Optimal scheduling for charging and discharging electric vehicles

With the advancement in automobile and battery technology, Electric Vehicles (EV) have been made widely available commercially. With EV’s main source of energy coming from drawing electricity from the utility grid, it can be predicted that in the future, as the trend of consumers driving EVs increas...

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Main Author: Chua, Kunshuan
Other Authors: Soh Cheong Boon
Format: Final Year Project
Language:English
Published: 2018
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Online Access:http://hdl.handle.net/10356/74802
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-748022023-07-07T16:18:18Z Optimal scheduling for charging and discharging electric vehicles Chua, Kunshuan Soh Cheong Boon School of Electrical and Electronic Engineering DRNTU::Engineering With the advancement in automobile and battery technology, Electric Vehicles (EV) have been made widely available commercially. With EV’s main source of energy coming from drawing electricity from the utility grid, it can be predicted that in the future, as the trend of consumers driving EVs increases, the amount of load demand EVs have on the grid increases significantly as well. In this project, a comparison of optimization methods to improve on EV charging scheduling will be done. With the use of MATLAB as the software platform to create mathematical programming models for EVs optimal charging scheduling and Gurobi solver will be used to solve the optimization problem. The comparison will be done on charging EVs without scheduling, a global optimization with centralized control scheduling and a local optimization with sliding window scheduling algorithm. A decentralized charging scheduling algorithm based on game theory with the objective of minimizing system energy cost and in which, also reducing Peak to Average Ratio, will also be discussed. All in all, while a global centralized control charging schedule produces the best solution and helps to reshape the base load of the grid, it is unrealistic to apply the model. Local optimization using local controllers with sliding window scheduling algorithm produce similar solution when compared with centralized control and much better than charging EVs without scheduling scheme. A decentralized charging scheduling with game theory provides an alternative by minimizing energy cost and hence, reducing Peak to Average Ratio of the total load demand, including EV, and optimize local variables turn by turn, in which, produce a global optimal solution while providing consumers incentive for doing so. Bachelor of Engineering 2018-05-24T03:07:51Z 2018-05-24T03:07:51Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74802 en Nanyang Technological University 65 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Chua, Kunshuan
Optimal scheduling for charging and discharging electric vehicles
description With the advancement in automobile and battery technology, Electric Vehicles (EV) have been made widely available commercially. With EV’s main source of energy coming from drawing electricity from the utility grid, it can be predicted that in the future, as the trend of consumers driving EVs increases, the amount of load demand EVs have on the grid increases significantly as well. In this project, a comparison of optimization methods to improve on EV charging scheduling will be done. With the use of MATLAB as the software platform to create mathematical programming models for EVs optimal charging scheduling and Gurobi solver will be used to solve the optimization problem. The comparison will be done on charging EVs without scheduling, a global optimization with centralized control scheduling and a local optimization with sliding window scheduling algorithm. A decentralized charging scheduling algorithm based on game theory with the objective of minimizing system energy cost and in which, also reducing Peak to Average Ratio, will also be discussed. All in all, while a global centralized control charging schedule produces the best solution and helps to reshape the base load of the grid, it is unrealistic to apply the model. Local optimization using local controllers with sliding window scheduling algorithm produce similar solution when compared with centralized control and much better than charging EVs without scheduling scheme. A decentralized charging scheduling with game theory provides an alternative by minimizing energy cost and hence, reducing Peak to Average Ratio of the total load demand, including EV, and optimize local variables turn by turn, in which, produce a global optimal solution while providing consumers incentive for doing so.
author2 Soh Cheong Boon
author_facet Soh Cheong Boon
Chua, Kunshuan
format Final Year Project
author Chua, Kunshuan
author_sort Chua, Kunshuan
title Optimal scheduling for charging and discharging electric vehicles
title_short Optimal scheduling for charging and discharging electric vehicles
title_full Optimal scheduling for charging and discharging electric vehicles
title_fullStr Optimal scheduling for charging and discharging electric vehicles
title_full_unstemmed Optimal scheduling for charging and discharging electric vehicles
title_sort optimal scheduling for charging and discharging electric vehicles
publishDate 2018
url http://hdl.handle.net/10356/74802
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