Short-Term Hydrothermal Scheduling Using Improved Social Group Optimization Algorithm

Abstract

Social Group Optimization (SGO) was introduced in 2016, whose algorithm is made by seeing the social interaction of human beings. SGO is divided into two-phase for searching for the best fitness value, i.e. phase of improvement and phase of acquisition. In the improving phase, each human in the social group gains information by communicating with each other, whereas in acquiring phase human beings of the social group communicate with a random individual and gain more information to give the best fitness value. In the improved version of SGO, i.e. Improved Social Group Optimization (ISGO) the self-awareness probability (SAP) component is introduced as a modification in acquiring phase, which improves an individual ability to learn from the best knowledgeable human of a social group to give more accurate fitness value. The core goal of using this modification in SGO is to get the best minimum total production cost for the thermal plant by meeting all the operating and physical constraints for Short-Term Hydrothermal problems using simulation.