Page 351 - From Smart Grid to Internet of Energy

Big data, privacy and security in smart grids Chapter 8 315

8.2.3 IoT and big data
The IoT is a comprehensive definition including all type of devices such as sen-
sors, detectors, transducers, measurement devices, and interactive actuators
which are connected to internet over similar or different network types. All such
devices comprise intelligent or smart device interface on data acquisition and
data processing planes. The “things” are convenient to inherit, transmit, share,
and deploy the data thanks to internet infrastructure. It is known that IoT
concept has been derived from preliminary applications of radio frequency
identification (RFID) technology that has been firstly proposed by Ashton
[11]. Nevertheless, the definition and conceptual environment of IoT have been
gradually evolved day by day. The IoT defines interactive devices that are
sensitive to their environment to detect changes, conditions, and operation cir-
cumstances, and they are able to interact with each other to inform entire
network. IoT have found widespread usage areas including transportation,
energy, health, security, public and social life, education, and communication
applications. It is expected almost all electronic devices and components will be
connected to internet and comply with IoT environment. There are several lead-
ing technologies such as human to machine (H2M) and machine to machine
(M2M) communication, semantic sensor networks (SSNs), big data analytics,
machine learning, and ubiquitous computing (UbiComp) providing progress
of IoT [11, 12].
In addition to wireless connections, the wired communication methods are
also used in IoT applications to solve daily life problems and to improve con-
nectivity. The components of an IoT infrastructure comprise cyber-physical
system (CPS) that includes hardware for data acquisition, data processing
and software for transmission and data analytics. The information technologies
are adopted to smart grid environment as well as other application areas of IoT
due to large number of device usage. The heterogeneous device variety and
generated massive data sets are handled by big data applications to produce
meaningful data on demand, and to facilitate the selection of precise data among
huge stacks. The big data is one of the state-of-the-art research areas on IoT
aspects that includes volume, variety, velocity, and value of data. The generated
massive datasets are handled by using sophisticated big data analysis methods
such as data classification, regression, and clustering solutions to decrease com-
munication and processing costs [13]. The required efficient data processing
algorithms are presented in the following section in detail.
Smart grid integration is one of the recently widespread application of IoT.
The large number of sensing nodes and measurement devices generate heterog-
enous data stacks for storing and processing at each monitoring interval. The
inherited data are comprised by measurements of generated power rates, con-
sumer energy demand data, network control data, DSM commands and programs,
smart meter data, blackout and fault monitoring data, and many more related
measurement and sensing data. The wide variety of application types and data
acquisition frequencies force service providers to install high capability servers