A particle swarm optimization for economic dispatch with nonsmooth cost functions

By Jong-Bae Park, Ki-Song Lee, Joong-Rin Shin, Kwang Y. Lee. IEEE Transactions on Power Systems, 2005

1,218 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2cd4e9a65884e9ad64d65163b435cc74611582d5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Nima Amjady
2. Hadi Nasiri-Rad
3. Behnam Mohammadi-Ivatloo
4. L. F. I. Kwang Y. Lee
5. J. Vlachogiannis
6. Elias Kyriakides
7. Irina Ciornei
8. Ganesh Kumar Venayagamoorthy

Citations in the corpus

• Iteration PSO with time varying acceleration coefficients for solving non-convex economic dispatch problems (2012, background): “The inertia weight (x) is linearly decreasing as the iterations proceed and can be calculated using (14) [32].”
• Taguchi method for solving the economic dispatch problem with nonsmooth cost functions (2005, methodology): “Therefore, it is more realistic to represent the generation cost function as a piecewise quadratic cost function [ 16 ].”
• An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems (2010, methodology): “The effect of the constraint treatment strategy can be observed by comparing PSO [16] and the CTPSO of this paper.”
• Optimization of Governor Parameters to Prevent Frequency Oscillations in Power Systems (2018, methodology): “The particle swarm optimization (PSO) algorithm is used to solve the above optimization problem [16], [17].”
• Economic dispatch using particle swarm optimization: A review (2009, methodology): “[62] adopted a modified PSO (MPSO) incorporating dynamic search space reduction strategy to accelerate the optimization of ECD-VPL and ECD-VPL-MF problems.”
• Nonconvex Economic Dispatch With AC Constraints by a New Real Coded Genetic Algorithm (2009, methodology): “Several methods such as dynamic programming (DP) [6], evolutionary programming (EP) [7], improved fast EP (IFEP) [8], a fast EP using the weighted mean of Gaussian and Cauchy mutations, called MFEP [8], tabu search (TS) [9], genetic algorithm (GA) [4], [10], hybrid EP combined with sequential quadra”
• Hybrid SOA–SQP algorithm for dynamic economic dispatch with valve-point effects (2010, methodology): “The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient (EG) by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule.”
• CHAOTIC PARTICLE SWARM OPTIMIZATION FOR ECONOMIC DISPATCH CONSIDERING THE GENERATOR CONSTRAINTS (2007, methodology): “Recently, PSO has been successfully employed to solve the ED problem while considering generator constraints [19] and nonsmooth cost constraints [20].”
• A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems (2007, methodology): “The comparison of generation cost obtained by IFEP [14], MPSO [15], TABLE III BEST POWER OUTPUT FOR 40-GENERATOR SYSTEM”