scholarly journals Solving Optimal Reactive Power Dispatch Problem by Chaotic Based Brain Storm Optimization Algorithm

2020 ◽  
Vol 3 (2) ◽  
pp. 145-150
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Reactive Power ◽  
Optimal Solution ◽  
Test System ◽  
Predator Prey ◽  
Brain Storm Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Local Optimal Solution ◽  
Reactive Power Dispatch

In this work Chaotic Predator-Prey Brain Storm Optimization (CPS) algorithm is proposed to solve optimal reactive power dispatch problem. Predator–Prey Brain Storm Optimization position cluster centers to execute as predators, accordingly it will progress towards enhanced positions, although the left over thoughts do as preys; consequently they move far from their neighboring predators. In the projected algorithm chaotic theory has been applied to enhance the quality of the exploration.  Ergodicity and indiscretion are utilized in the CPS algorithm, such that projected algorithm will not get trapped in the local optimal solution.  Chaotic predator-prey brain storm optimization (CPS) algorithm has been tested in standard IEEE 30 bus test system and results show the projected algorithm reduced the real power loss effectively.

A Novel Evolutionary Optimization Technique for Solving Optimal Reactive Power Dispatch Problems

2016 ◽  
pp. 244-275 ◽  
Author(s):  
Provas Kumar Roy
Keyword(s):  
Reactive Power ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Search Space ◽  
Continuous Space ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Local Optimal Solution ◽  
Reactive Power Dispatch

Biogeography based optimization (BBO) is an efficient and powerful stochastic search technique for solving optimization problems over continuous space. Due to excellent exploration and exploitation property, BBO has become a popular optimization technique to solve the complex multi-modal optimization problem. However, in some cases, the basic BBO algorithm shows slow convergence rate and may stick to local optimal solution. To overcome this, quasi-oppositional biogeography based-optimization (QOBBO) for optimal reactive power dispatch (ORPD) is presented in this study. In the proposed QOBBO algorithm, oppositional based learning (OBL) concept is integrated with BBO algorithm to improve the search space of the algorithm. For validation purpose, the results obtained by the proposed QOBBO approach are compared with those obtained by BBO and other algorithms available in the literature. The simulation results show that the proposed QOBBO approach outperforms the other listed algorithms.

scholarly journals Optimal Reactive Power Dispatch using Crow Search Algorithm

2018 ◽  
Vol 8 (3) ◽  
pp. 1423 ◽  
Author(s):  
Lakshmi M ◽  
Ramesh Kumar A
Keyword(s):  
Reactive Power ◽  
Search Algorithm ◽  
Test System ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Voltage Deviation ◽  
Optimal Setting ◽  
Reactive Power Dispatch ◽  
And Control ◽  
Total Voltage

<p>The optimal reactive power dispatch is a kind of optimization problem that plays a very important role in the operation and control of the power system. This work presents a meta-heuristic based approach to solve the optimal reactive power dispatch problem. The proposed approach employs Crow Search algorithm to find the values for optimal setting of optimal reactive power dispatch control variables. The proposed way of approach is scrutinized and further being tested on the standard IEEE 30-bus, 57-bus and 118-bus test system with different objectives which includes the minimization of real power losses, total voltage deviation and also the enhancement of voltage stability. The simulation results procured thus indicates the supremacy of the proposed approach over the other approaches cited in the literature.</p>

Optimal Reactive Power Dispatch Incorporating TCSC-TCPS Devices Using Different Evolutionary Optimization Techniques

2016 ◽  
pp. 326-359
Author(s):  
Provas Kumar Roy ◽  
Susanta Dutta ◽  
Debashis Nandi
Keyword(s):  
Phase Shifter ◽  
Reactive Power ◽  
Test System ◽  
Artificial Bee Colony Optimization ◽  
Flexible Ac Transmission ◽  
Facts Devices ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch ◽  
Evolutionary Optimization Techniques

The chapter presents two effective evolutionary methods, namely, artificial bee colony optimization (ABC) and biogeography based optimization (BBO) for solving optimal reactive power dispatch (ORPD) problem using flexible AC transmission systems (FACTS) devices. The idea is to allocate two types of FACTS devices such as thyristor-controlled series capacitor (TCSC) and thyristor-controlled phase shifter (TCPS) in such a manner that the cost of operation is minimized. In this paper, IEEE 30-bus test system with multiple TCSC and TCPS devices is considered for investigations and the results clearly show that the proposed ABC and BBO methods are very competent in solving ORPD problem in comparison with other existing methods.

scholarly journals UNIQUE ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PROBLEM

2017 ◽  
Vol 5 (2) ◽  
pp. 122-134
Author(s):  
K. Lenin
Keyword(s):  
Minimum Distance ◽  
Antarctic Krill ◽  
Reactive Power ◽  
Test System ◽  
Krill Herd Algorithm ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Krill Herd ◽  
Reactive Power Dispatch ◽  
Simulation Results

In this paper, a new algorithm based on krill herd actions, named as Antarctic krill Herd Algorithm (AKHA) is proposed for solving optimal reactive power dispatch problem. The AKHA algorithm is based on behavior of krill individuals. The minimum distance of each individual krill from food and from uppermost density of the herd are deliberated as the foremost mission for the krill movement. Projected AKHA algorithm has been tested in standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm in reducing the real power loss and voltage stability also improved.

scholarly journals A Multi-Period Optimal Reactive Power Dispatch Approach Considering Multiple Operative Goals

2021 ◽  
Vol 11 (18) ◽  
pp. 8535
Author(s):  
Jairo A. Morán-Burgos ◽  
Juan E. Sierra-Aguilar ◽  
Walter M. Villa-Acevedo ◽  
Jesús M. López-Lezama
Keyword(s):  
Reactive Power ◽  
Test System ◽  
Discrete Control ◽  
Mixed Integer ◽  
Power System Operations ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
General Algebraic Modeling System ◽  
Reactive Power Dispatch ◽  
Selection Of

The optimal reactive power dispatch (ORPD) problem plays a key role in daily power system operations. This paper presents a novel multi-period approach for the ORPD that takes into account three operative goals. These consist of minimizing total voltage deviations from set point values of pilot nodes and maneuvers on transformers taps and reactive power compensators. The ORPD is formulated in GAMS (General Algebraic Modeling System) software as a mixed integer nonlinear programming problem, comprising both continuous and discrete control variables, and is solved using the BONMIN solver. The most outstanding benefit of the proposed ORPD model is the fact that it allows optimal reactive power control throughout a multi-period horizon, guaranteeing compliance with the programmed active power dispatch. Additionally, the minimization of maneuvers on reactors and capacitor banks contributes to preserving the useful life of these devices. Furthermore, the selection of pilot nodes for voltage control reduces the computational burden and allows the algorithm to provide fast solutions. The results of the IEEE 118 bus test system show the applicability and effectiveness of the proposed approach.

scholarly journals A hybrid bacterial foraging-particle swarm optimization technique for solving optimal reactive power dispatch problem

2020 ◽  
Vol 9 (2) ◽  
pp. 127
Author(s):  
P. Lokender Reddy ◽  
Yesuratnam Guduri
Keyword(s):  
Particle Swarm Optimization ◽  
Evolutionary Computation ◽  
Reactive Power ◽  
Particle Swarm ◽  
Test System ◽  
Swarm Optimization ◽  
Bacterial Foraging ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch

<div data-canvas-width="397.27351844386203">This paper presents a hybrid evolutionary computation algorithm termed as hybrid bacterial foraging-particle swarm optimization (HBFPSO) algorithm, to optimal reactive power dispatch (ORPD) problem. HBFPSO algorithm merges velocity and position updating strategy of particle swarm optimization (PSO) algorithm and reproduction and elimination dispersal of bacterial foraging algorithm (BFA). The ORPD is solved for minimization of two objective functions; system real power loss and voltage stability L-index. The objective is minimized by optimally choosing the control variables; generator excitations, tap positions of on-load tap changing transformers and switched var compensators while satisfying their constraints and also the constraints of dependent variabl</div><div data-canvas-width="98.30049385204596">es; voltages of all load buses and reactive power generation of all generators. The proposed approach has been evaluated on a standard IEEE 30 bus test system and 24 bus EHV southern region equivalent Indian power system. The results offered by the proposed algorithm are compared with those offered by other evolutionary computation algorithms reported in the recent state of the art literature and the superiority of the proposed algorithm is demonstrated.</div>

Optimal Allocation of Static Synchronous Series Compensator Controllers using Chemical Reaction Optimization for Reactive Power Dispatch

2016 ◽  
Vol 5 (3) ◽  
pp. 43-62 ◽  
Author(s):  
Susanta Dutta ◽  
Provas Kumar Roy ◽  
Debashis Nandi
Keyword(s):  
Chemical Reaction ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Optimal Solution ◽  
Chemical Reaction Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reaction Optimization ◽  
Reactive Power Dispatch ◽  
Static Synchronous Series Compensator

Static synchronous series compensator (SSSC) is one of the most effective flexible AC transmission systems (FACTS) devices used for enhancing power system security. In this paper, optimal location and sizing of SSSC are investigated for solving the optimal reactive power dispatch (ORPD) problem in order to minimize the active power loss in the transmission networks. A new and efficient chemical reaction optimization (CRO) is proposed to find the feasible optimal solution of the SSSC based optimal reactive power dispatch (ORPD) problem. The proposed approach is carried out on the standard IEEE 30 bus and IEEE 57 bus test systems. The optimization results obtained by the proposed CRO are analyzed and compared with the same obtained from genetic algorithm (GA), teaching learning based optimization (TLBO), quasi-oppositional TLBO (QOTLBO) and strength pareto evolutionary algorithm (SPEA). The results demonstrate the capabilities of the proposed approach to generate true and well-distributed optimal solutions.

scholarly journals Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2968 ◽  
Author(s):  
Zelan Li ◽  
Yijia Cao ◽  
Le Van Dai ◽  
Xiaoliang Yang ◽  
Thang Trung Nguyen
Keyword(s):  
Power Systems ◽  
Optimization Algorithm ◽  
Reactive Power ◽  
Optimization Problems ◽  
Optimal Solution ◽  
System Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch ◽  
Antlion Optimization

In this paper, a novel improved Antlion optimization algorithm (IALO) has been proposed for solving three different IEEE power systems of optimal reactive power dispatch (ORPD) problem. Such three power systems with a set of constraints in transmission power networks such as voltage limitation of all buses, limitations of tap of all transformers, maximum power transmission limitation of all conductors and limitations of all capacitor banks have given a big challenge for global optimal solution search ability of the proposed method. The proposed IALO method has been developed by modifying new solution generation technique of standard antlion optimization algorithm (ALO). By optimizing three single objective functions of systems with 30, 57 and 118 buses, the proposed method has been demonstrated to be more effective than ALO in terms of the most optimal solution search ability, solution search speed and search stabilization. In addition, the proposed method has also been compared to other existing methods and it has obtained better results than approximately all compared ones. Consequently, the proposed IALO method is deserving of a potential optimization tool for solving ORPD problem and other optimization problems in power system optimization fields.

scholarly journals CROWDING DISTANCE BASED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PROBLEM

2018 ◽  
Vol 6 (6) ◽  
pp. 226-237
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Test System ◽  
Swarm Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Crowding Distance ◽  
Reactive Power Dispatch

In this paper, Crowding Distance based Particle Swarm Optimization (CDPSO) algorithm has been proposed to solve the optimal reactive power dispatch problem. Particle Swarm Optimization (PSO) is swarm intelligence-based exploration and optimization algorithm which is used to solve global optimization problems. In PSO, the population is referred as a swarm and the individuals are called particles. Like other evolutionary algorithms, PSO performs searches using a population of individuals that are updated from iteration to iteration. The crowding distance is introduced as the index to judge the distance between the particle and the adjacent particle, and it reflects the congestion degree of no dominated solutions. In the population, the larger the crowding distance, the sparser and more uniform. In the feasible solution space, we uniformly and randomly initialize the particle swarms and select the no dominated solution particles consisting of the elite set. After that by the methods of congestion degree choosing (the congestion degree can make the particles distribution more sparse) and the dynamic e infeasibility dominating the constraints, we remove the no dominated particles in the elite set. Then, the objectives can be approximated. Proposed crowding distance based Particle Swarm Optimization (CDPSO) algorithm has been tested in standard IEEE 30 bus test system and simulation results shows clearly the improved performance of the projected algorithm in reducing the real power loss and static voltage stability margin has been enhanced.

scholarly journals A modified bacterial foraging algorithm based optimal reactive power dispatch

2019 ◽  
Vol 13 (1) ◽  
pp. 361
Author(s):  
Palvai Lokender Reddy ◽  
G. Yesuratnam
Keyword(s):  
Reactive Power ◽  
Test System ◽  
Standard Test ◽  
Initial Population ◽  
Objective Functions ◽  
Bacterial Foraging ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Bacterial Foraging Algorithm ◽  
Reactive Power Dispatch

<p>This article describes an approach for optimal reactive power dispatch problem using a Modified Bacterial Foraging Algorithm. Modified bacterial foraging algorithm introduces a differential evolution operator in chemotaxis to overcome tumble failure in tumble step and accelerates the convergence speed of the original operator. In the new algorithm chaotic dynamics are used to generate initial population to have uniform distribution. The proposed new algorithm is applied to Optimal reactive power dispatch problem with two objective functions; minimization of real power loss and voltage stability L-index. The objective functions are minimized by optimally choosing the control variables such as generator excitations, tap positions of on-load tap changing transformers and switched var compensators. The proposed approach has been evaluated on an IEEE 30 bus standard test system. The performance of the proposed algorithm is compared with other evolutionary computation algorithms in the literature and the effectiveness of the proposed algorithm is demonstrated.</p><em><em><br /></em></em>

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