Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs
Recent years have seen a marked increase in the world's energy needs. Numerous studies have been conducted to examine distributed generation (DG) utilizing renewable energy sources (RESs) in order to address this need. The number of environmental problems that are raised by the usage of traditi...
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| Format: | Article |
| Language: | English |
| Published: |
Yanbu Industrial College
2024-01-01
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| Series: | Yanbu Journal of Engineering and Science |
| Online Access: | https://doi.org/10.53370/001c.91483 |
| _version_ | 1797367574602711040 |
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| author | Mohamed I. Mosaad |
| author_facet | Mohamed I. Mosaad |
| author_sort | Mohamed I. Mosaad |
| collection | DOAJ |
| description | Recent years have seen a marked increase in the world's energy needs. Numerous studies have been conducted to examine distributed generation (DG) utilizing renewable energy sources (RESs) in order to address this need. The number of environmental problems that are raised by the usage of traditional power plants is also decreased by these renewable sources. The ideal position and size of the RESs-DG significantly influence the bus voltage profile, power quality, and efficiency of Radial Distribution Systems (RDS) because of power losses. In this study, the use of wind energy systems as a DG source in RDS is investigated. One of the most common RESs used as DG sources, the ideal location and size for wind system, was chosen to demonstrate this enquiry. The goal of this optimization work, which used the Arithmetic Optimization Algorithm (AOA), was to increase system efficiency by minimizing power losses and improving the voltage profile and power quality. Two widely used RDS, including the IEEE 31 and 69 bus systems, have been used to evaluate how well the recommended technique has been implemented. Genetic Algorithm (GA) is offered to examine the efficacy of the recommended AOA. The findings show that the used AOA approach can pinpoint the appropriate size and positioning of a wind farm in order to reduce power loss, enhance voltage profile, and outperform other existing tactics with superiority over GA. |
| first_indexed | 2024-03-08T17:19:19Z |
| format | Article |
| id | doaj.art-e7398abd21f54bd2b7e745860499792c |
| institution | Directory Open Access Journal |
| issn | 1658-5321 |
| language | English |
| last_indexed | 2024-03-08T17:19:19Z |
| publishDate | 2024-01-01 |
| publisher | Yanbu Industrial College |
| record_format | Article |
| series | Yanbu Journal of Engineering and Science |
| spelling | doaj.art-e7398abd21f54bd2b7e745860499792c2024-01-03T08:31:48ZengYanbu Industrial CollegeYanbu Journal of Engineering and Science1658-53212024-01-01202Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSsMohamed I. MosaadRecent years have seen a marked increase in the world's energy needs. Numerous studies have been conducted to examine distributed generation (DG) utilizing renewable energy sources (RESs) in order to address this need. The number of environmental problems that are raised by the usage of traditional power plants is also decreased by these renewable sources. The ideal position and size of the RESs-DG significantly influence the bus voltage profile, power quality, and efficiency of Radial Distribution Systems (RDS) because of power losses. In this study, the use of wind energy systems as a DG source in RDS is investigated. One of the most common RESs used as DG sources, the ideal location and size for wind system, was chosen to demonstrate this enquiry. The goal of this optimization work, which used the Arithmetic Optimization Algorithm (AOA), was to increase system efficiency by minimizing power losses and improving the voltage profile and power quality. Two widely used RDS, including the IEEE 31 and 69 bus systems, have been used to evaluate how well the recommended technique has been implemented. Genetic Algorithm (GA) is offered to examine the efficacy of the recommended AOA. The findings show that the used AOA approach can pinpoint the appropriate size and positioning of a wind farm in order to reduce power loss, enhance voltage profile, and outperform other existing tactics with superiority over GA.https://doi.org/10.53370/001c.91483 |
| spellingShingle | Mohamed I. Mosaad Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs Yanbu Journal of Engineering and Science |
| title | Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs |
| title_full | Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs |
| title_fullStr | Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs |
| title_full_unstemmed | Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs |
| title_short | Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs |
| title_sort | using arithmetic optimization algorithm to allocate and size wind energy systems in rdss |
| url | https://doi.org/10.53370/001c.91483 |
| work_keys_str_mv | AT mohamedimosaad usingarithmeticoptimizationalgorithmtoallocateandsizewindenergysystemsinrdss |