Page 299 - From Smart Grid to Internet of Energy

266 From smart grid to internet of energy

forecasting objectives of microgrid controller middleware in IoT-based
smart grid applications. The most widely used optimization algorithms
perform the objectives regarding to the predicted data where the process is
based on probabilistic methods such as Monte Carlo, Support Vector Machine
(SVM), Dynamic line rating (DLR), and Markov Decision Process. The soft
computing methods can provide better forecasting techniques by analyzing
the stored data from past to now, and the performance of entire system may
be optimized.
The EVs are accepted as an environmental friendly technology to reduce the
adverse effect of internal combustion engine (ICE) cars. The high use of EVs
expedites their integration to utility grid as a source and load at discharge and
charge cycles. The increased usage of EVs may play destructive role on utility
grid if the uncontrolled power demand of charging EVs is integrated to the
mains. Two types of EV integration to the utility network are defined as
V2G and G2V. In the V2G type of integration, power flow occurs in bidirec-
tional mode where one is performed from grid to vehicle as charging and the
second is from vehicle to grid during discharging the batteries. On the other
hand, the power flow is always unidirectional since grid charges the batteries
in G2V operation. The bidirectional V2G capable EVs ease the DR control
by scheduling the discharge cycles at peak hours and charging cycles at off-peak
hours. As a consumption level application, the EV integration to the smart grid
is an emerging research area in terms of DG, DR, microgrid, and communica-
tion topics. Once a huge number of EVs are connected to the grid for charging, it
causes several PQ problems drawing highly loaded grid profile. Several voltage
deviations, frequency fluctuations, degraded PQ, instability on the power grid,
inadequate efficiency are some of the deficiencies occurred by uncoordinated
integration of EVs to the grid. Therefore, several solutions are provided owing
to smart communication and coordination features of smart grid. These coordi-
nation and control issues are mostly related with battery management systems
(BMSs) that are responsible to track some parameters of batteries such as state
of charge (SoC) and state of health (SoH). The communication methods are
listed into three categories as dedicated lines, wired systems such as Ethernet,
telephone lines etc., and wireless technologies based on Bluetooth or IEEE
812.15.4 type communication mediums. Regardless of communication method,
the main purpose of EV communication is to implement a CPS that is based on
bidirectional communication network across the AMI base of EV and utility
grid. The CPS facilitates the coordination of EVs by using many type of sensors
together, and by installing a transmission system for inherited data. Since the
CPS corresponds with the digital communication medium and analog power
transmission medium, it is vulnerable to intrusions and attacks caused by the
natural structure of power system. Thus, a protection and authentication system
is required to improve reliability and security of CPS. The confidentiality,
authenticity, availability, and integrity are researched in the context of privacy
aware CPS.