Performance of Gradient-Based Optimizer on Charging Station Placement Problem / H. Essam, D. Sanchari, D. A. Oliva Navarro [et al.]

Уровень набора: MathematicsАльтернативный автор-лицо: Essam, H., Houssein;Sanchari, D., Deb;Oliva Navarro, D. A., specialist in the field of informatics and computer technology, Professor of Tomsk Polytechnic University, 1983-, Diego Alberto;Hegazy, R., Rezk;Hesham, A., Alhumade;Mokhtar, S., SaidКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет, Инженерная школа информационных технологий и робототехники, Отделение информационных технологийЯзык: английский.Резюме или реферат: 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..Примечания о наличии в документе библиографии/указателя: [References: 54 tit.].Тематика: электронный ресурс | труды учёных ТПУ | gradient-based optimizer (GBO) | charging station placement problem | electric vehicles (EVs) | metaheuristic algorithms | оптимизаторы | электромобили | метаэвристические алгоритмы Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 54 tit.]

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.

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