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Parameter Improved Particle Swarm Optimization Based Direct-Current Vector Control Strategy for Solar PV SystemNAMMALVAR, P.   , RAMKUMAR, S. |
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Author keywords
solar energy, particle swarm optimization, optimal control, power conditioning, microgrids
References keywords
power(22), control(10), systems(7), energy(7), grid(6), current(6), voltage(5), system(5), generation(5), connected(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 105 - 112
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01013
Web of Science Accession Number: 000426449500013
SCOPUS ID: 85043243615
Abstract
This paper projects Parameter Improved Particle Swarm Optimization (PIPSO) based direct current vector control technology for the integration of photovoltaic array in an AC micro-grid to enhance the system performance and stability. A photovoltaic system incorporated with AC micro-grid is taken as the pursuit of research study. The test system features two power converters namely, PV side converter which consists of DC-DC boost converter with Perturbation and Observe (P&O) MPPT control to reap most extreme power from the PV array, and grid side converter which consists of Grid Side-Voltage Source Converter (GS-VSC) with proposed direct current vector control strategy. The gain of the proposed controller is chosen from a set of three values obtained using apriori test and tuned through the PIPSO algorithm so that the Integral of Time multiplied Absolute Error (ITAE) between the actual and the desired DC link capacitor voltage reaches a minimum and allows the system to extract maximum power from PV system, whereas the existing d-q control strategy is found to perform slowly to control the DC link voltage under varying solar insolation and load fluctuations. From simulation results, it is evident that the proposed optimal control technique provides robust control and improved efficiency. |
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[1] Tri-band Impedance Matching Network Design Using Particle Swarm Optimization Algorithm, ULKER, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 19, 2019.
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[2] Photosynthetic rate prediction model of newborn leaves verified by core fluorescence parameters, Zhang, Pan, Zhang, Zhongxiong, Li, Bin, Zhang, Haihui, Hu, Jin, Zhao, Juan, Scientific Reports, ISSN 2045-2322, Issue 1, Volume 10, 2020.
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[3] Efficient Solar Integrated Doubly Fed Induction Generator for Wind Energy Harnessing, Kumar, Arjun, Shivashankar, , Ram, Bhagwan S., Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), ISSN 2352-0965, Issue 5, Volume 13, 2020.
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[4] Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system, Roslan, M. F., Al-Shetwi, Ali Q., Hannan, M. A., Ker, P. J., Zuhdi, A. W. M., Wang, Long, PLOS ONE, ISSN 1932-6203, Issue 12, Volume 15, 2020.
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[5] Grasshopper optimization algorithm tuned maximum power point tracking for solar photovoltaic systems, Subramanian, Annapoorani, Raman, Jayaparvathy, Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, Issue 9, Volume 12, 2021.
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[6] An Anomaly Data Mining Method for Mass Sensor Networks Using Improved PSO Algorithm Based on Spark Parallel Framework, Yuan, Jingzhen, Journal of Grid Computing, ISSN 1570-7873, Issue 2, Volume 18, 2020.
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[7] Certain investigations of ANFIS assisted CPHO algorithm tuned MPPT controller for PV arrays under partial shading conditions, Pachaivannan, Nammalvar, Subburam, Ramkumar, Padmanaban, Meganathan, Subramanian, Annapoorani, Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, Issue 10, Volume 12, 2021.
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[8] Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 22, 2022.
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[9] Power Optimization in Hybrid Renewable Energy Standalone System using SMC-ANFIS, KALVINATHAN, V., CHITRA, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 22, 2022.
Digital Object Identifier: 10.4316/AECE.2022.03008 [CrossRef] [Full text]
[10] An Improved Hybrid Clustering Algorithm Based on Particle Swarm Optimization and K-means, Liu, Shuying, Zou, Yanfei, IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, Issue 1, Volume 750, 2020.
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[11] An approach to the utilization of grid integration to analyze the performance and quality of solar photovoltaic model, Jeelani, Syed Hamim, Puviarasi, R., M., Chilambarasan, Shinde, Sarita Santaji, Surakasi, Raviteja, Sharma, Vipin, Madhavarao, S., Sudhakar, M., Mohanavel, V., Energy Reports, ISSN 2352-4847, Issue , 2022.
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[12] Fuzzy tuned real and reactive power regulation in GC-VSI for PV systems, Pachaivannan, Nammalvar, Subburam, Ramkumar, Ramkumar, Umadevi, Padmanaban, Meganathan, International Journal of Electronics, ISSN 0020-7217, Issue 3, Volume 110, 2023.
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[13] Crowded plant height optimisation algorithm tuned maximum power point tracking for grid integrated solar power conditioning system, Pachaivannan, Nammalvar, Subburam, Ramkumar, Ramkumar, Umadevi, Kasinathan, Padmanathan, IET Renewable Power Generation, ISSN 1752-1416, Issue 12, Volume 13, 2019.
Digital Object Identifier: 10.1049/iet-rpg.2018.5053 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
