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technologies will affect the plug-in hybrid vehicles (PHEV) technology and
its influences on DSM and peak management scenarios.

4.2.2.6 Computational intelligence
An important component of smart grids is the computational intelligence that
has progressed enormously during the last decade, making it possible to per-
form advanced control methods in real-time and forecasting applications.
Deployment of this technology will greatly affect the power quality of smart
microgrids since most of the real-time PQI methods need high computational
capabilities; giving this ability to digital controllers will greatly affect the
PQI process.

4.2.2.7 Advanced control methods
Advanced control methods can monitor and control the power system com-
ponents and can make it possible for power electronics to give timely and
rapid dynamic response to any event. These methods also involve in
decision-making procedures of market pricing, enhancing asset management
and a wide area of computer-based algorithms, such as data collecting, moni-
toring, and analyzing to provide innovative solutions from deterministic and
predictive perspectives. As is mentioned in Section 4.2.2.6, improvements in
computational capabilities have opened a path to power electronic experts to
merge power-converting task with PQI capabilities for power electro-
nic based converters [14].

4.2.2.8 Active demand-side management and demand response
The DSM is a set of activities, which finally will lead to enhanced reliability,
expense management, peak shaving, peak shifting, transmission and genera-
tion of cost reduction, and improved voltage quality. Different technologies
are involved in DSM, including monitoring system, RESs, battery storage,
smart appliances, computational intelligence, and almost all the smart grid
technologies. Having a more reliable microgrid that has a high-quality volt-
age profile is a consequence of the implementation of DSM.

4.2.2.9 Multiagent technology
Multiagent technology is somewhat an umbrella term that encompasses sev-
eral technologies for a common goal; this goal could be any achievement,
such as PQI in smart microgrids. Multiagent system makes it possible for
different sections to work in parallel to achieve the defined goal; it is a kind
of hierarchical system that makes the use of different agents to perform a
task, for example, to perform a demand response scenario; different agents
should be employed, such as monitoring and metering agent, computational
agent, decision-making agent, and, finally, the agent that is responsible to
perform the actions regarding generation and consumption units.