This study deals with the application of hybrid PSO and GSA (hybrid PSOGSA) algorithm to solve the CEED problem. The PSOGSA algorithm profits from the abilities of both PSO and GSA algorithms. The performance of the proposed algorithm is tested on three standard test systems, with different constraints and various cost curve natures. Numerical results obtained by the proposed approach were compared with other optimization results reported in the literature recently.

Chapter Contents:

• 8.1 Introduction
• 8.2 Problem formulation
• 8.2.1 Fuel cost function
• 8.2.2 Emission function
• 8.2.3 Constraints
• 8.2.3.1 Power balance constraint
• 8.2.3.2 Generation capacity constraint
• 8.2.4 Slack generator calculation
• 8.3 Solution method
• 8.3.1 Overview of PSOGSA
• 8.3.1.1 Particle swarm optimization
• 8.3.1.2 Gravitational search algorithm
• 8.3.1.3 Hybridization of PSO and GSA
• 8.3.2 PSOGSA implementation to the CEED problem
• 8.4 Simulation results
• 8.4.1 Test system 1
• 8.4.2 Test system 2
• 8.4.3 Test system 3
• 8.5 Educational software—ceedgui
• 8.6 Conclusion
• References

Inspec keywords: particle swarm optimisation; search problems; power system economics; load dispatching

Other keywords: cost curve natures; standard test systems; hybrid PSO-SGA algorithm; gravitational search algorithm; combined economic and emission dispatch; CEED problem

Subjects: Optimisation techniques; Combinatorial mathematics; Power system management, operation and economics