Abstract: This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.
Abstract: The stability is an important topic to plan and manage the energy in the microgrids as the same as the conventional power systems. The voltage and frequency stability is one of the most important issues recently studied in microgrids. The objectives of this paper are the modelling and designing of the components and optimal controllers for the voltage and frequency control of the AC/DC hybrid microgrid under the different disturbances. Since the PI controllers have the advantages of simple structure and easy implementation, so they are designed and modeled in this paper. The harmony search (HS) algorithm is used to optimize the controllers’ parameters. According to the achieved results, the PI controllers have a good performance in voltage and frequency control of the microgrid.
Abstract: Optimizing the parameters in the controller plays a
vital role in the control theory and its applications. Optimizing the
PID parameters is finding out the best value from the feasible
solutions. Finding the optimal value is an optimization problem.
Inverted Pendulum is a very good platform for control engineers to
verify and apply different logics in the field of control theory. It is
necessary to find an optimization technique for the controller to tune
the values automatically in order to minimize the error within the
given bounds. In this paper, the algorithmic concepts of Harmony
search (HS) and Genetic Algorithm (GA) have been analyzed for the
given range of values. The experimental results show that HS
performs well than GA.
Abstract: This study presents a hybrid metaheuristic algorithm
to obtain optimum designs for steel space buildings. The optimum
design problem of three-dimensional steel frames is mathematically
formulated according to provisions of LRFD-AISC (Load and
Resistance factor design of American Institute of Steel Construction).
Design constraints such as the strength requirements of structural
members, the displacement limitations, the inter-story drift and the
other structural constraints are derived from LRFD-AISC
specification. In this study, a hybrid algorithm by using teachinglearning
based optimization (TLBO) and harmony search (HS)
algorithms is employed to solve the stated optimum design problem.
These algorithms are two of the recent additions to metaheuristic
techniques of numerical optimization and have been an efficient tool
for solving discrete programming problems. Using these two
algorithms in collaboration creates a more powerful tool and
mitigates each other’s weaknesses. To demonstrate the powerful
performance of presented hybrid algorithm, the optimum design of a
large scale steel building is presented and the results are compared to
the previously obtained results available in the literature.
Abstract: Floorplanning plays a vital role in the physical design
process of Very Large Scale Integrated (VLSI) chips. It is an
essential design step to estimate the chip area prior to the optimized
placement of digital blocks and their interconnections. Since VLSI
floorplanning is an NP-hard problem, many optimization techniques
were adopted in the literature. In this work, a music-inspired
Harmony Search (HS) algorithm is used for the fixed die outline
constrained floorplanning, with the aim of reducing the total chip
area. HS draws inspiration from the musical improvisation process of
searching for a perfect state of harmony. Initially, B*-tree is used to
generate the primary floorplan for the given rectangular hard
modules and then HS algorithm is applied to obtain an optimal
solution for the efficient floorplan. The experimental results of the
HS algorithm are obtained for the MCNC benchmark circuits.
Abstract: Many wireless sensor network applications require
K-coverage of the monitored area. In this paper, we propose a
scalable harmony search based algorithm in terms of execution
time, K-Coverage Enhancement Algorithm (KCEA), it attempts to
enhance initial coverage, and achieve the required K-coverage degree
for a specific application efficiently. Simulation results show that
the proposed algorithm achieves coverage improvement of 5.34%
compared to K-Coverage Rate Deployment (K-CRD), which achieves
1.31% when deploying one additional sensor. Moreover, the proposed
algorithm is more time efficient.
Abstract: The physical methods for RNA secondary structure prediction are time consuming and expensive, thus methods for computational prediction will be a proper alternative. Various algorithms have been used for RNA structure prediction including dynamic programming and metaheuristic algorithms. Musician's behaviorinspired harmony search is a recently developed metaheuristic algorithm which has been successful in a wide variety of complex optimization problems. This paper proposes a harmony search algorithm (HSRNAFold) to find RNA secondary structure with minimum free energy and similar to the native structure. HSRNAFold is compared with dynamic programming benchmark mfold and metaheuristic algorithms (RnaPredict, SetPSO and HelixPSO). The results showed that HSRNAFold is comparable to mfold and better than metaheuristics in finding the minimum free energies and the number of correct base pairs.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: Voltage collapse is instability of heavily loaded electric
power systems that cause to declining voltages and blackout. Power
systems are predicated to become more heavily loaded in the future
decade as the demand for electric power rises while economic and
environmental concerns limit the construction of new transmission
and generation capacity. Heavily loaded power systems are closer to
their stability limits and voltage collapse blackouts will occur if
suitable monitoring and control measures are not taken. To control
transmission lines, it can be used from FACTS devices.
In this paper Harmony search algorithm (HSA) and Genetic
Algorithm (GA) have applied to determine optimal location of
FACTS devices in a power system to improve power system stability.
Three types of FACTS devices (TCPAT, UPFS, and SVC) have been
introduced. Bus under voltage has been solved by controlling reactive
power of shunt compensator. Also a combined series-shunt
compensators has been also used to control transmission power flow
and bus voltage simultaneously.
Different scenarios have been considered. First TCPAT, UPFS, and
SVC are placed solely in transmission lines and indices have been
calculated. Then two types of above controller try to improve
parameters randomly. The last scenario tries to make better voltage
stability index and losses by implementation of three types controller
simultaneously. These scenarios are executed on typical 34-bus test
system and yields efficiency in improvement of voltage profile and
reduction of power losses; it also may permit an increase in power
transfer capacity, maximum loading, and voltage stability margin.
Abstract: Individually Network reconfiguration or Capacitor control
perform well in minimizing power loss and improving voltage
profile of the distribution system. But for heavy reactive power loads
network reconfiguration and for heavy active power loads capacitor
placement can not effectively reduce power loss and enhance
voltage profiles in the system. In this paper, an hybrid approach
that combine network reconfiguration and capacitor placement using
Harmony Search Algorithm (HSA) is proposed to minimize power
loss reduction and improve voltage profile. The proposed approach
is tested on standard IEEE 33 and 16 bus systems. Computational
results show that the proposed hybrid approach can minimize losses
more efficiently than Network reconfiguration or Capacitor control.
The results of proposed method are also compared with results
obtained by Simulated Annealing (SA). The proposed method has
outperformed in terms of the quality of solution compared to SA.
Abstract: The utilization of renewable energy sources in electric
power systems is increasing quickly because of public apprehensions
for unpleasant environmental impacts and increase in the energy
costs involved with the use of conventional energy sources. Despite
the application of these energy sources can considerably diminish the
system fuel costs, they can also have significant influence on the
system reliability. Therefore an appropriate combination of the
system reliability indices level and capital investment costs of system
is vital. This paper presents a hybrid wind/photovoltaic plant, with
the aim of supplying IEEE reliability test system load pattern while
the plant capital investment costs is minimized by applying a hybrid
particle swarm optimization (PSO) / harmony search (HS) approach,
and the system fulfills the appropriate level of reliability.