An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization
Today, DC microgrids provide the possibility to provide proper management and control for energy storage systems, generation sources, consumers, and other power components. The droop control method is one of the most common methods used in DC microgrids. One of the main challenges in the droop contr...
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| Format: | Article |
| Language: | English |
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Bilijipub publisher
2023-09-01
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| Series: | Advances in Engineering and Intelligence Systems |
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| Online Access: | https://aeis.bilijipub.com/article_180453_73a9faf370b7c5c4a9c3ff2da0cfb88c.pdf |
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| _version_ | 1823856419428892672 |
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| author | Muhammad Hammad Saeed Sajid Iqbal Madni Sohail Usman Akram |
| author_facet | Muhammad Hammad Saeed Sajid Iqbal Madni Sohail Usman Akram |
| author_sort | Muhammad Hammad Saeed |
| collection | DOAJ |
| description | Today, DC microgrids provide the possibility to provide proper management and control for energy storage systems, generation sources, consumers, and other power components. The droop control method is one of the most common methods used in DC microgrids. One of the main challenges in the droop control method is that it is not possible to share the current and regulate the voltage at the same time in this method. To overcome the weaknesses of the voltage drop control method, the paper presents an adaptive control method that can be used to share the current and adjust the voltage accordingly based on the load condition. When the load in the microgrid is low, the output current is lower than the maximum limit and so current sharing is not a difficult challenge. When the load increases to the point where the output current exceeds the maximum limit then current sharing becomes very important. Using this method, this problem is solved by increasing the total gain decrease. For more accuracy, a gray-wolf algorithm has been used to optimize the droop gains. The performance of the proposed method has been verified through a set of simulations, and the results confirm the effectiveness of the proposed method for the DC microgrid. |
| format | Article |
| id | doaj-art-50863f8b6b69464c94869ea01596a0cd |
| institution | Kabale University |
| issn | 2821-0263 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Bilijipub publisher |
| record_format | Article |
| series | Advances in Engineering and Intelligence Systems |
| spelling | doaj-art-50863f8b6b69464c94869ea01596a0cd2025-02-12T08:47:20ZengBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02632023-09-0100203506010.22034/aeis.2023.406515.1110180453An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf OptimizationMuhammad Hammad Saeed0Sajid Iqbal1Madni Sohail2Usman Akram3China Three Gorges University, Yichang, Hubei, 443005, ChinaUniversity of Engineering and Technology, Lahore, Punjab, 39161, PakistanUniversity of Southern Denmark, Sønderborg, 6400, DenmarkUniversity of Southern Denmark, Sønderborg, 6400, DenmarkToday, DC microgrids provide the possibility to provide proper management and control for energy storage systems, generation sources, consumers, and other power components. The droop control method is one of the most common methods used in DC microgrids. One of the main challenges in the droop control method is that it is not possible to share the current and regulate the voltage at the same time in this method. To overcome the weaknesses of the voltage drop control method, the paper presents an adaptive control method that can be used to share the current and adjust the voltage accordingly based on the load condition. When the load in the microgrid is low, the output current is lower than the maximum limit and so current sharing is not a difficult challenge. When the load increases to the point where the output current exceeds the maximum limit then current sharing becomes very important. Using this method, this problem is solved by increasing the total gain decrease. For more accuracy, a gray-wolf algorithm has been used to optimize the droop gains. The performance of the proposed method has been verified through a set of simulations, and the results confirm the effectiveness of the proposed method for the DC microgrid.https://aeis.bilijipub.com/article_180453_73a9faf370b7c5c4a9c3ff2da0cfb88c.pdfdc microgridadaptive controldroopcurrent sharingvoltage regulation |
| spellingShingle | Muhammad Hammad Saeed Sajid Iqbal Madni Sohail Usman Akram An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization Advances in Engineering and Intelligence Systems dc microgrid adaptive control droop current sharing voltage regulation |
| title | An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization |
| title_full | An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization |
| title_fullStr | An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization |
| title_full_unstemmed | An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization |
| title_short | An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization |
| title_sort | optimal adaptive control of dc microgrid with the aim of accurate current sharing and voltage regulation according to the load variation and gray wolf optimization |
| topic | dc microgrid adaptive control droop current sharing voltage regulation |
| url | https://aeis.bilijipub.com/article_180453_73a9faf370b7c5c4a9c3ff2da0cfb88c.pdf |
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