Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems
The increasing number of electric vehicles (EVs) in today’s transport sector is gradually leading to the phasing out of petroleum-based vehicles. However, the rapid deployment of EVs largely depends on the coordinated and fast expansion of EV charging stations (EVCSs). The integration of...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9537756/ |
| _version_ | 1819107671319511040 |
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| author | Willy Stephen Tounsi Fokui Michael J. Saulo Livingstone Ngoo |
| author_facet | Willy Stephen Tounsi Fokui Michael J. Saulo Livingstone Ngoo |
| author_sort | Willy Stephen Tounsi Fokui |
| collection | DOAJ |
| description | The increasing number of electric vehicles (EVs) in today’s transport sector is gradually leading to the phasing out of petroleum-based vehicles. However, the rapid deployment of EVs largely depends on the coordinated and fast expansion of EV charging stations (EVCSs). The integration of EVCSs in the modern distribution network characterized by increased penetration of randomly distributed photovoltaic (PV) systems is challenging as they can lead to excessive power losses and voltage deviations beyond acceptable limits. In this paper, a hybrid bacterial foraging optimization algorithm and particle swarm optimization (BFOA-PSO) technique is proposed for the optimal placement of EVCSs into the distribution network with high penetration of randomly distributed rooftop PV systems. The optimization problem is formulated as a multi-objective problem minimizing active and reactive power losses, average voltage deviation index, and maximizing voltage stability index. The IEEE 69 node distribution network is used as the case network. The simulation is done using MATLAB to integrate the EVCSs in five cases of randomly sized and placed PV systems in the distribution network. For all five cases, a minimal increase in power losses is recorded with minor changes in the voltage deviation and stability indices due to the placement of the EVCSs. But for the voltages of nodes 29 to 48, the other node voltages remain unchanged upon placement of the EVCSs. The largest increase in power losses due to the EVCSs being brought into the network with PVs was noticed in case 3 (from 142.27kW, and 62.90kVar to 147.65kW, and 72.48kVar). |
| first_indexed | 2024-12-22T02:57:44Z |
| format | Article |
| id | doaj.art-64bff00935e14de3a6f50123634684e2 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T02:57:44Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-64bff00935e14de3a6f50123634684e22022-12-21T18:41:13ZengIEEEIEEE Access2169-35362021-01-01913239713241110.1109/ACCESS.2021.31128479537756Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic SystemsWilly Stephen Tounsi Fokui0https://orcid.org/0000-0001-7398-159XMichael J. Saulo1Livingstone Ngoo2Department of Electrical Engineering, Technology and Innovation, Pan African University Institute for Basic Sciences, Nairobi, KenyaDepartment of Electrical and Electronic Engineering, Technical University of Mombasa, Mombasa, KenyaDepartment of Electrical and Communications Engineering, Multimedia University of Kenya, Nairobi, KenyaThe increasing number of electric vehicles (EVs) in today’s transport sector is gradually leading to the phasing out of petroleum-based vehicles. However, the rapid deployment of EVs largely depends on the coordinated and fast expansion of EV charging stations (EVCSs). The integration of EVCSs in the modern distribution network characterized by increased penetration of randomly distributed photovoltaic (PV) systems is challenging as they can lead to excessive power losses and voltage deviations beyond acceptable limits. In this paper, a hybrid bacterial foraging optimization algorithm and particle swarm optimization (BFOA-PSO) technique is proposed for the optimal placement of EVCSs into the distribution network with high penetration of randomly distributed rooftop PV systems. The optimization problem is formulated as a multi-objective problem minimizing active and reactive power losses, average voltage deviation index, and maximizing voltage stability index. The IEEE 69 node distribution network is used as the case network. The simulation is done using MATLAB to integrate the EVCSs in five cases of randomly sized and placed PV systems in the distribution network. For all five cases, a minimal increase in power losses is recorded with minor changes in the voltage deviation and stability indices due to the placement of the EVCSs. But for the voltages of nodes 29 to 48, the other node voltages remain unchanged upon placement of the EVCSs. The largest increase in power losses due to the EVCSs being brought into the network with PVs was noticed in case 3 (from 142.27kW, and 62.90kVar to 147.65kW, and 72.48kVar).https://ieeexplore.ieee.org/document/9537756/Electric vehiclecharging stationphotovoltaichybrid BFOA-PSOoptimal placement |
| spellingShingle | Willy Stephen Tounsi Fokui Michael J. Saulo Livingstone Ngoo Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems IEEE Access Electric vehicle charging station photovoltaic hybrid BFOA-PSO optimal placement |
| title | Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems |
| title_full | Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems |
| title_fullStr | Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems |
| title_full_unstemmed | Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems |
| title_short | Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network With Randomly Distributed Rooftop Photovoltaic Systems |
| title_sort | optimal placement of electric vehicle charging stations in a distribution network with randomly distributed rooftop photovoltaic systems |
| topic | Electric vehicle charging station photovoltaic hybrid BFOA-PSO optimal placement |
| url | https://ieeexplore.ieee.org/document/9537756/ |
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