IEEE Systems, Man and Cybernetics Magazine - April 2022 - 25

evolutional processes like genetic inheritance and natural
selection.
GA is an iterative process in which a population of
potential candidate solutions is first randomly generated.
The population in each iteration is called a generation.
All of the individual candidates (known as genes)
in the population are then evaluated using a fitness
function (i.e., the problem objective). The best candidates
are stochastically selected from the current generation,
and their genomes are modified
by recombinat ion (crossover) and
replacement (mutation) to form a new
generation of candidate solutions, which
is then used in the next iteration. The
stopping criteria for the algorithm are
the maximum population size and best
candidate allocation that satisfy the
objective function.
100
60
80
Harmony Search Algorithm
HSA is a popular metaheuristic algorithm
inspired by the musical improvisation process
[23]. Consider a music orchestra that
improvises to find and perform the most
harmonious and melodious music. Each
musician in an orchestra corresponds to
a decision variable, and an instrument's
pitch range corresponds to the set of
possible values of the decision variable.
The musical harmony produced by the
musicians at a certain time can be considered
as the solution vector for an iteration.
An audience's aesthetic judgment
of the music can be related to the fitness
of the objective function. Just like a
musical orchestra attempts to find (or
play) the best music possible by improving
it over time, the optimization algorithm
aims to progressively find the
optimal solution. Thus, HSA is an idealized
mapping from qualitative improvisation
into a quantitative formulation,
where musical harmony concepts are
applied to an optimization process.
Representative Simulations
for Demand Response in Home
Energy Management Systems
Some simulation results are now provided
to demonstrate the performance of
the optimization algorithms GA and HSA. As
the household loads, the eight appliances
listed in Table 1 are investigated with the
given power ratings and operating time
periods. Since the uninterruptible appliances
cannot be shifted after they start
40
20
12 a.m. 4 a.m. 8 a.m. 12 p.m.
Time (h)
100
60
80
40
20
12 a.m. 4 a.m. 8 a.m. 12 p.m.
Time (h)
(a)
100
150
200
50
12 a.m. 4 a.m. 8 a.m. 12 p.m.
Time (h)
100
150
200
50
12 a.m. 4 a.m. 8 a.m. 12 p.m.
Time (h)
(b)
4 p.m. 8 p.m.
12 a.m.
4 p.m. 8 p.m.
Without HEMS
With HSA-HEMS
12 a.m.
4 p.m. 8 p.m.
12 a.m.
Without HEMS
With HSA-HEMS
4 p.m. 8 p.m. 12 a.m.
operating, the HEMS schedules the operation of the iron
after the washing machine. Interruptible appliances, on
the other hand, are scheduled based on the pricing signal
in any time period. The energy consumption of the household
appliances for one day (starting from 12 a.m. to
12 a.m. the following day) with a scheduling resolution of
1 h (t) is considered. The TOU pricing tariffs for the summer
(1 May to 31 October 2019) and winter (1 November
2018 to 30 April 2019) seasons are taken from [24].
Without HEMS
With GA-HEMS
Without HEMS
With GA-HEMS
Figure 3. The electricity costs per hour under the TOU pricing scheme
for a day each in the (a) summer and (b) winter seasons without
and with the two Has: GA and HSA.
April 2022 IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE 25
Electricity Cost (Cents)
Electricity Cost (Cents)
Electricity Cost (Cents)
Electricity Cost (Cents)
IEEE Systems, Man and Cybernetics Magazine - April 2022

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