Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model
In today’s transportation sector, the growing number of electric vehicles (EVs) is progressively replacing petroleum-fueled vehicles, which are also expected to minimize greenhouse gas emissions. The main problem with EVs is the requirement of charging energy, which is fed through distrib...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9877797/ |
| _version_ | 1811267054451294208 |
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| author | Habib Ur Rahman Habib Asad Waqar Bashar Sakeen Farhan Tanveer Ahmad Mehdi Jahangiri Moustafa Magdi Ismail Parvez Ahmad Asad Abbas Yun-Su Kim |
| author_facet | Habib Ur Rahman Habib Asad Waqar Bashar Sakeen Farhan Tanveer Ahmad Mehdi Jahangiri Moustafa Magdi Ismail Parvez Ahmad Asad Abbas Yun-Su Kim |
| author_sort | Habib Ur Rahman Habib |
| collection | DOAJ |
| description | In today’s transportation sector, the growing number of electric vehicles (EVs) is progressively replacing petroleum-fueled vehicles, which are also expected to minimize greenhouse gas emissions. The main problem with EVs is the requirement of charging energy, which is fed through distribution network, while simultaneously feeding already connected load. The EV’s integration with the distribution network will overload the network due to EV’s charging load, which will eventually trip the power system protection. In this context, it is necessary to minimize power losses, improve voltage profile with sustainable power supply network. Therefore, optimal placement of EVs is required in the distribution network. Conventionally, researchers have used DGs to minimize power losses and improve voltage profile. In this paper, authors analyzed the effect of EV’s integration with simultaneous placement of distributed generations (DGs). The integration of EVs with higher penetration of DGs is cumbersome due to higher power losses and voltage variances that are outside allowable boundaries. The optimal placement of EVs into the distribution system with higher penetration of DGs is proposed in this paper using a battle royale optimization (BRO) algorithm. Since it is a new problem on CIGRE network which is not discussed before. Hence, the authors compared results with three most famous algorithms namely genetic algorithm (GA), particle swarm optimization (PSO), and accelerated PSO (APSO). The optimization problem is developed as a multi-objective function while decreasing active and reactive power losses, and minimising maximum voltage deviation index. The studied distribution network is the CIGRE 14-bus medium voltage (MV) distribution network. Three case studies are taken in which EVs are integrated in two scenarios with optimally sized and located DGs systems in the CIGRE distribution network using MATLAB. Case-1 includes simple network with DGs integration. Case-2 includes EVs only in the simple network, and case-3 finally includes EVs and DGs for optimal placement with minimum losses. The placement of the EVs results in a decrease in power losses and voltage deviation indices. The bus voltages of case-2, on the other hand, stay unchanged when the EVs are integrated. Case 3 with BRO showed the large reduction in power losses owing to the addition of EVs to the distribution network with DGs (from 19.98 kW, and 19.89 kVar to 2.54 kW, and 3.35 kVar). |
| first_indexed | 2024-04-12T20:55:31Z |
| format | Article |
| id | doaj.art-313b5b89ccf842499a085635f7ac0dd5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T20:55:31Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-313b5b89ccf842499a085635f7ac0dd52022-12-22T03:17:00ZengIEEEIEEE Access2169-35362022-01-0110959499596910.1109/ACCESS.2022.32043119877797Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark ModelHabib Ur Rahman Habib0https://orcid.org/0000-0003-2640-3185Asad Waqar1https://orcid.org/0000-0001-6500-0990Bashar Sakeen Farhan2https://orcid.org/0000-0002-5746-8638Tanveer Ahmad3Mehdi Jahangiri4https://orcid.org/0000-0001-6803-8804Moustafa Magdi Ismail5Parvez Ahmad6https://orcid.org/0000-0003-1409-3175Asad Abbas7Yun-Su Kim8https://orcid.org/0000-0002-6803-929XDepartment of Electrical Engineering, Faculty of Electrical and Electronics Engineering, University of Engineering and Technology Taxila, Taxila, PakistanElectrical Department, Engineering Collage, AL-Iraqia University, Ministry of Higher Education, Baghdad, IraqElectrical Department, Engineering Collage, AL-Iraqia University, Ministry of Higher Education, Baghdad, IraqDepartment of Advanced Information Technology, Kyushu University, Fukuoka, JapanEnergy Research Center, Islamic Azad University, Shahrekord Branch, Shahrekord, IranElectrical Engineering Department, Faculty of Engineering, Minia University, Minya, EgyptSchool of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Electrical Engineering, Bahria University, Islamabad, PakistanGraduate School of Energy Convergence, Gwangju Institute of Science and Technology (GIST), Gwangju, South KoreaIn today’s transportation sector, the growing number of electric vehicles (EVs) is progressively replacing petroleum-fueled vehicles, which are also expected to minimize greenhouse gas emissions. The main problem with EVs is the requirement of charging energy, which is fed through distribution network, while simultaneously feeding already connected load. The EV’s integration with the distribution network will overload the network due to EV’s charging load, which will eventually trip the power system protection. In this context, it is necessary to minimize power losses, improve voltage profile with sustainable power supply network. Therefore, optimal placement of EVs is required in the distribution network. Conventionally, researchers have used DGs to minimize power losses and improve voltage profile. In this paper, authors analyzed the effect of EV’s integration with simultaneous placement of distributed generations (DGs). The integration of EVs with higher penetration of DGs is cumbersome due to higher power losses and voltage variances that are outside allowable boundaries. The optimal placement of EVs into the distribution system with higher penetration of DGs is proposed in this paper using a battle royale optimization (BRO) algorithm. Since it is a new problem on CIGRE network which is not discussed before. Hence, the authors compared results with three most famous algorithms namely genetic algorithm (GA), particle swarm optimization (PSO), and accelerated PSO (APSO). The optimization problem is developed as a multi-objective function while decreasing active and reactive power losses, and minimising maximum voltage deviation index. The studied distribution network is the CIGRE 14-bus medium voltage (MV) distribution network. Three case studies are taken in which EVs are integrated in two scenarios with optimally sized and located DGs systems in the CIGRE distribution network using MATLAB. Case-1 includes simple network with DGs integration. Case-2 includes EVs only in the simple network, and case-3 finally includes EVs and DGs for optimal placement with minimum losses. The placement of the EVs results in a decrease in power losses and voltage deviation indices. The bus voltages of case-2, on the other hand, stay unchanged when the EVs are integrated. Case 3 with BRO showed the large reduction in power losses owing to the addition of EVs to the distribution network with DGs (from 19.98 kW, and 19.89 kVar to 2.54 kW, and 3.35 kVar).https://ieeexplore.ieee.org/document/9877797/Accelerated PSO (APSO)battle royale optimization (BRO) algorithmCIGRE 14-bus MV distribution networkdistributed generatorsgenetic algorithm (GA)multi-objective optimization |
| spellingShingle | Habib Ur Rahman Habib Asad Waqar Bashar Sakeen Farhan Tanveer Ahmad Mehdi Jahangiri Moustafa Magdi Ismail Parvez Ahmad Asad Abbas Yun-Su Kim Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model IEEE Access Accelerated PSO (APSO) battle royale optimization (BRO) algorithm CIGRE 14-bus MV distribution network distributed generators genetic algorithm (GA) multi-objective optimization |
| title | Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model |
| title_full | Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model |
| title_fullStr | Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model |
| title_full_unstemmed | Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model |
| title_short | Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model |
| title_sort | analysis of optimal integration of evs and dgs into cigre x2019 s mv benchmark model |
| topic | Accelerated PSO (APSO) battle royale optimization (BRO) algorithm CIGRE 14-bus MV distribution network distributed generators genetic algorithm (GA) multi-objective optimization |
| url | https://ieeexplore.ieee.org/document/9877797/ |
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