Reducing Greenhouse Gas Emissions and Improving Air Quality
74
74
customers, so that better services can be provided (Reka and Dragicevic,
2018; SAS, 2019). Artificial intelligence technology can be used effectively
with advanced network technology to make the smart grid efficient in processing data. The Internet of Things links objects to the Internet to create
a global infrastructure for the information society, enabling communication
that allows intelligent devices to work cooperatively for the benefit of society.
For example, an intelligent system of the customer and the smart grid can
decide when to turn on the electricity to charge the battery on an EV. Smart
meters are able to provide data that can be used with machine learning to
make better decisions that improve efficiency and security (SAS, 2016).
The two- way communication in smart grids allows for a significant increase
in collected data and much greater consumer engagement and participation.
Consumers can adjust their consumption of electricity and modify their
behavior when they perform some tasks. Solar panels for electricity generation and storage behind the meter are becoming more common, and the
smart grid and smart meters make the grid more robust and secure. This does
require that all involved follow established communication standards and
electrical system standards to provide an effective service (Bikmetov et al.,
2017). Several different computing platforms and various web services are
available for energy management and control of the smart grid. Internet of
Things technologies may be used for automated management of smart grid
decision making to achieve effective energy use. The benefits of the Internet
of Things for the smart grid include better customer service, greater energy
efficiency, improved data- driven decision making, increased integration of
distributed energy resources, and better customer engagement (SAS, 2016).
Machine learning, using data from smart meters and other information, may
also lead to increased cybersecurity (e.g. by recognizing anomalies more
quickly) and reductions in restoration time when problems are encountered.
The digital revolution associated with the Internet of Things and the process of developing automated decision systems that make use of machine
learning have been described as the fourth industrial revolution (Marr, 2018;
Reka and Dragicevic, 2018). The smart grid is one application of this new
approach to improving communication and decision making. It is now possible to automate some smart grid applications so that higher- demand activities, such as EV charging, can be turned on when demand for electricity
needs to be increased and there is a price incentive to do so.
7.3 Energy Storage
The smart grid, like any electrical grid, is fundamentally about balancing, at all times, the electricity that is being generated (coming in) and
the electricity that is being demanded by customers (flowing out). There
74
74
customers, so that better services can be provided (Reka and Dragicevic,
2018; SAS, 2019). Artificial intelligence technology can be used effectively
with advanced network technology to make the smart grid efficient in processing data. The Internet of Things links objects to the Internet to create
a global infrastructure for the information society, enabling communication
that allows intelligent devices to work cooperatively for the benefit of society.
For example, an intelligent system of the customer and the smart grid can
decide when to turn on the electricity to charge the battery on an EV. Smart
meters are able to provide data that can be used with machine learning to
make better decisions that improve efficiency and security (SAS, 2016).
The two- way communication in smart grids allows for a significant increase
in collected data and much greater consumer engagement and participation.
Consumers can adjust their consumption of electricity and modify their
behavior when they perform some tasks. Solar panels for electricity generation and storage behind the meter are becoming more common, and the
smart grid and smart meters make the grid more robust and secure. This does
require that all involved follow established communication standards and
electrical system standards to provide an effective service (Bikmetov et al.,
2017). Several different computing platforms and various web services are
available for energy management and control of the smart grid. Internet of
Things technologies may be used for automated management of smart grid
decision making to achieve effective energy use. The benefits of the Internet
of Things for the smart grid include better customer service, greater energy
efficiency, improved data- driven decision making, increased integration of
distributed energy resources, and better customer engagement (SAS, 2016).
Machine learning, using data from smart meters and other information, may
also lead to increased cybersecurity (e.g. by recognizing anomalies more
quickly) and reductions in restoration time when problems are encountered.
The digital revolution associated with the Internet of Things and the process of developing automated decision systems that make use of machine
learning have been described as the fourth industrial revolution (Marr, 2018;
Reka and Dragicevic, 2018). The smart grid is one application of this new
approach to improving communication and decision making. It is now possible to automate some smart grid applications so that higher- demand activities, such as EV charging, can be turned on when demand for electricity
needs to be increased and there is a price incentive to do so.
7.3 Energy Storage
The smart grid, like any electrical grid, is fundamentally about balancing, at all times, the electricity that is being generated (coming in) and
the electricity that is being demanded by customers (flowing out). There