Advertisement
Published in:
2010 | OriginalPaper | Chapter
A New Improved Particle Swarm Optimization Technique for Daily Economic Generation Scheduling of Cascaded Hydrothermal Systems
Authors : K. K. Mandal, B. Tudu, N. Chakraborty
Published in: Swarm, Evolutionary, and Memetic Computing
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Optimum scheduling of hydrothermal plants is an important task for economic operation of power systems. Many evolutionary techniques such as particle swarm optimization, differential evolution have been applied to solve these problems and found to perform in a better way in comparison with conventional optimization methods. But often these methods converge to a sub-optimal solution prematurely. This paper presents a new improved particle swarm optimization technique called self-organizing hierarchical particle swarm optimization technique with time-varying acceleration coefficients (SOHPSO_TVAC) for solving daily economic generation scheduling of hydrothermal systems to avoid premature convergence. The performance of the proposed method is demonstrated on a sample test system comprising of cascaded reservoirs. The results obtained by the proposed methods are compared with other methods. The results show that the proposed technique is capable of producing comparable results.