The future adoption of electric vehicles (EV) as the main means of commuting will put an additional stress on the distribution grid; the level where EVs are mainly expected to be charged. Estimation of the EV charging influence on the distribution grid is a critical task for distribution system operators (DSO) in order to plan for grid reinforcement and to avoid service failure. Due to the unpredictable nature of daily human activities, stochastic modeling for daily EVs’ owner behavior and residential power consumption is needed. In our study a new estimation model for the EV power demand during the charging process is developed to accurately estimate the charging demand, which is combined with daily household power consumption loads based on real life measurements to estimate the total demand in the system. This demand can be applied to the standard IEEE 69 distribution system and can quantify the influence of different penetration levels under an uncontrolled (dumb) charging case, also under a proposed controlled charging algorithm for both summer and winter seasons.
In this paper is presented an algorithm for the power management of a smart home with electric vehicle and photovoltaic panels. The case study is performed considering the power demand of the household appliances, the charging/discharging of the electric vehicle, and the power supplied by the photovoltaic panels. The photovoltaic panels have a small installed power and benefit from the support scheme from the government for these types of generation sources, so it is a prosumer. The simulation is performed for a day. Additionally, the cost of power supplied to the consumer is also analyzed.
Demand Response for Smart Home An Evaluation from an End Users Perspective Based on a High Resolution Power Demand Model
