Combined Computational Intelligence Approach for the Power System Optimization Problem

This paper presents an adoption of a natural phenomenon as Thunderstorm Algorithm (TA) which is applied to solve a problem of the power production composition under various constraints. This work also introduces artificial salmon tracking algorithm (ASTA) for defining the optimal strategy of the power system on the power consumption. Both algorithms are tested on the IEEE-62 bus system as a selected structure for the mathematical cased model. By considering all parameters, results show that ASTA can be applied to predict the power consumption and TA also has good performances while searching the optimal solution. Moreover, the power production can be presented throughout an economic dispatch problem. Technically, this computation demonstrates the optimal solution with fast convergence and short time consumption. These processes also perform smooth and stable characteristics for the searching completion.