Page 285 - From Smart Grid to Internet of Energy

Internet of things for smart grid applications Chapter 7 255

The communication infrastructure should be resistant against interference,
latency, noises and fading sources for the presented applications in Table 7.1.
The component of a communication system along smart grid may be compliant
with wireline or wireless transceivers regarding to operation area and require-
ments. The prominent wireline communication system used in smart metering
applications is known as power line communication (PLC) while wireless com-
munications are based on radio frequency (RF), microwave or mesh trans-
ceivers at various frequency and data rates. The smart metering and
monitoring applications perform required control services due to AMI technol-
ogy. In the literature, very few papers comprehensively surveying IoT applica-
tions and services in smart grid has been presented so far.
However, it is possible to find featured studies presenting IoT based smart
grid applications considering recent communication opportunities. The recent
papers on IoT and smart grid topics have been focused on specified applications
as generation, transmission or consumer side applications. Comparing to other
recent surveys and researches, the primary aim is to present IoT applications for
all aspects of smart grid infrastructure and their contribution to smart grid sys-
tems. In this chapter, smart metering concepts and systems are presented in a
deeper description of smart meters, AMI technologies, and smart monitoring
systems. It has been summarized the featured and emerging applications, ser-
vices, architectural perspectives and challenging technologies of whole smart
grid infrastructure in the following sections. Afterwards, the driving factors
of IoT for smart grid and IoT applications in smart grid are presented in this
chapter.

7.2 Driving factors of IoT for smart grid
The remote monitoring and control ability of smart grid infrastructure increases
the capability of power plants to achieve more robust DSM and DG while
decreasing the losses. Hence, the power generation cycle requires some control
structures such as demand forecasting (DF) and automatic generation control
(AGC) in smart grid. The load and source variety owing to wide usage of
EVs, RESs, energy storage systems, and smart consumers with their own
distributed energy resources (DERs) adversely affect the common demand
management approaches. The gradual and increasing integration of these
source-load duos to the electricity grid requires robust DF to manage the gen-
eration cycle. Another control method to tackle the problems caused by pene-
tration of intermittent RESs and network requirement is AGC which is known
as secondary frequency control method. In fact, the main idea behind the AGC
was to decouple generation and load balance for several years. The preliminary
applications were known as automatic voltage regulator (AVR) that is named as
the load frequency control (LFC). These control methods were effective on slow
and limited changed in the load profile. Therefore, they become inadequate
against the recent integration of RESs and distributed generation sources