Dynamic modeling of electric vehicle movable loads based on driving pattern analysis

With the electrification of transportation, a growing number of electric vehicles (EVs) will emerge as new loads in power system. Comparing to traditional stationary loads, EV charging loads can be regarded as movable loads connecting among buses of a power system. The random moving and charging process of EVs is inherited from the stochastic driving pattern of EV drivers. Moreover, EVs closely link power system and transportation system. An effective traffic management will alleviate the impact of massive EV charging loads on power system. This paper propose a technique to model the stochastic moving feature of EV charging loads based on driving pattern analysis. Graph theory is used to bridge the transportation and transmission network. The spatial and temporal distributions of expected nodal EV charging loads are determined by Monte Carlo simulation (MCS). The system studies show that number of daily trips plays a key role in EV charging loads modeling.