S. O. Orero and M. R. Irving, “A Genetic Algorithm Modelling Framework and Solution Technique for Short Term Optimal Hydrothermal Scheduling,” IEEE Transactions on Power System, Vol. 13, No. 2, May 1998.

has been cited by the following article:

• TITLE: A Novel Particle Swarm Optimization for Optimal Scheduling of Hydrothermal System

  AUTHORS: Wenping Chang

  KEYWORDS: Hydrothermal Generation Scheduling, Particle Swarm Optimization, Fuzzy, Adaptability

  JOURNAL NAME: Energy and Power Engineering, Vol.2 No.4, November 26, 2010

  ABSTRACT: A fuzzy adaptive particle swarm optimization (FAPSO) is presented to determine the optimal operation of hydrothermal power system. In order to solve the shortcoming premature and easily local optimum of the standard particle swarm optimization (PSO), the fuzzy adaptive criterion is applied for inertia weight based on the evolution speed factor and square deviation of fitness for the swarm, in each iteration process, the inertia weight is dynamically changed using the fuzzy rules to adapt to nonlinear optimization process. The performance of FAPSO is demonstrated on hydrothermal system comprising 1 thermal unit and 4 hydro plants, the comparison is drawn in PSO, FAPSO and genetic algorithms (GA) in terms of the solution quality and computational efficiency. The experiment showed that the proposed approach has higher quality solutions and strong ability in global search.