Abstract :
The energy demand of electric vehicles (EVs) is expected to take a significant share in the electricity market in the future. As the charging power of EVs is much higher than any other individual household appliances, the power demand modeling of EVs needs to be analyzed. In this study, the charging profile of EVs is modeled by combining two probabilistic functions together: state of charge (SOC) before charging and start charging time (SCT). Analysis study shows that beta distribution function is selected as the more appropriate approach to represent the initial SOC of an EV. Furthermore, two charging scenarios are considered to model SCTs. Finally, demand profiles are worked out and compared between different scenarios, and among different penetration levels of EVs. The structure of this paper is presented as below. Two charging scenarios (methods) are introduced firstly. Next, fitness analysis of Beta distribution is performed. Thirdly, the SOC of EVs before charging is modeled. Fourthly, the SCT of EVs for each charging method is modeled. Fifthly, the power demand of an EV is modeled. Finally, the calculated new typical load profiles with EVs´ charging are presented.
Keywords :
electric vehicles; power markets; statistical distributions; EV charging power; SCT; SOC; beta distribution function; electric vehicles residential energy demand profile modeling; electricity market; power demand modeling; probabilistic functions; probabilistic model; start charging time; state of charge; typical load profiles; Batteries; Distribution functions; Gaussian distribution; Load modeling; Power demand; Probabilistic logic; System-on-a-chip; Electric vehicles; Load modeling; Probabilistic methods;
