Modified particle swarm optimization using simplex search method for multiobjective economic emission dispatch problem

2017 ◽  
Author(s):  
Namarta Chopra ◽  
Y.S. Brar ◽  
J.S. Dhillon
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Search Method ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Simplex Search ◽  
Simplex Search Method ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

scholarly journals Economic Power Dispatch using Hybrid Particle Swarm Optimization with Simplex Search Method

2020 ◽  
Vol 18 (1) ◽  
pp. 70-79 ◽  
Author(s):  
Namarta Chopra ◽  
Yadwinder Brar ◽  
Jaspreet Dhillon
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Search Method ◽  
Economic Power ◽  
Fuel Cost ◽  
Swarm Optimization ◽  
Power Dispatch ◽  
Simplex Search ◽  
Simplex Search Method ◽  
Economic Power Dispatch

This paper presents the solution of economic power dispatch (EPD) in thermal power plants using the hybridization of particle swarm optimization (PSO) and simplex search method (SSM). EPD is obtaining the best generating schedule to supply the power demand and covering the transmission losses with minimum overall fuel cost. Physical constraints like valve point loading effects, ramp rate limits and prohibited operating zones are also included with basic EPD problem to increase the practicability in the problem. As PSO performs well in finding the global best solution and SSM in finding the local best solution, thus their combination improves the overall minimum results obtained for the generation fuel cost objective function. The performance of the proposed methodology is tested on different test systems having categories of small-scale, medium-scale and large-scale power system problems. The results obtained are then compared with other reported methods to show the superiority of the proposed algorithm.

scholarly journals A New Hybrid Nelder-Mead Particle Swarm Optimization for Coordination Optimization of Directional Overcurrent Relays

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
An Liu ◽  
Ming-Ta Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problem ◽  
Operating Time ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Method ◽  
Swarm Optimization ◽  
Simplex Search ◽  
Simplex Search Method ◽  
Overcurrent Relays

Coordination optimization of directional overcurrent relays (DOCRs) is an important part of an efficient distribution system. This optimization problem involves obtaining the time dial setting (TDS) and pickup current (Ip) values of each DOCR. The optimal results should have the shortest primary relay operating time for all fault lines. Recently, the particle swarm optimization (PSO) algorithm has been considered an effective tool for linear/nonlinear optimization problems with application in the protection and coordination of power systems. With a limited runtime period, the conventional PSO considers the optimal solution as the final solution, and an early convergence of PSO results in decreased overall performance and an increase in the risk of mistaking local optima for global optima. Therefore, this study proposes a new hybrid Nelder-Mead simplex search method and particle swarm optimization (proposed NM-PSO) algorithm to solve the DOCR coordination optimization problem. PSO is the main optimizer, and the Nelder-Mead simplex search method is used to improve the efficiency of PSO due to its potential for rapid convergence. To validate the proposal, this study compared the performance of the proposed algorithm with that of PSO and original NM-PSO. The findings demonstrate the outstanding performance of the proposed NM-PSO in terms of computation speed, rate of convergence, and feasibility.

Economic emission dispatch using an advanced particle swarm optimization technique

2019 ◽  
Vol 16 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Hamid Rezaie ◽  
Mehrdad Abedi ◽  
Saeed Rastegar ◽  
Hassan Rastegar
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Swarm Optimization ◽  
Content Type ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

Purpose This study aims to present a novel optimization technique to solve the combined economic emission dispatch (CEED) problem considering transmission losses, valve-point loading effects, ramp rate limits and prohibited operating zones. This is one of the most complex optimization problems concerning power systems. Design/methodology/approach The proposed algorithm has been called advanced particle swarm optimization (APSO) and was created by applying several innovative modifications to the classic PSO algorithm. APSO performance was tested on four test systems having 14, 40, 54 and 120 generators. Findings The suggested modifications have improved the accuracy, convergence rate, robustness and effectiveness of the algorithm, which has produced high-quality solutions for the CEED problem. Originality/value The results obtained by APSO were compared with those of several other techniques, and the effectiveness and superiority of the proposed algorithm was demonstrated. Also, because of its superlative characteristics, APSO can be applied to many other engineering optimization problems. Moreover, the suggested modifications can be easily used in other population-based optimization algorithms to improve their performance.

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