**10. Conclusion**

The divergences in office building load and generated electricity from PV panels can be lowered by controlling the charging and discharging amounts from both EVs and used EV batteries. In addition, in this demonstration test, the uncertainty related to EV availability and its capacity do not show any significant impact. It is because the drivers of EVs are basically the employees who are working in the office building and almost the commuting routes are constant every day. It is considered that although there is an uncertainty on EVs' availability and their capacity, the divergence between the predicted and real grid loads could be reduced as long as the capacity of the used EV batteries which are owned by EMS are able to cover

There are some important findings and suggestions which can be derived from the above theoretical study and demonstration test which are related to the employment of EVs and their

**a.** To calculate an optimum peak-cut threshold, an accurate forecast of both demand and supply is required. The demand forecast is influenced strongly by two main factors (especially the fluctuating load): weather condition and human behavior inside the building. To achieve more accurate weather forecast, timely update of weather informa‐ tion from meteorological agency and utilization of historical meteorological data are considered very important. In addition, regarding the forecasting of the human behavior, a construction of database and knowledge of specific behavior patterns of the office building is demanded. In case that the measurement of behavior patterns is relatively difficult to be performed, the method of guiding the behavior of the residence by estab‐

**b.** Objective and accurate metering system to measure the amount of charged and discharged electricity to and from EVs is crucially demanded to enhance the trust and transparency. It can be performed by independent third party which is trusted by both EV owners and EMS/aggregator, especially in an aggregator-based contract scheme. The measurement

**c.** The increase in EVs number taking part in this ancillary service results in larger available capacity for load leveling (peak-cut). Unfortunately, this phenomenon is also potential to cause higher risk of larger fluctuation in case that EMS cannot forecast accurately the number of EVs. Installation of larger amount of stationary battery (used EV batteries) is considered potential to buffer and absorb this fluctuation through charging and discharg‐

**d.** If some EVs which are participating in the ancillary service stop suddenly their service and demand an emergence charging due to some factors, such as traveling distance which will be traveled, EMS also must be able to coordinate this kind of sudden charging demand

for EVs. The uncoordinated charging can result in creation of a new peak-load.

can also include the participating duration, including stand-by time.

those fluctuating factors.

ing controls.

**9. Some findings and suggestions**

144 Modeling and Simulation for Electric Vehicle Applications

used batteries to support the electricity in a small-scale EMS.

lishing some regulations or policies might be taken.

This chapter discussed the enhanced utilization of EVs and their used batteries to participate in ancillary service to support the electricity, especially in a small-scale EMS. In addition, experimental study based on the real data collected from the demonstration test bed has also been described. The study showed that it is feasible to utilize EVs and used EV batteries in supporting small-scale EMS. Furthermore, load leveling which determines initially the peakcut threshold and, then controls both charging and discharging behaviors of EVs and used EV batteries based on peak-cut threshold is considered as a valid technique. As a result, the purchased electricity from the grid can be kept to be lower than the contracted power capacity.

Accurate forecast of both load and supply is considered as one of the important issues in this utilization, in addition to the availability forecast of EVs and their batteries. The supply includes the condition of electricity market, possible generated power by REs, and available electricity which can be supplied by EVs. Furthermore, highly accurate load forecast, especially the fluctuating load including human behavior and air conditioning, is also very essential to achieve an optimum target condition as it has been estimated by EMS.
