A Monotone Approximate Dynamic Programming Approach for the Stochastic Scheduling, Allocation, and Inventory Replenishment Problem: Applications to Drone and Electric Vehicle Battery Swap Stations

There is a growing interest in using electric vehicles (EVs) and drones for many applications. However, battery-oriented issues, including range anxiety and battery degradation, impede adoption. Battery swap stations are one alternative to reduce these concerns that allow the swap of depleted for full batteries in minutes. We consider the problem of deriving actions at a battery swap station when explicitly considering the uncertain arrival of swap demand, battery degradation, and replacement. We model the operations at a battery swap station using a finite horizon Markov decision process model for the stochastic scheduling, allocation, and inventory replenishment problem (SAIRP), which determines when and how many batteries are charged, discharged, and replaced over time. We present theoretical proofs for the monotonicity of the value function and monotone structure of an optimal policy for special SAIRP cases. Because of the curses of dimensionality, we develop a new monotone approximate dynamic programming (ADP) method, which intelligently initializes a value function approximation using regression. In computational tests, we demonstrate the superior performance of the new regression-based monotone ADP method compared with exact methods and other monotone ADP methods. Furthermore, with the tests, we deduce policy insights for drone swap stations.

Impact of Charging on Battery Life and Battery Degradation in Electric Vehicles

Electrical vehicles are the future of the world; hence, there is a necessity to pave the way for the upcoming technology and to ensure its contribution to the society fairly. Nevertheless, if the EVs completely replaced the fuel-based cars, more EV charging stations would be needed which might develop overconsumption of the main grid power causing remarkable instability. Consequently, the micro grids become the solution to this problem, in which they are defined as relatively small networks of energy sources and loads at the distribution level that aim to provide electricity to remote locations where the charging stations are located. In this chapter, the EV is considered as a load to the micro grid indirectly through the EV charging stations. Thus, micro grid loads will be retrieved from experimental data of an actual prototype electric vehicle to reflect on the battery degradation in a micro-grid connected system.