Simulator for EV Charging Systems in Flexibility Markets
Rizvi, Syed Hamza Abbas (2025)
2025
Tietojenkäsittelyopin maisteriohjelma - Master's Programme in Computer Science
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2025-12-31
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-2025123112299
https://urn.fi/URN:NBN:fi:tuni-2025123112299
Tiivistelmä
The rise in the adoption of EVs across the world has grown significantly over the years. This has made the EV charging environment more complex and brought challenges on the capacity of the grid. The increasing integration of EVs into power systems creates new opportunities for demand-side flexibility, particularly through Vehicle-to-Grid (V2G) interactions. An optimal charging solution is needed for this complex environment, along with a low-cost way to model and study the system before real-world implementation. Simulation provides a practical approach to represent complex real-world systems and evaluate their behaviour in a controlled setting.
This thesis presents the design and implementation of an electric vehicle (EV) charging simulation for flexibility market scenarios using the SimCES platform. The research aims to develop a simulation that allows users to charge their vehicles with minimal effort by eliminating the need for detailed initial charging inputs, while giving users control over charging and discharging by defining user preferences. Two research questions are addressed. The first investigates the limitations and challenges encountered when implementing an EV V2G charging simulation using the SimCES platform. The second examines how a V2G EV charging scenario can be effectively simulated using the SimCES platform.
To address these questions, a V2G-based simulation containing User, Station, Grid and V2G Controller component was designed and implemented. The V2G Controller component included a simulation algorithm responsible for managing charging and discharging behaviour based on grid load, and user-defined preferences. Several example simulation scenarios were tested, covering different charging and discharging conditions and cost configurations.
The results show that the developed system successfully supports EV charging and V2G simulations. The simulation demonstrates correct component interaction, energy flow behaviour, and pricing-based decision-making. At the same time, the study identified platform-level and debugging limitations that decreased developer productivity. The research suggested future work to improve SimCES platform as well as extending the simulation algorithm. Overall, this work demonstrates the feasibility of using the SimCES platform for EV charging simulations and provides a foundation for future research and development in flexibility-based energy systems.
This thesis presents the design and implementation of an electric vehicle (EV) charging simulation for flexibility market scenarios using the SimCES platform. The research aims to develop a simulation that allows users to charge their vehicles with minimal effort by eliminating the need for detailed initial charging inputs, while giving users control over charging and discharging by defining user preferences. Two research questions are addressed. The first investigates the limitations and challenges encountered when implementing an EV V2G charging simulation using the SimCES platform. The second examines how a V2G EV charging scenario can be effectively simulated using the SimCES platform.
To address these questions, a V2G-based simulation containing User, Station, Grid and V2G Controller component was designed and implemented. The V2G Controller component included a simulation algorithm responsible for managing charging and discharging behaviour based on grid load, and user-defined preferences. Several example simulation scenarios were tested, covering different charging and discharging conditions and cost configurations.
The results show that the developed system successfully supports EV charging and V2G simulations. The simulation demonstrates correct component interaction, energy flow behaviour, and pricing-based decision-making. At the same time, the study identified platform-level and debugging limitations that decreased developer productivity. The research suggested future work to improve SimCES platform as well as extending the simulation algorithm. Overall, this work demonstrates the feasibility of using the SimCES platform for EV charging simulations and provides a foundation for future research and development in flexibility-based energy systems.