A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems

By A. Immanuel Selvakumar, K. Thanushkodi. IEEE Transactions on Power Systems, 2007

865 citations recorded by the source corpus.

How researchers see this paper

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

Biogeography-Based Optimization for Different Economic Load Dispatch Problems (2010, methodology): “The performance of the proposed method in terms of solution quality and computational efficiency has been compared 1) with SOH_PSO [12] and other methods for a 40-generator system including valve-point loading; 2) with Hopfield model [4] and other techniques for a 20-generator system with quadratic ”
Dynamic Economic Dispatch Using Lagrangian Relaxation With Multiplier Updates Based on a Quasi-Newton Method (2013, background): “Modern optimization algorithms, including simulated annealing (SA) [11], particle swarm optimization (PSO) [12], genetic algorithms (GA) [13], and others [14]–[16], also have global search capabilities (i.e., the ability to find optimal or 0885-8950 © 2013 IEEE satisfactory suboptimal solutions with”
Continuous quick group search optimizer for solving non-convex economic dispatch problems (2012, methodology): “1624 NPSO-LRS [5] 624.”
Economic dispatch using chaotic bat algorithm (2016, neutral): “62 s 5 NPSO-LRS [34] 15,450 15,454 15,452 NA NA 6 MTS [39] 15,450.”