Combined Computational Intelligence Approach for the Power System Optimization Problem

Abstract

A power system optimization is one of the major problems in the operating performances of the existing system. This problem takes place on the various technical cases to get optimal conditions of the system. Moreover, many approaches have been implemented to carry out the solution under operational constraints. This paper presents Thunderstorm Algorithm (TA) and Artificial Salmon Tracking Algorithm (ASTA) for defining the optimal strategy of the power system optimization based on the unit commitment. Both algorithms are tested on the IEEE-62 bus system, whereas, results show that ASTA and TA can be combined together to solve the power system problem. These algorithms have been applied to predict the power consumption and it has good performances while searching for the optimal solution. These results also show that the economic dispatch problem is conducted to the power production while the algorithm is performed in good characteristics.