Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm
A combined PSO-ANN control is proposed in this work to achieve the best voltage regulation in a distribution network, based on quick response and minimum average voltage deviation. The Jordanian Sabha Distribution Network (JSDN) with PV Farms is used as a real case study to examine a voltage variati...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/16/1/360 |
| _version_ | 1797625930169974784 |
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| author | Jasim Ghaeb Samer Salah Firas Obeidat |
| author_facet | Jasim Ghaeb Samer Salah Firas Obeidat |
| author_sort | Jasim Ghaeb |
| collection | DOAJ |
| description | A combined PSO-ANN control is proposed in this work to achieve the best voltage regulation in a distribution network, based on quick response and minimum average voltage deviation. The Jordanian Sabha Distribution Network (JSDN) with PV Farms is used as a real case study to examine a voltage variation issue. Two STATCOMs are used to solve the voltage fluctuation problem on the network’s three buses. The required reactive powers of STATCOMs for voltage regulation during load variation are calculated in offline mode using a particle swarm optimization (PSO) algorithm. Despite its high performance in solving voltage issue in the JSDN network, the PSO controller is unable to react promptly to dynamic changes in the network. An artificial neural network (ANN) is therefore suggested as an online mode controller for quick and efficient voltage regulation. The offline dataset is used to train the ANN for online voltage regulation utilizing the MATLAB-Tool Box. At an average voltage deviation (AVD) of 1.168%; (whereas an acceptable one is 6%), the results revealed the proposed ANN controller’s competence for voltage regulation in the distribution network. Moreover, to find the best position based on an efficient voltage regulation, many sites for STATCOMs are taken into consideration. |
| first_indexed | 2024-03-11T10:03:26Z |
| format | Article |
| id | doaj.art-eba2bbd54a81428182d146ff8f3e7e84 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T10:03:26Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-eba2bbd54a81428182d146ff8f3e7e842023-11-16T15:18:04ZengMDPI AGEnergies1996-10732022-12-0116136010.3390/en16010360Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV FarmJasim Ghaeb0Samer Salah1Firas Obeidat2Mechatronics Engineering Department, Faculty of Engineering, Philadelphia University, Amman 19392, JordanMechatronics Engineering Department, Faculty of Engineering, Philadelphia University, Amman 19392, JordanRenewable Energy Engineering, Faculty of Engineering, Philadelphia University, Amman 19392, JordanA combined PSO-ANN control is proposed in this work to achieve the best voltage regulation in a distribution network, based on quick response and minimum average voltage deviation. The Jordanian Sabha Distribution Network (JSDN) with PV Farms is used as a real case study to examine a voltage variation issue. Two STATCOMs are used to solve the voltage fluctuation problem on the network’s three buses. The required reactive powers of STATCOMs for voltage regulation during load variation are calculated in offline mode using a particle swarm optimization (PSO) algorithm. Despite its high performance in solving voltage issue in the JSDN network, the PSO controller is unable to react promptly to dynamic changes in the network. An artificial neural network (ANN) is therefore suggested as an online mode controller for quick and efficient voltage regulation. The offline dataset is used to train the ANN for online voltage regulation utilizing the MATLAB-Tool Box. At an average voltage deviation (AVD) of 1.168%; (whereas an acceptable one is 6%), the results revealed the proposed ANN controller’s competence for voltage regulation in the distribution network. Moreover, to find the best position based on an efficient voltage regulation, many sites for STATCOMs are taken into consideration.https://www.mdpi.com/1996-1073/16/1/360renewable energysmart gridsdistribution networksSTATCOMsPV systems |
| spellingShingle | Jasim Ghaeb Samer Salah Firas Obeidat Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm Energies renewable energy smart grids distribution networks STATCOMs PV systems |
| title | Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm |
| title_full | Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm |
| title_fullStr | Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm |
| title_full_unstemmed | Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm |
| title_short | Intelligent Control for Voltage Regulation in the Distribution Network Equipped with PV Farm |
| title_sort | intelligent control for voltage regulation in the distribution network equipped with pv farm |
| topic | renewable energy smart grids distribution networks STATCOMs PV systems |
| url | https://www.mdpi.com/1996-1073/16/1/360 |
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