Convergence Parameter Analysis for Different Metaheuristic Methods Control Constant Estimation and it’s Tradeoff Inference

2015 ◽  
Vol 6 (2) ◽  
pp. 404
Author(s):  
R. Sagayaraj ◽  
S. Thangavel
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Bat Algorithm ◽  
Cuckoo Search ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Parameter Analysis ◽  
Heuristic Methods ◽  
Metaheuristic Methods ◽  
Control Constant

This paper is an extension of our previous work, which discussed the difficulty in implementing different methods of resistance emulation techniques on the hardware due to its control constant estimation delay. In order to get rid of the delay this paper attempts to include the meta-heuristic methods for the control constants of the controller. To achieve the minimum Total Harmonic Disturbance (THD) in the AC side of the converter modern meta-heuristic methods are compared with the traditional methods. The convergence parameters, which are primary for the earlier estimation of the control constants, are compared with the measured parameters, tabulated and tradeoff inference is done among the methods. This kind of implementation does not need the mathematical model of the system under study for finding the control constants. The parameters considered for estimation are population size, maximum number of epochs, and global best solution of the control constants, best THD value and execution time. MatlabTM /Simulink based simulation is optimized with the M-file based optimization techniques like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm and Bat Algorithm.

scholarly journals Cuckoo Search Algorithm for Optimal Placement and Sizing of Static Var Compensator in Large-Scale Power Systems

2016 ◽  
Vol 6 (2) ◽  
pp. 59-68 ◽  
Author(s):  
Khai Phuc Nguyen ◽  
Goro Fujita ◽  
Vo Ngoc Dieu
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Search Algorithm ◽  
Harmony Search ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Static Var Compensator

Abstract This paper presents an application of Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator. Cuckoo search algorithm is a modern heuristic technique basing Cuckoo species’ parasitic strategy. The Lévy flight has been employed to generate random Cuckoo eggs. Moreover, the objective function is a multiobjective problem, which minimizes loss power, voltage deviation and investment cost of Static VAR Compensator while satisfying other operating constraints in power system. Cuckoo search algorithm is evaluated on three case studies and compared with the Teaching-learning-based optimization, Particle Swarm optimization and Improved Harmony search algorithm. The results show that Cuckoo search algorithm is better than other optimization techniques and its performance is also better.

A Comparative Study of Global-Best Harmony Search and Bat Algorithms on Optimization Problems

2013 ◽  
Vol 464 ◽  
pp. 352-357
Author(s):  
Pasura Aungkulanon
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Computation Time ◽  
Finite Sequence ◽  
Bat Algorithm ◽  
Harmony Search Algorithm ◽  
Response Surfaces ◽  
Sample Mean ◽  
Constrained Problems

The engineering optimization problems are large and complex. Effective methods for solving these problems using a finite sequence of instructions can be categorized into optimization and meta-heuristics algorithms. Meta-heuristics techniques have been proved to solve various real world problems. In this study, a comparison of two meta-heuristic techniques, namely, Global-Best Harmony Search algorithm (GHSA) and Bat algorithm (BATA), for solving constrained optimization problems was carried out. GHSA and BATA are optimization algorithms inspired by the structure of harmony improvisation search process and social behavior of bat echolocation for decision direction. These algorithms were implemented under different natures of three optimization, which are single-peak, multi-peak and curved-ridge response surfaces. Moreover, both algorithms were also applied to constrained engineering problems. The results from non-linear continuous unconstrained functions in the context of response surface methodology and constrained problems can be shown that Bat algorithm seems to be better in terms of the sample mean and variance of design points yields and computation time.

scholarly journals Economic and Emission Dispatch Problems Using a New Hybrid Algorithm

2021 ◽  
Vol 15 ◽  
pp. 21-28
Author(s):  
Mimoun Younes ◽  
Fouad Khodja ◽  
Riad Lakhdar Kherfene
Keyword(s):  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Computational Time ◽  
Environmental Legislation ◽  
Multi Objective ◽  
Economic Power Dispatch ◽  
Emission Dispatch

Environmental legislation, with its increasing pressure on the energy sector to control greenhouse gases, is a driving force to reduce CO2 emissions, forced the power system operators to consider the emission problem as a consequential matter beside the economic problems, so the economic power dispatch problem has become a multi-objective optimization problem. This paper sets up an new hybrid algorithm combined in two algorithm, the harmony search algorithm and ant colony optimization (HSA-ACO), to solve the optimization with combined economic emission dispatch. This problem has been formulated as a multi-objective problem by considering both economy and emission simultaneously. The feasibility of the proposed approach was tested on 3-unit and 6-unit systems. The simulation results show that the proposed algorithm gives comparatively better operational fuel cost and emission in less computational time compared to other optimization techniques.

Hybridizing harmony search algorithm with cuckoo search for global numerical optimization

2014 ◽  
Vol 20 (1) ◽  
pp. 273-285 ◽  
Author(s):  
Gai-Ge Wang ◽  
Amir H. Gandomi ◽  
Xiangjun Zhao ◽  
Hai Cheng Eric Chu
Keyword(s):  
Numerical Optimization ◽  
Search Algorithm ◽  
Harmony Search ◽  
Cuckoo Search ◽  
Harmony Search Algorithm ◽  
Global Numerical Optimization

scholarly journals Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
S. K. Saha ◽  
R. Dutta ◽  
R. Choudhury ◽  
R. Kar ◽  
D. Mandal ◽  
...  
Keyword(s):  
Filter Design ◽  
Search Algorithm ◽  
Harmony Search ◽  
Search Space ◽  
Fir Filter ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Fir Filters ◽  
Linear Phase ◽  
Fir Filter Design

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected asa prioriguess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

scholarly journals Comparisional Investigation of Load Dispatch Solutions with TLBO

2017 ◽  
Vol 7 (6) ◽  
pp. 3246
Author(s):  
DSNM Rao ◽  
Niranjan Kumar
Keyword(s):  
Particle Swarm Optimization ◽  
Teaching And Learning ◽  
Search Algorithm ◽  
Harmony Search ◽  
Heuristic Method ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
The Other ◽  
Economic Load Dispatch ◽  
Swarm Optimization

This paper discusses economic load dispatch Problem is modeled with non-convex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm is applied to solve the load dispatch problem for 6 unit and 10 unit test systems along with the other algorithms. This comparisional investigation explored various merits of TLBO with respect to PSO, DE, and HAS in the field economic load dispatch.

Application of Static Var Compensator (SVC) With PI Controller for Grid Integration of Wind Farm Using Harmony Search

2016 ◽  
Vol 17 (5) ◽  
pp. 555-566 ◽  
Author(s):  
H. E. Keshta ◽  
A. A. Ali ◽  
E. M. Saied ◽  
F. M. Bendary
Keyword(s):  
Wind Farm ◽  
Reactive Power ◽  
Control Method ◽  
Search Algorithm ◽  
Harmony Search ◽  
Pi Controller ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Static Var Compensator

Abstract Large-scale integration of wind turbine generators (WTGs) may have significant impacts on power system operation with respect to system frequency and bus voltages. This paper studies the effect of Static Var Compensator (SVC) connected to wind energy conversion system (WECS) on voltage profile and the power generated from the induction generator (IG) in wind farm. Also paper presents, a dynamic reactive power compensation using Static Var Compensator (SVC) at the a point of interconnection of wind farm while static compensation (Fixed Capacitor Bank) is unable to prevent voltage collapse. Moreover, this paper shows that using advanced optimization techniques based on artificial intelligence (AI) such as Harmony Search Algorithm (HS) and Self-Adaptive Global Harmony Search Algorithm (SGHS) instead of a Conventional Control Method to tune the parameters of PI controller for SVC and pitch angle. Also paper illustrates that the performance of the system with controllers based on AI is improved under different operating conditions. MATLAB/Simulink based simulation is utilized to demonstrate the application of SVC in wind farm integration. It is also carried out to investigate the enhancement in performance of the WECS achieved with a PI Controller tuned by Harmony Search Algorithm as compared to a Conventional Control Method.

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