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Alternative vehicles, such as plug-in hybrid electric vehicles (PHEVs), become more popular. The batteries of these PHEVs are designed to be charged at home, from a standard outlet in the garage, or on a corporate car park. These extra electrical loads have an impact on the distribution grid. The uncoordinated power consumption on a local scale can lead to grid problems. Therefore coordinated charging is proposed. The exact forecasting of household loads is not possible, so stochastic programming is introduced. The stochastic approach represents an error in the forecasting of the daily load profiles. Two main program techniques are analyzed: quadratic and dynamic programming. The coordination of the PHEVs reduces the power losses and improves the power quality. The estimation of the costs of grid reinforcement must be compared with the cost of the implementation of a smart metering system for the coordination of the charging.

Internal combustion engines (ICE) are combined with electric motors and batteries in both hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV) to improve efficiency and achieve a limited all electric range. This paper determines the electrical power required for charging a fleet of PHEVs in Belgium. A stochastic model based on the driving behavior of Western European drivers, determines the availability of the PHEVs for grid charging.Three scenarios are defined to generate charging profiles based on the driving profiles. The first two scenarios, defined as uncoordinated charging, are based on a continuation of the current tariff schemes available to residential users, i.e. a single electricity tariff or a double electricity tariff including a day and night tariff. In the third scenario, coordinated charging is proposed. When coordinated charging is applied, the time of charging is shifted to a more appropriate moment of the night where total electrical load is minimal. The charging energy when coordinated charging is applied for each PHEV is defined to be equal to that of the single tariff scenario.The extra load caused by charging PHEVs is added to the residential and industrial electricity consumption of Belgium in 2008. Based on this data, a year load duration diagram can be determined to quantify demand for both power and energy in base load, variable load and peak load. Uncoordinated charging for residential users will cause difficulties for the electricity production system because peak load will rise substantially while base load stays the same. Coordinated charging is essential to minimize the impact on the electricity production system and could be implemented using smart meter technology.

Electric appliances consume electricity when they are in standby mode and sometimes even in off-mode. These "losses" of each appliance individually are not large but the sum over all appliances is no longer negligible. The standby losses of ten households are investigated. The standby power varies from 7 to 134 W and has an average of 40 W. The standby consumption is on average 274 kWh/year, representing 8% of the yearly consumption of an average household. With the 1-Watt plan, it is possible to reduce the standby losses to a significantly lower level. Other possibilities to reduce the standby power are standards and technology improvement.

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Traditionally, the impact of charging electric vehicles in the electricity grid is determined through scenario-analysis and based on statistical data. In this paper, instead of making assumptions on driving behavior, the energy consumption was calculated with measured driving profiles of conventional vehicles in order to quantify the future impact on the grid in more detail. As a function of the penetration of the Plug-in Hybrid Electric Vehicles and Battery Electric Vehicles, the increase in the peak power requirement in the grid is assessed. I.