur, and his Ph.D. in Electrical Engineering from Jawaharlal Nehru Technological University, Anantapur. He served as Head of EEE department at RCE till August, 2022. He has published 30 research articles in national and international journals of repute, In relation to his research areas. His research interests include distributed generation, reliability, renewable energy sources, Internet of Things (IoT), artificial intelligence, and optimization techniques. He was awarded withbest paper at the International Conference on Electrical Engineering, which was held at Gitam University, Visakhapatnam. He is a reviewer for the Taylor & Francis Publications’ Electric Power Components and Systems Journal. He is the editorial member for International Journal of Modern Trends in Science and Technology (IJMTST) (ISSN:2455-3778). He awarded as Best Faculty by the Ramachandra College of Engineering, Eluru. At his current working institute, he has chaired and organised 20 FDPs, 30 workshops, and 30 guest lectures. He is an ISTE Professional Body Life Member. He gave lectures in several colleges in Andhra Pradesh and Tamil Nadu. He is the recipient of YOUNG RESEARCHER award and YOUN SCIENTIST AWARD. He authored 3 Text books related to ELECTRICAL ENGINEERING. Total 3 Patents are under his credit.

K. Sarada, Department of Electrical & Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India

K. Sarada, completed B.Tech in 2001 from Sri Vidyanikethan Engineering College, did M.tech in 2005 from S V University College of Engineering, Tirupati. Pursing Phd from Rayalaseema University, Kurnool. Her research areas are power systems, deregulated power systems, control and operation, Microgrids, Power Quality.

Currently working as ASSOCIATE PROFESSOR, DEPT. OF EEE, KONERU LAKSHMAIAH EDUCATION FOUNDATION.

P. Jithendar, Department of Electrical and Electronics Engineering, MLR institute of Technology, Hyderabad, India

P. Jithendar Currently working as associate professor at Department of EEE, MLR Institute of Technology, Dundigal, TS, India and obtained his B.Tech at BVRIT, Narasapur, TS and his M.Tech at JBIET, TS. HE published 2 journals. Area of interest IS Solar energy systems.

Telugu Maddileti, Department of ECE, Malla Reddy Engineering College (A), Telangana-500100, India

Telugu Maddileti is currently working as an Associate Professor in the department of ECE at MREC. He has a total of 18 years of teaching experience in academics including 7 years of Research experience. He has completed B.Tech degree in Electronics and communication Engineering in the year 2005 and M.Tech in VLSI System Design from JNT University, Hyderabad in 2009. Received PhD from JNTU, Anantpur in 2021. He is enthusiastic to work in the field of VLSI. His area of interests include Low power VLSI, Optimization of Analog and Mixed Signal Circuits in addition to digital system design using CADENCE tools. He has presented more than 60 International/National Technical Papers in journals & conferences.

G. Nanda Kishor Kumar, Computer Science and Engineering, Malla Reddy University, Hyderabad, Telangana, India

G. Nanda Kishor Kumar, is professor in Malla Reddy university, Controller of Examinations. His research area is computer science application like cloud and bigdata applications. He has 10 research papers in various technologies.

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Published

2023-10-30

How to Cite

Sarma S, S. ., Sarada, K. ., Jithendar, P. ., Maddileti, T. ., & Kumar, G. N. K. . (2023). A Deep Learning Based Enhancing the Power by Reducing the Harmonics in Grid Connected Inverters. Distributed Generation &Amp; Alternative Energy Journal, 39(01), 137–164. https://doi.org/10.13052/dgaej2156-3306.3916

Issue

2024: Vol 39 Iss 1

Section

Digital twin for Accelerating Sustainability in Energy Automation and Smart Grid