Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station
The potential of Electric Vehicles (EVs) to decarbonize the transportation industry has attracted a lot of attention in recent years in response to growing environmental concerns. Electric Vehicle Charging Stations (EVCSs) need to be properly located for widespread EV integration. The distr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Faculty of Technical Sciences in Cacak
2024-01-01
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| Series: | Serbian Journal of Electrical Engineering |
| Subjects: | |
| Online Access: | https://doiserbia.nb.rs/img/doi/1451-4869/2024/1451-48692401001P.pdf |
| _version_ | 1797215488938344448 |
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| author | Pratap Arvind Tiwari Prabhakar Maurya Rakesh Singh Bindeshwar |
| author_facet | Pratap Arvind Tiwari Prabhakar Maurya Rakesh Singh Bindeshwar |
| author_sort | Pratap Arvind |
| collection | DOAJ |
| description | The potential of Electric Vehicles (EVs) to decarbonize the transportation
industry has attracted a lot of attention in recent years in response to
growing environmental concerns. Electric Vehicle Charging Stations (EVCSs)
need to be properly located for widespread EV integration. The distribution
system is facing additional challenges due to inclusion of EVCS. The adverse
impacts of EVCS on the Radial Distribution Network (RDN) may be minimized
using Distributed Generations (DGs) or Distribution Static Compensators
(DSTATCOMs) or by reconfiguring the network. This paper uses a novel
optimization technique to solve the problem of simultaneous optimal
placement of EVCS with network reconfiguration and optimal planning (siting
and sizing) of DGs and DSTATCOMs. The multiple objective functions are
considered in order to minimize the active power losses, the voltage
deviation, the investment costs for DGs and DSTATCOMs, and to increase the
voltage stability of the system. A novel meta-heuristic Cheetah Optimization
Algorithm (COA) is used to solve the optimization problem. To examine the
effectiveness of the suggested strategy on 33-bus and 136-bus networks,
several scenarios of simultaneous incorporation of EVCS, DG, and DSTATCOM
installations with network reconfiguration are taken into consideration. The
COA results are also compared to the results of grey wolf optimization and
genetic algorithms. |
| first_indexed | 2024-04-24T11:30:52Z |
| format | Article |
| id | doaj.art-59967e50f20d44418e3a512188e4a0db |
| institution | Directory Open Access Journal |
| issn | 1451-4869 2217-7183 |
| language | English |
| last_indexed | 2024-04-24T11:30:52Z |
| publishDate | 2024-01-01 |
| publisher | Faculty of Technical Sciences in Cacak |
| record_format | Article |
| series | Serbian Journal of Electrical Engineering |
| spelling | doaj.art-59967e50f20d44418e3a512188e4a0db2024-04-10T10:18:37ZengFaculty of Technical Sciences in CacakSerbian Journal of Electrical Engineering1451-48692217-71832024-01-0121113710.2298/SJEE2401001P1451-48692401001PCheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging stationPratap Arvind0Tiwari Prabhakar1Maurya Rakesh2Singh Bindeshwar3Madan Mohan Malaviya University of Technology, Department of Electrical Engineering, Gorakhpur, IndiaMadan Mohan Malaviya University of Technology, Department of Electrical Engineering, Gorakhpur, IndiaSardar Vallabhbhai National Institute of Technology, Department of Electrical Engineering, Surat, IndiaKamla Nehru Institute of Technology, Department of Electrical Engineering, Sultanpur, IndiaThe potential of Electric Vehicles (EVs) to decarbonize the transportation industry has attracted a lot of attention in recent years in response to growing environmental concerns. Electric Vehicle Charging Stations (EVCSs) need to be properly located for widespread EV integration. The distribution system is facing additional challenges due to inclusion of EVCS. The adverse impacts of EVCS on the Radial Distribution Network (RDN) may be minimized using Distributed Generations (DGs) or Distribution Static Compensators (DSTATCOMs) or by reconfiguring the network. This paper uses a novel optimization technique to solve the problem of simultaneous optimal placement of EVCS with network reconfiguration and optimal planning (siting and sizing) of DGs and DSTATCOMs. The multiple objective functions are considered in order to minimize the active power losses, the voltage deviation, the investment costs for DGs and DSTATCOMs, and to increase the voltage stability of the system. A novel meta-heuristic Cheetah Optimization Algorithm (COA) is used to solve the optimization problem. To examine the effectiveness of the suggested strategy on 33-bus and 136-bus networks, several scenarios of simultaneous incorporation of EVCS, DG, and DSTATCOM installations with network reconfiguration are taken into consideration. The COA results are also compared to the results of grey wolf optimization and genetic algorithms.https://doiserbia.nb.rs/img/doi/1451-4869/2024/1451-48692401001P.pdfnetwork reconfigurationdistributed generationelectric vehicle charging stationreal power loss reductiondistribution static compensator |
| spellingShingle | Pratap Arvind Tiwari Prabhakar Maurya Rakesh Singh Bindeshwar Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station Serbian Journal of Electrical Engineering network reconfiguration distributed generation electric vehicle charging station real power loss reduction distribution static compensator |
| title | Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station |
| title_full | Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station |
| title_fullStr | Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station |
| title_full_unstemmed | Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station |
| title_short | Cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of DG and DSTATCOM with electric vehicle charging station |
| title_sort | cheetah optimization algorithm for simultaneous optimal network reconfiguration and allocation of dg and dstatcom with electric vehicle charging station |
| topic | network reconfiguration distributed generation electric vehicle charging station real power loss reduction distribution static compensator |
| url | https://doiserbia.nb.rs/img/doi/1451-4869/2024/1451-48692401001P.pdf |
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