Page 298 - From Smart Grid to Internet of Energy

Internet of things for smart grid applications Chapter 7 265

The integration of large RES plants improves the capabilities of utility grid.
However, the power quality and control operations should also comply with
interconnection standards such as IEEE-P1547-2003, which presents a bench-
mark model for integration. The integration of DERs to utility grid causes sev-
eral challenges in terms of technical, economical, and management aspects.
Therefore, several control and management procedures have been implemented
for microgrid and DG integration to utility grid.
The microgrid central controllers (MGCC) that are improved for microgrid
management are dedicated systems to accomplish DSM, DR control, and gen-
eration control duties. It regulates the voltage and frequency of the microgrid
and sustains the system stability. MGCC, source controller (SC), and load con-
trollers (LC) illustrate the block diagram of a MGCC in the microgrid scenario
in Fig. 7.4 where LV section is controlled. The MGCC compares load demand
and generation level of microgrid and decides to increase the generation level or
leaving some non-critical loads from microgrid to supply critical loads. MGCC
accomplish this operation by controlling SC and LC subsystems in the micro-
grid. It is noted that MGCC can save 21.56% of daily energy consumption by
managing DR and generation control [23]. Furthermore, MGCC can detect the
instant power quality of microgrid at point of common coupling (PCC) and can
improve power factor by connecting and disconnecting to the utility grid. The
synchronization operation during reconnecting is also performed by MGCC.
Regardless of controller type used among MGCC, micro-source controller or
decentralized controller; the microgrid controller improves resiliency and flex-
ibility of power network to supply load without any curtailment or blackout.
Besides, controllers decrease the operation costs, DER integration and usage
rate, limits the carbon emission, and enhances reliability, sustainability, and
security of sources. The microgrid controllers enable the power network to
interface distributed management systems, DER aggregators, and distributed
metering systems [23–26].
On the other hand, the decentralized control provides separate communica-
tion channels dedicated to each DERs. Thus, all the controllers transmit mea-
surement data on their own channel, and the errors caused by the high
penetration of widespread sources eliminated in this way. The DER controllers
are no longer subjected to central controllers in decentralized control infrastruc-
ture while adaptive control methods are also proposed for ESS and energy con-
version devices in the context of MMS. The intermittent structure of RES and
charge-discharge cycles of energy storage devices used microgrids require pre-
diction and forecast systems to ensure the resiliency and DSM reliability of res-
idential systems to improve IoT applications. The computational methods that
can be applied in predicting and forecasting studies are surveyed in [27] where
selecting, sizing, optimization, power source variety analysis are researched.
The coordination of central controllers also provides forecasting assistance in
addition to operational cost analysis, load forecast in short and very short terms,
and power demand detection. The optimization plays vital role in predicting and