Performance of Gradient-Based Optimizer on Charging Station Placement Problem
The electrification of transportation is necessary due to the expanded fuel cost and change in climate. The management of charging stations and their easy accessibility are the main concerns for receipting and accepting Electric Vehicles (EVs). The distribution network reliability, voltage stability...
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| Format: | Article |
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MDPI AG
2021-11-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/21/2821 |
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| author | Essam H. Houssein Sanchari Deb Diego Oliva Hegazy Rezk Hesham Alhumade Mokhtar Said |
| author_facet | Essam H. Houssein Sanchari Deb Diego Oliva Hegazy Rezk Hesham Alhumade Mokhtar Said |
| author_sort | Essam H. Houssein |
| collection | DOAJ |
| description | The electrification of transportation is necessary due to the expanded fuel cost and change in climate. The management of charging stations and their easy accessibility are the main concerns for receipting and accepting Electric Vehicles (EVs). The distribution network reliability, voltage stability and power loss are the main factors in designing the optimum placement and management strategy of a charging station. The planning of a charging stations is a complicated problem involving roads and power grids. The Gradient-based optimizer (GBO) used for solving the charger placement problem is tested in this work. A good balance between exploitation and exploration is achieved by the GBO. Furthermore, the likelihood of becoming stuck in premature convergence and local optima is rare in a GBO. Simulation results establish the efficacy and robustness of the GBO in solving the charger placement problem as compared to other metaheuristics such as a genetic algorithm, differential evaluation and practical swarm optimizer. |
| first_indexed | 2024-03-10T05:57:13Z |
| format | Article |
| id | doaj.art-cffd26b532b945c9bce23d5dce49f580 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T05:57:13Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-cffd26b532b945c9bce23d5dce49f5802023-11-22T21:19:21ZengMDPI AGMathematics2227-73902021-11-01921282110.3390/math9212821Performance of Gradient-Based Optimizer on Charging Station Placement ProblemEssam H. Houssein0Sanchari Deb1Diego Oliva2Hegazy Rezk3Hesham Alhumade4Mokhtar Said5Faculty of Computers and Information, Minia University, Minia 61519, EgyptSchool of Engineering, University of Warwick, Coventry CV4 7AL, UKDivisión de Electrónica y Computación, Universidad de Guadalajara, CUCEI, Av. Revolución 1500, Guadalajara 44430, MexicoCollege of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11911, Saudi ArabiaChemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi ArabiaElectrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 43518, EgyptThe electrification of transportation is necessary due to the expanded fuel cost and change in climate. The management of charging stations and their easy accessibility are the main concerns for receipting and accepting Electric Vehicles (EVs). The distribution network reliability, voltage stability and power loss are the main factors in designing the optimum placement and management strategy of a charging station. The planning of a charging stations is a complicated problem involving roads and power grids. The Gradient-based optimizer (GBO) used for solving the charger placement problem is tested in this work. A good balance between exploitation and exploration is achieved by the GBO. Furthermore, the likelihood of becoming stuck in premature convergence and local optima is rare in a GBO. Simulation results establish the efficacy and robustness of the GBO in solving the charger placement problem as compared to other metaheuristics such as a genetic algorithm, differential evaluation and practical swarm optimizer.https://www.mdpi.com/2227-7390/9/21/2821gradient-based optimizer (GBO)charging station placement problemelectric vehicles (EVs)metaheuristic algorithms |
| spellingShingle | Essam H. Houssein Sanchari Deb Diego Oliva Hegazy Rezk Hesham Alhumade Mokhtar Said Performance of Gradient-Based Optimizer on Charging Station Placement Problem Mathematics gradient-based optimizer (GBO) charging station placement problem electric vehicles (EVs) metaheuristic algorithms |
| title | Performance of Gradient-Based Optimizer on Charging Station Placement Problem |
| title_full | Performance of Gradient-Based Optimizer on Charging Station Placement Problem |
| title_fullStr | Performance of Gradient-Based Optimizer on Charging Station Placement Problem |
| title_full_unstemmed | Performance of Gradient-Based Optimizer on Charging Station Placement Problem |
| title_short | Performance of Gradient-Based Optimizer on Charging Station Placement Problem |
| title_sort | performance of gradient based optimizer on charging station placement problem |
| topic | gradient-based optimizer (GBO) charging station placement problem electric vehicles (EVs) metaheuristic algorithms |
| url | https://www.mdpi.com/2227-7390/9/21/2821 |
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