Paper Title:Optimal swapping battery strategies for urban charging stations Research and/or engineering questions / objective (100 words): Swapping batteries represents a potential solution for urban charging stations by offering a fast delivery instead of few hours of service. Moreover, the buffer of batteries can be also used to store the energy so electricity can be extracted from the net or from solar panels at the appropriate moments, becoming a control problem well suited for optimal control theory (OCT). The present work proposes a control strategy based on dynamic programming (DP) to optimize the charging procedure of batteries in a swapping urban station with solar panels. Methodology (150 words):The proposed algorithm uses a prediction of the expected traffic at the area, as well as the expected cost of the electricity in the net. Traffic density has been collected in the city of Valencia at various days to feed the algorithm with a reasonable prediction of expected demand, while real-time data of the electricity cost is used to feed the control proposed. A simplified model with only three states and one control has been used for running the DP and obtain an optimal action matrix that defines the station control criteria along the day. The model estimates the evolution of discharged and charged batteries with an average charging ratio based on the input of the system, i.e. the number of batteries switched on for charging at each time step. Results (150 words): A realistic model that computes the state of charge of each battery in the station as well as the cue of vehicles evolution is used for simulation purposes, while a Poisson distribution of traffic is used to simulate the batteries demand uncertainty in a conventional day. Simulations are devoted to analysing the potential of the optimal control to reduce the electricity cost, as well as the benefits of using solar energy in a station. Results demonstrate that feeding the control system with a prediction of traffic and electricity cost might save up to 7.8% of electricity cost with affordable punctual cues. Regarding solar energy, a minimum irradiated surface of 20m2 is suggested to deal with a station with an average capacity of 250 vehicles per day which represents a saving of 2% of energy. Limitations of this study (100 words): Although the study is focused on motorcycle battery swapping, the swapping technology can be also applied to other type of vehicles. However, the battery design should allow a reliable swapping which limits the technology to light vehicles. Moreover, the optimization depends on a traffic prediction which might not be affordable in some conditions. What does the paper offer that is new in the field in comparison to other works of the author? (100 words) Although dynamic programming has been successfully applied to many control problems, the application to swapping urban stations with a simplified model is novel and contributes to the state of the art in the field. Moreover, the use of traffic density data measured in Valencia offers an interesting and realistic analysis of the potential of such technology. Conclusions (100 words): - Swapping technology can be used to reduce the delivery time of batteries in urban charging stations, but it can also represent an energy buffer to reduce the cost of electricity and the carbon footprint. - Traffic density prediction can be used to optimize the charging procedure by optimal control theory, such as dynamic programming. - Solar panels can be used to reduce the energy consumption, but additional sun exposed surface would be required for potential benefits.
Dr. Pau Bares, Lecturer, Universitat Politècnica de València