Modeling and simulation for electric taxi charging/swapping load

This paper firstly proposesa method for modeling charging/swapping load distribution of electric taxi. With this method ， Monte Carlo Method and Dijkstra Algorithm are adopted to simulate the electric taxi's operation behavior based on the analysis of its operation characteristics. Then facility optimization model is proposed to minimize the life circle cost (LCC) of charging/swapping facilities and the time value of electric taxi under the constraints of queuing model and the price spread between oil and electricity. Finally, a practical example is carried out to demonstrate the performance of the modeling method and facility optimization model.

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Modeling and simulation for electric taxi charging/swapping load

Cited by 5 publications

References 3 publications

Multiple agents and reinforcement learning for modelling charging loads of electric taxis

Multiple agents and reinforcement learning for modelling charging loads of electric taxis

Multi-PET Cooperative Autonomous Navigation Based on Multi-agent Deep Deterministic Policy Gradient

Modeling for electric taxi load and optimization model for charging/swapping facilities of electric taxi

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