Model predictive control for on–off charging of electrical vehicles in smart grids
Abstract Over the next decade, a massive number of plug‐in electric vehicles (PEVs) will need to be integrated into current power grids. This is likely to give rise to unmanageable fluctuations in power demand and unacceptable deviations in voltage. These negative impacts are difficult to mitigate b...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-06-01
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| Series: | IET Electrical Systems in Transportation |
| Online Access: | https://doi.org/10.1049/els2.12010 |
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| author | Ye Shi Hoang D. Tuan Andrey V. Savkin H. Vincent Poor |
| author_facet | Ye Shi Hoang D. Tuan Andrey V. Savkin H. Vincent Poor |
| author_sort | Ye Shi |
| collection | DOAJ |
| description | Abstract Over the next decade, a massive number of plug‐in electric vehicles (PEVs) will need to be integrated into current power grids. This is likely to give rise to unmanageable fluctuations in power demand and unacceptable deviations in voltage. These negative impacts are difficult to mitigate because PEVs connect and disconnect from the grid randomly and each type of PEVs has different charging profiles. This paper presents a solution to these problems that involves coordination of power grid control and PEV charging. The proposed strategy minimises the overall costs of charging and power generation in meeting future increases in PEV charging demand and the operational constraints of the power grid. The solution is based on an on–off PEV charging strategy that is easy and convenient to implement online. The joint coordination problem is formulated by a mixed integer non‐linear programming (MINP) with binary charging and continuous voltage variables and is solved by a highly novel computational algorithm. Its online implementation is based on a new model predictive control method that is free from prior assumptions about PEVs' arrival and charging information. Comprehensive simulations are provided to demonstrate the efficiency and practicality of the proposed methods. |
| format | Article |
| id | doaj-art-10aee71402244dffb683e112af48690c |
| institution | Kabale University |
| issn | 2042-9738 2042-9746 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Electrical Systems in Transportation |
| spelling | doaj-art-10aee71402244dffb683e112af48690c2025-02-03T01:29:38ZengWileyIET Electrical Systems in Transportation2042-97382042-97462021-06-0111212113310.1049/els2.12010Model predictive control for on–off charging of electrical vehicles in smart gridsYe Shi0Hoang D. Tuan1Andrey V. Savkin2H. Vincent Poor3School of Information Science and Technology Shanghaitech University Shanghai ChinaSchool of Electrical and Data Engineering University of Technology Sydney Broadway New South Wales AustraliaSchool of Electrical Engineering and Telecommunications The University of New South Wales Sydney New South Wales AustraliaDepartment of Electrical Engineering Princeton University Princeton New Jersey USAAbstract Over the next decade, a massive number of plug‐in electric vehicles (PEVs) will need to be integrated into current power grids. This is likely to give rise to unmanageable fluctuations in power demand and unacceptable deviations in voltage. These negative impacts are difficult to mitigate because PEVs connect and disconnect from the grid randomly and each type of PEVs has different charging profiles. This paper presents a solution to these problems that involves coordination of power grid control and PEV charging. The proposed strategy minimises the overall costs of charging and power generation in meeting future increases in PEV charging demand and the operational constraints of the power grid. The solution is based on an on–off PEV charging strategy that is easy and convenient to implement online. The joint coordination problem is formulated by a mixed integer non‐linear programming (MINP) with binary charging and continuous voltage variables and is solved by a highly novel computational algorithm. Its online implementation is based on a new model predictive control method that is free from prior assumptions about PEVs' arrival and charging information. Comprehensive simulations are provided to demonstrate the efficiency and practicality of the proposed methods.https://doi.org/10.1049/els2.12010 |
| spellingShingle | Ye Shi Hoang D. Tuan Andrey V. Savkin H. Vincent Poor Model predictive control for on–off charging of electrical vehicles in smart grids IET Electrical Systems in Transportation |
| title | Model predictive control for on–off charging of electrical vehicles in smart grids |
| title_full | Model predictive control for on–off charging of electrical vehicles in smart grids |
| title_fullStr | Model predictive control for on–off charging of electrical vehicles in smart grids |
| title_full_unstemmed | Model predictive control for on–off charging of electrical vehicles in smart grids |
| title_short | Model predictive control for on–off charging of electrical vehicles in smart grids |
| title_sort | model predictive control for on off charging of electrical vehicles in smart grids |
| url | https://doi.org/10.1049/els2.12010 |
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