A normative self-organizing migrating algorithm for power economic dispatch of thermal generators with valve-point effects and multiple fuels

A new class of meta-heuristics called SOMA (Self-Organizing Migrating Algorithm) was proposed in recent literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organizing behavior of groups of individuals in a ¿social environment¿. This paper proposes a modified SOMA approach to solving the economic load dispatch problem of thermal generators with the valve-point effect. To show the performance of the proposed modified SOMA algorithm based on fundamentals of normative knowledge in cultural algorithms, which was applied to test the power economic problem comprised 10 generating units with valve-point effects and multiple fuels for the load demands of 2400 MW. Simulation results show that the classical and modified SOMA algorithms are efficient and have good convergence property when compared with results of other optimization methods reported in the literature.