Hybrid Cuckoo Search Algorithm for Optimal Placement and Sizing of Static VAR Compensator

2016 ◽  
pp. 288-326 ◽  
Author(s):  
Khai Phuc Nguyen ◽  
Dieu Ngoc Vo ◽  
Goro Fujita
Keyword(s):  
Power System ◽  
Search Algorithm ◽  
Combinatorial Problem ◽  
Cuckoo Search ◽  
Global Optimum ◽  
Cuckoo Search Algorithm ◽  
Optimal Placement ◽  
Static Var Compensator ◽  
Voltage Deviation ◽  
Teaching Learning

This chapter proposes a Hybrid Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator (SVC). Hybrid Cuckoo search algorithm is a simple combination of the Cuckoo search algorithm (CSA) and Teaching-learning-based optimization (TLBO), where the learner phase of TLBO is added to improve performance of Cuckoo eggs. The proposed method is applied for optimizing location and sizing of SVC in electric power system. This problem is a kind of discrete and combinatorial problem. The objective function considers loss power, voltage deviation and operational cost of SVC and other operating constraints in power system. Numerical results from three various tested systems show that the proposed method is better than the conventional CSA and TLBO in finding the global optimum solutions and its performance is also high than others.

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.

scholarly journals Simultaneous placement of FACTS devices using cuckoo search algorithm

2020 ◽  
Vol 11 (3) ◽  
pp. 1344
Author(s):  
Basanagouda N. Patil ◽  
S. B. Karajgi
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Reactive Power Compensation ◽  
Optimal Placement ◽  
Facts Devices ◽  
In Series ◽  
Ac Transmission

The power system deregulation requires thechange in reactive power compensation in the power system. The optimal placement of FACTs (Flexi ble AC transmission system) devices is mandatory to recalculate the reactive power compensation in deregulation case. The FACTs devices generally used in series and shunt conections. Here the various facts devices connected in series & shunt combination simultaneously. The optimal placement and sizing of the devices are done in this paper by formulating the objective function with minimization of cost of the generation and minimizing the cost of Facts devices. MALAB is used for writing the code. IEEE 14 bus system is used to here for testing the system. Placing the FACTs separately and simultaneously are studied in case study. Cuckoo search algorithm is used to identify the solution to the optimization problem.

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

scholarly journals Optimal Tuning of Multimachine Power System Stabilizer using Cuckoo Search Algorithm

2015 ◽  
Vol 48 (30) ◽  
pp. 143-148 ◽  
Author(s):  
Dhanraj Chitara ◽  
Anil Swarnkar ◽  
Nikhil Gupta ◽  
K.R. Niazi ◽  
R.C. Bansal
Keyword(s):  
Power System ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Power System Stabilizer ◽  
Optimal Tuning ◽  
System Stabilizer
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