IEEE Systems, Man and Cybernetics Magazine - April 2022 - 23

information collected from hardware
installed in the electrical
power system and household.
The typical objective of an HEMS
is to minimize the customer's
costs. Bidirectional communication
among the HEMS, smar t
meters, utility, and power grid
enables the HEMS to meet
its
objectives by, for example, implementing
a peak-shaving strategy
while considering the electricity
price signal.
An IoT network, along with an
The continuous
integration of RESs
into the power system
has made it important
to enable effective
DSM to match the
power supply with
the load.
advanced metering infrastructure
(AMI), supports the bidirectional communication
and enables robust data management systems, strong
network connectivity, and smart metering systems.
The deployment of an AMI makes it possible for smart
meters to measure and collect useful information, such
as the energy consumption, available (generated) energy,
or energy price in the next hour, in a precise and
t imely manner. Moreover, th is informat ion is
exchanged between the HEMS and utility simultaneously
in real time. As a result, customers can take
par t
in DSM st rategies and manage the energy
demand effectively.
Figure 2 illustrates the operations of a typical HEMS.
Four components-the data aggregator (DA), software
and network management (SNM), appliance management
system (AMS), and HA-interface with each other
to form the HEMS. The DA receives energy pricing and
production information and sends this to the SNM and
HA. The AMS component collects data about appliances,
such as energy consumption, operation time interval,
data received from user interfaces, and so on, and
exchanges them with the HA and SNM. Thereafter, the
HA executes the scheduling task and sends the results (a
new schedule and so on) to the SNM, which operates as
the primary control and management component, managing
the accumulated data of the DA, HA, and AMS
components and processing the flow of instructions in
the network.
HEMSs and their characteristics have been extensively
investigated in the last decade, and a comprehensive
description of HEMS architectures, DSM
approaches, smart grid technologies, communication
protocols, and various decision-making algorithms
can be found in [2]. This article focuses on the operational
aspects of HEMSs and assesses their resilience
against a specific type of cyberattack. Such an attack
is defined by fake price signals that are used as
inputs to the HEMSs to alter their load schedule. To
the best of the authors' knowledge, this important
aspect has not yet been studied in the literature.
Before we discuss the details of the proposed study,
we briefly introduce the main
ideas behind DR and the scheduling
algorithms.
Demand Response
The goal of an HEMS is to enable
and support DSM to meet specific
objectives, such as the minimization
of customers' electricity bills,
utility costs, or system costs. DSM
is typically achieved by offering
financial incentives to customers,
inducing behavioral changes
through education, using higherefficiency
loads, increasing diversity
factors, using distributed energy resources, or other
measures [3]. The continuous integration of RESs into the
power system has made it important to enable effective
DSM to match the power supply with the load.
DR methods, which offer financial incentives to customers,
are popular and highly researched techniques to
achieve DSM since they incentivize RES integration along
with DSM. DR is defined as [4]:
a tariff or program established to motivate changes in
electric usage by end-users from their normal consumption
patterns in response to changes in the price
of electricity over time, or to give incentive payments
designed to induce lower electricity use at times of
high wholesale market prices or when system reliability
is jeopardized.
HEMSs nearly always employ DR methods to achieve
their goals.
Pricing Information
Energy Transaction
Data
Aggregation
Software and
Network
Management
Heuristic
Algorithms
Appliances
Fixed Power
Flexible Power
Appliance
Management
System
User Interfaces
Figure 2. The typical operations of an HEMS.
April 2022 IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE 23
IEEE Systems, Man and Cybernetics Magazine - April 2022

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