Electric Vehicle Charging Load Management : Algorithm and Modelling Perspectives
Simolin, Toni (2022)
Tampere University
2022
Tieto- ja sähkötekniikan tohtoriohjelma - Doctoral Programme in Computing and Electrical Engineering
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Väitöspäivä
2022-09-02
Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-03-2505-3
https://urn.fi/URN:ISBN:978-952-03-2505-3
Tiivistelmä
Electric vehicles are seen as the key solution for emission-free private transportation. The share of electric vehicles is small at the time of writing this thesis, but their share is increasing rapidly. The charging demand is consequently also increasing at a fast pace. Uncontrolled charging has been seen as an inefficient solution in a large-scale implementation; thus, there is more pressure to develop intelligent and efficient charging infrastructure solutions.
This thesis assesses electric vehicle charging from two perspectives: charging load modelling and control algorithm development. It is necessary to ensure that tests are carried out reliably in order to develop and evaluate the operation of different charging algorithms. Electric vehicle charging, especially a large-scale implementation, often must be examined using simulations; thus, emphasis must be given to the simulation details. Different solutions may be necessary in different scenarios in charging algorithm development. The focus in this thesis is on charging mode 3 of the international charging standard IEC 61851. This thesis divides control algorithms into three components to advance the algorithm development: Capacity determination, Capacity allocation, and Capacity usage rate correction. Each component corresponds to managing a certain objective in a charging control algorithm.
One of the key findings of this thesis relates to a phenomenon called “non-ideal charging characteristics”: how to take them into account in charging load modelling and in charging control algorithms. The non-ideal charging characteristics have often been neglected in charging load modelling-related studies in the scientific literature, yet it is shown that they can notably influence the results. A charging current measurement-based simulation model is developed to take the non-idealities into account in the charging load modelling, and its accuracy is validated using hardware-in-the-loop simulations. Additionally, an algorithm feature called “charging characteristics expectation” is developed to take the non-idealities into account in the charging control algorithms. The feature allows a control algorithm to track the potential mismatches between the charging current limits set by the charging stations and the actual charging currents to overcome the related issues. Additionally, this thesis assesses peak load limitation-based charging control solutions. It is concluded that home charging demand can likely be fulfilled in most cases in Finnish households without a need to increase peak loads of the whole real estate. Furthermore, to consider varying charging demands of electric vehicle users, different charging control prioritization principles, such as mobility requirement, battery energy status, or price-based, are investigated.
This thesis assesses electric vehicle charging from two perspectives: charging load modelling and control algorithm development. It is necessary to ensure that tests are carried out reliably in order to develop and evaluate the operation of different charging algorithms. Electric vehicle charging, especially a large-scale implementation, often must be examined using simulations; thus, emphasis must be given to the simulation details. Different solutions may be necessary in different scenarios in charging algorithm development. The focus in this thesis is on charging mode 3 of the international charging standard IEC 61851. This thesis divides control algorithms into three components to advance the algorithm development: Capacity determination, Capacity allocation, and Capacity usage rate correction. Each component corresponds to managing a certain objective in a charging control algorithm.
One of the key findings of this thesis relates to a phenomenon called “non-ideal charging characteristics”: how to take them into account in charging load modelling and in charging control algorithms. The non-ideal charging characteristics have often been neglected in charging load modelling-related studies in the scientific literature, yet it is shown that they can notably influence the results. A charging current measurement-based simulation model is developed to take the non-idealities into account in the charging load modelling, and its accuracy is validated using hardware-in-the-loop simulations. Additionally, an algorithm feature called “charging characteristics expectation” is developed to take the non-idealities into account in the charging control algorithms. The feature allows a control algorithm to track the potential mismatches between the charging current limits set by the charging stations and the actual charging currents to overcome the related issues. Additionally, this thesis assesses peak load limitation-based charging control solutions. It is concluded that home charging demand can likely be fulfilled in most cases in Finnish households without a need to increase peak loads of the whole real estate. Furthermore, to consider varying charging demands of electric vehicle users, different charging control prioritization principles, such as mobility requirement, battery energy status, or price-based, are investigated.
Kokoelmat
- Väitöskirjat [4850]