Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm
Electric Vehicle (EV) charging station placement problem is a facility location problem. The EV charging station placement problem concerns about the total coverage in traffic network, the system losses and node voltage deviations in electric distribution system. To address the loss reduction and vo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9760414/ |
| _version_ | 1828344936145092608 |
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| author | S. Muthukannan D. Karthikaikannan |
| author_facet | S. Muthukannan D. Karthikaikannan |
| author_sort | S. Muthukannan |
| collection | DOAJ |
| description | Electric Vehicle (EV) charging station placement problem is a facility location problem. The EV charging station placement problem concerns about the total coverage in traffic network, the system losses and node voltage deviations in electric distribution system. To address the loss reduction and voltage profile improvement, the distribution systems are normally equipped with shunt capacitors for reactive power compensation. In this paper mathematical model comprising three objective functions, maximization of coverage and minimization of loss and node voltage deviations subjected to constraints is proposed for the simultaneous placement of EV charging stations and shunt capacitors. The control variables for optimization are the rating and location of charging stations and shunt capacitors. A hybrid optimization algorithm (PSO-DS) combining particle swarm optimization algorithm and direct search method is proposed for the solution of the mathematical model. The performance of PSO-DS is justified by comparing it with other state-of-the-art algorithms in solving the standard benchmark functions. Simulations are carried out on a 33-bus distribution system and a 25-node traffic network system to determine the different planning strategy for the placement of charging stations. |
| first_indexed | 2024-04-14T00:04:19Z |
| format | Article |
| id | doaj.art-e5697f1d05954b7eb253f2a0e3d6abe9 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-14T00:04:19Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e5697f1d05954b7eb253f2a0e3d6abe92022-12-22T02:23:35ZengIEEEIEEE Access2169-35362022-01-0110480884810110.1109/ACCESS.2022.31688309760414Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization AlgorithmS. Muthukannan0D. Karthikaikannan1https://orcid.org/0000-0002-1149-0151SASTRA Deemed to be University, Thanjavur, Tamil Nadu, IndiaSchool of Electrical and Electronics Engineering, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, IndiaElectric Vehicle (EV) charging station placement problem is a facility location problem. The EV charging station placement problem concerns about the total coverage in traffic network, the system losses and node voltage deviations in electric distribution system. To address the loss reduction and voltage profile improvement, the distribution systems are normally equipped with shunt capacitors for reactive power compensation. In this paper mathematical model comprising three objective functions, maximization of coverage and minimization of loss and node voltage deviations subjected to constraints is proposed for the simultaneous placement of EV charging stations and shunt capacitors. The control variables for optimization are the rating and location of charging stations and shunt capacitors. A hybrid optimization algorithm (PSO-DS) combining particle swarm optimization algorithm and direct search method is proposed for the solution of the mathematical model. The performance of PSO-DS is justified by comparing it with other state-of-the-art algorithms in solving the standard benchmark functions. Simulations are carried out on a 33-bus distribution system and a 25-node traffic network system to determine the different planning strategy for the placement of charging stations.https://ieeexplore.ieee.org/document/9760414/Charging stationelectric vehicle (EV)facility location problemparticle swarm optimization (PSO)direct search (DS) |
| spellingShingle | S. Muthukannan D. Karthikaikannan Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm IEEE Access Charging station electric vehicle (EV) facility location problem particle swarm optimization (PSO) direct search (DS) |
| title | Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm |
| title_full | Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm |
| title_fullStr | Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm |
| title_full_unstemmed | Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm |
| title_short | Multiobjective Planning Strategy for the Placement of Electric-Vehicle Charging Stations Using Hybrid Optimization Algorithm |
| title_sort | multiobjective planning strategy for the placement of electric vehicle charging stations using hybrid optimization algorithm |
| topic | Charging station electric vehicle (EV) facility location problem particle swarm optimization (PSO) direct search (DS) |
| url | https://ieeexplore.ieee.org/document/9760414/ |
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