Developing and Analysing a Photovoltaic (PV) Renewable Energy Source with Particle Swarm Optimization (PSO) Algorithm for Battery Management in Grid Environment Power Quality
Renewable energy is the most viable option for rural electrification due to its widespread availability. In the previous work balance between power generation and load power, with batteries serving as a backup source for both Photovoltaic (PV) and wind energy are having drawbacks such as maintains a...
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| Published in | SN computer science Vol. 5; no. 8; p. 1172 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
Springer Nature Singapore
14.12.2024
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2661-8907 2662-995X 2661-8907 |
| DOI | 10.1007/s42979-024-03549-y |
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| Abstract | Renewable energy is the most viable option for rural electrification due to its widespread availability. In the previous work balance between power generation and load power, with batteries serving as a backup source for both Photovoltaic (PV) and wind energy are having drawbacks such as maintains a constancy between source and load request, even in the face of sudden changes in load and fluctuations in PV and wind power generation. To solve the problem micro grid comprising of a Photovoltaic (PV) array battery energy storage are developed in this work. One of the primary sources of renewable energy is photovoltaic energy, which can vary significantly depending on temperature, cell type, and irradiance levels. In wind power generation, the rotor's accessibility allows for the Doubly Fed Induction Generator (DFIG) to regulate the stator power, with the overall power being derived from the rotor. Maximum Power Point Tracking (MPPT) is based on Particle Swarm Optimization (PSO) and procedures the PV module's current output in relation to the battery voltage. It calculates the power maximum output of the element and changes optimum voltage for charging the battery with the maximum amount of power. In a hybrid system, there are two buses and AC bus and a DC bus, a single AC bus, with an AC/AC converter connecting the wind turbine and a DC/AC converter connecting the PV to the AC bus. The DC bus is used to connect sources with a DC current, while the AC bus is used for sources with an alternating current. This micro grid is simulated using MATLAB/Simulink tool and gain better power quality output. |
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| AbstractList | Renewable energy is the most viable option for rural electrification due to its widespread availability. In the previous work balance between power generation and load power, with batteries serving as a backup source for both Photovoltaic (PV) and wind energy are having drawbacks such as maintains a constancy between source and load request, even in the face of sudden changes in load and fluctuations in PV and wind power generation. To solve the problem micro grid comprising of a Photovoltaic (PV) array battery energy storage are developed in this work. One of the primary sources of renewable energy is photovoltaic energy, which can vary significantly depending on temperature, cell type, and irradiance levels. In wind power generation, the rotor's accessibility allows for the Doubly Fed Induction Generator (DFIG) to regulate the stator power, with the overall power being derived from the rotor. Maximum Power Point Tracking (MPPT) is based on Particle Swarm Optimization (PSO) and procedures the PV module's current output in relation to the battery voltage. It calculates the power maximum output of the element and changes optimum voltage for charging the battery with the maximum amount of power. In a hybrid system, there are two buses and AC bus and a DC bus, a single AC bus, with an AC/AC converter connecting the wind turbine and a DC/AC converter connecting the PV to the AC bus. The DC bus is used to connect sources with a DC current, while the AC bus is used for sources with an alternating current. This micro grid is simulated using MATLAB/Simulink tool and gain better power quality output. |
| ArticleNumber | 1172 |
| Author | Arulmurugan, V. S. Bharathidasan, P. Balaji, K. Rajeswari, C. |
| Author_xml | – sequence: 1 givenname: V. S. surname: Arulmurugan fullname: Arulmurugan, V. S. organization: Department of Electrical and Electronics Engineering, Shree Venkateshwara Hi-Tech Engineering College – sequence: 2 givenname: C. surname: Rajeswari fullname: Rajeswari, C. email: chandranrajes@gmail.com organization: Department of Electrical and Electronics Engineering, Excel Engineering College – sequence: 3 givenname: P. surname: Bharathidasan fullname: Bharathidasan, P. organization: Department of Electrical and Electronics Engineering, Excel Engineering College – sequence: 4 givenname: K. surname: Balaji fullname: Balaji, K. organization: Department of Electrical and Electronics Engineering, Shree Venkateshwara Hi-Tech Engineering College |
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| Cites_doi | 10.1016/j.rineng.2022.100422 10.1016/j.renene.2020.09.008 10.34259/ijew.22.905131143 10.47392/IRJAEM.2024.0137 10.1080/23311916.2022.2044576 10.1109/ACCESS.2021.3059687 10.20998/2074-272X.2023.2.07 10.1109/JSYST.2020.2985164 10.1109/INDISCON50162.2020.00047 10.1016/j.ijepes.2021.107805 10.1007/s42835-023-01679-6 10.1016/j.ijepes.2022.108455 10.1080/03772063.2021.1920481 10.52783/jes.3462 10.1016/j.est.2022.105865 10.1109/ACCESS.2024.3378749 10.1007/s42452-020-3118-0 10.3389/fenrg.2023.1169172 |
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| Copyright | The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Copyright Springer Nature B.V. Dec 2024 |
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| Keywords | Wind Doubly Fed Induction Generator (DFIG) Photovoltaic (PV) Maximum Power Point Tracking (MPPT) Battery energy management |
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| SubjectTerms | Advances in Computational Approaches for Image Processing Algorithms Alternating current Alternative energy sources Batteries Cloud Applications and Network Security Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data buses Data Structures and Information Theory Direct current Distributed generation Electric potential Electrical loads Electricity Hybrid systems Induction generators Information Systems and Communication Service Irradiance Maximum power tracking Optimization Original Research Particle swarm optimization Pattern Recognition and Graphics Photovoltaic cells Power management Radiation Renewable energy sources Rotors Software Engineering/Programming and Operating Systems Solar energy Vision Voltage Wind power generation Wind turbines Wireless Networks |
| Title | Developing and Analysing a Photovoltaic (PV) Renewable Energy Source with Particle Swarm Optimization (PSO) Algorithm for Battery Management in Grid Environment Power Quality |
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