Page 458 - Decision Making Applications in Modern Power Systems

Multistage and decentralized operations of Chapter | 16 417

FIGURE 16.3 Smart charging communication system for electric vehicle (EVs).

exchange server implements the optimized charging power sequences into
the charging stations to which the participants’ vehicles plug.

16.3 Deterministic problem formulation

In this section, we introduce the EV-grid integration modeling strategies for
privately owned and fleet vehicles with the objective of reducing aggregate
energy and demand costs for each billing month period. The AlCoPark
garage has a typical electric load pattern on weekdays with peaks in early
morning and late afternoon caused by privately owned and fleet vehicle
charging, respectively. Using the actual charging demand data from each
charging station and the whole facility electric meter demand data, we will
demonstrate the ability to shift discrete charging demand segments for indi-
vidual charging sessions that reduce the aggregated peak demand in each
billing month without impacting the amount of charge received by each
vehicle.
For fleet vehicles, we propose a series of control strategies to control the
availability of the charging stations for the fleet EVs. The goal is to manage
the aggregated charging power of the fleet from time of peak demand or
high-cost periods to lower cost periods. For privately owned vehicles, the
goal of the proposed smart charging framework is to reschedule the power