دانلود رایگان مقاله تحلیل عملکرد مدل تصادفی ایستگاه شارژ خودرو الکتریکی

Abstract

Wide-spread infrastructures for electric vehicle battery charging stations are essential in order to significantly increase the implementation of electric vehicles (EVs) in the foreseeable future. Therefore, we propose a stochastic model and charge scheduling methods for an EV battery charging system. We utilize a flexible Poisson process with a hidden Markov chain for modeling the complexity of the time-varying behavior of the EV stream into the system. Relevant random factors and constraints, which include parking times, requested amounts of electricity, the number of parking lots (charging facilities), and maximal demand level, are considered within the proposed stochastic model. Performance measures for the proposed charge scheduling are analytically derived by obtaining stationary distributions of states concerning the number of inbound EVs, waiting time distributions, and the joint distributions of parking time and electricity charged during random parking times.

5 Concluding remarks

We proposed a realistic stochastic model for EV battery charging stations and analyzed performance measures of two typical charge scheduling methods: the first-in-first-served (FIFO) and the processor sharing (PS). After obtaining stationary distribution for steady states and some conditional distributions, we then derived two performance measures for the charge scheduling methods: the probability of fully charging within the system and the rational expectation of the charged energy given the parking time and requested energy. Furthermore, we employed a flexible Poisson process of a Markov-modulated Poisson process for an incoming stream of EVs under the proposed stochastic model, which incorporates the time-varying behavior of EV arrivals into the parking lot.