Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things
The increasing use of Internet of Things (IoTs) has brought more advantages in supplying power to electric vehicles (EVs). With the help of IoTs, EVs can be charged more easily by mobile charging stations (MCSs) compared with the fixed charging stations (FCSs). However, previous works in the managem...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8466586/ |
| _version_ | 1819163001307004928 |
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| author | Huwei Chen Zhou Su Yilong Hui Hui Hui |
| author_facet | Huwei Chen Zhou Su Yilong Hui Hui Hui |
| author_sort | Huwei Chen |
| collection | DOAJ |
| description | The increasing use of Internet of Things (IoTs) has brought more advantages in supplying power to electric vehicles (EVs). With the help of IoTs, EVs can be charged more easily by mobile charging stations (MCSs) compared with the fixed charging stations (FCSs). However, previous works in the management of power supply in FCSs have not been properly applied in MCSs, e.g., dynamic of EV users' arrival and variable power supply from MCSs in IoTs. In this paper, we study how to manage MCSs' supply power in IoTs under the condition that MCSs supply multiple kinds of power. First, considering the randomness of power supply and dynamic of EV users' arrival, we develop the dynamic framework of power supply and the economic model. Then, aiming to maximize the long-term average profits of MCSs, a stochastic optimization problem is formulated to decide the optimal strategy of power management. Based on the Lyapunov optimization theory, a Lyapunov-based online distributed algorithm is proposed to obtain the optimal solutions. Meanwhile, the performance of our proposed algorithm is analyzed and simulation results validate the effectiveness of our proposal. |
| first_indexed | 2024-12-22T17:37:11Z |
| format | Article |
| id | doaj.art-e20f70adb1f8479db4fec3f8388796be |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T17:37:11Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e20f70adb1f8479db4fec3f8388796be2022-12-21T18:18:30ZengIEEEIEEE Access2169-35362018-01-016535095352010.1109/ACCESS.2018.28689378466586Dynamic Charging Optimization for Mobile Charging Stations in Internet of ThingsHuwei Chen0Zhou Su1https://orcid.org/0000-0002-6518-3130Yilong Hui2Hui Hui3School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, ChinaSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai, ChinaSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai, ChinaSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai, ChinaThe increasing use of Internet of Things (IoTs) has brought more advantages in supplying power to electric vehicles (EVs). With the help of IoTs, EVs can be charged more easily by mobile charging stations (MCSs) compared with the fixed charging stations (FCSs). However, previous works in the management of power supply in FCSs have not been properly applied in MCSs, e.g., dynamic of EV users' arrival and variable power supply from MCSs in IoTs. In this paper, we study how to manage MCSs' supply power in IoTs under the condition that MCSs supply multiple kinds of power. First, considering the randomness of power supply and dynamic of EV users' arrival, we develop the dynamic framework of power supply and the economic model. Then, aiming to maximize the long-term average profits of MCSs, a stochastic optimization problem is formulated to decide the optimal strategy of power management. Based on the Lyapunov optimization theory, a Lyapunov-based online distributed algorithm is proposed to obtain the optimal solutions. Meanwhile, the performance of our proposed algorithm is analyzed and simulation results validate the effectiveness of our proposal.https://ieeexplore.ieee.org/document/8466586/Internet of Thingselectric vehiclesmobile charging stationsLyapunov optimizationonline distributed algorithm |
| spellingShingle | Huwei Chen Zhou Su Yilong Hui Hui Hui Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things IEEE Access Internet of Things electric vehicles mobile charging stations Lyapunov optimization online distributed algorithm |
| title | Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things |
| title_full | Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things |
| title_fullStr | Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things |
| title_full_unstemmed | Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things |
| title_short | Dynamic Charging Optimization for Mobile Charging Stations in Internet of Things |
| title_sort | dynamic charging optimization for mobile charging stations in internet of things |
| topic | Internet of Things electric vehicles mobile charging stations Lyapunov optimization online distributed algorithm |
| url | https://ieeexplore.ieee.org/document/8466586/ |
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