scholarly journals A binary particle swarm optimization approach for power system security enhancement

2022 ◽  
Vol 12 (2) ◽  
pp. 1929
Author(s):  
Padmanabha Raju Chinda ◽  
Ragaleela Dalapati Rao
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Optimal Power Flow ◽  
Cost Minimization ◽  
Particle Swarm ◽  
System Security ◽  
Binary Particle Swarm Optimization ◽  
Optimization Approach ◽  
Power System Security ◽  
Swarm Optimization

Improvement of power system security manages the errand of making healing move against conceivable system overloads in the framework following the events of contingencies. Generation re-dispatching is answer for the evacuation of line overloads. The issue is the minimization of different goals viz. minimization of fuel cost, minimization of line loadings and minimization of overall severity index. Binary particle swarm optimization (BPSO) method was utilized to take care of optimal power flow issue with different targets under system contingencies. The inspiration to introduce BPSO gets from the way that, in rivalry with other meta-heuristics, BPSO has demonstrated to be a champ by and large, putting a technique as a genuine alternative when one needs to take care of a complex optimization problem. The positioning is assessed utilizing fuzzy logic. Simulation Results on IEEE-14 and IEEE-30 bus systems are presented with different objectives.

Optimal load shedding by a new binary PSO

2016 ◽  
Vol 35 (3) ◽  
Author(s):  
Ahmad Ahmadi ◽  
Yousef Alinejad Beromi ◽  
Hassan rezai soleymanpour
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Design Methodology ◽  
Particle Swarm ◽  
System Security ◽  
Load Shedding ◽  
Binary Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Voltage Instability ◽  
Simulation Results

Purpose The voltage stability is a basic principle in the power system operation. Different short circuits, load growth, generation shortage, and other faults which disturb the voltage stability are serious threats to the system security. The voltage instability causes dispersal of a power system into sub-systems, and leads to blackout as well as heavy damages of the system equipments. Optimum load shedding during contingency situations is one of the most important issues in power system security analysis. Design/methodology/approach In this paper, a New Binary Particle Swarm Optimization technique (NB-PSO) is proposed for solving the integer-valued modeling of under-voltage load shedding (UVLS) problem. The updating mechanisms for the position and velocity of binary particles are amended in the proposed NB-PSO by using a new velocity definition, which has an excellent efficiency for solving complex binary optimization problems. Findings The effectiveness and capability of the proposed NB-PSO optimization algorithm were illustrated according to the simulation results of applying it to the IEEE 118-bus test system. In addition, the performance of the proposed NB-PSO based method was compared with other optimization algorithms, such as the Binary Particle Swarm Optimization (BPSO) and Hybrid Discrete Particle Swarm Optimization (HDPSO) techniques. It was perceived that the NB-PSO performs superior than the BPSO and HDPSO for determining the best location and the minimum level of load shedding in order to prevent voltage instability. Originality/value The proposed NB-PSO has novel modifications and techniques to enhance both exploration and exploitation capabilities to find the optimal feasible solution. The simulation results confirmed the effectiveness of the proposed method in determining the best location and the minimum amount of load shedding for voltage collapse prevention.

scholarly journals Operation cost reduction in unit commitment problem using improved quantum binary PSO algorithm

2020 ◽  
Vol 10 (2) ◽  
pp. 1149 ◽  
Author(s):  
Ali Nasser Hussain ◽  
Ali Abduladheem Ismail
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Cost Reduction ◽  
Unit Commitment ◽  
Particle Swarm ◽  
Total Power ◽  
Binary Particle Swarm Optimization ◽  
Unit Commitment Problem ◽  
Swarm Optimization ◽  
Operation Cost

Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC is used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system. This paper proposes an Improved Quantum Binary Particle Swarm Optimization (IQBPSO) algorithm. The tests have been made on a 10-units simulation system and the results show the improvement in an operation cost reduction after using the proposed algorithm compared with the ordinary Quantum Binary Particle Swarm Optimization (QBPSO) algorithm.

scholarly journals Bio-Inspired Feature Selection: An Improved Binary Particle Swarm Optimization Approach

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 85989-86002 ◽  
Author(s):  
Bai Ji ◽  
Xiaozheng Lu ◽  
Geng Sun ◽  
Wei Zhang ◽  
Jiahui Li ◽  
...  
Keyword(s):  
Feature Selection ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Optimization Approach ◽  
Swarm Optimization
Sign in / Sign up

Export Citation Format

Share Document