| Abstrakt: |
Today, environmental requirements are pressing the engineering process to maintain and control global warming. It is additionally expecting to decrease poison emanations. Subsequently, the framework operation must be outlined based on an economical environmentally-friendly approach taking into consideration the natural impacts and potential. This also has an impact on the operation of the power system, where this operation will also affect and be influenced by environmental conditions. Operationally, this system process is supported by the energy supplier to operate continuously in providing energy services for loads while electricity production must also achieve clean and green energy at a rational price. The optimal power composition between all potential power plants become one of the most problems considered renewable energies where the energy portion should be determined in available combination economically. Furthermore, the combination of power plants are very important to define an optimal energy service based as on the whole time operations. On the other hand, the optimal energy mixing must be obtained based on the optimization technique for finding the solution lead to many computational approach. This work covers in a latest evolutionary algorithm that has an opportunity to apply on technical problems, Artificial Salmon Tracking Algorithm, to estimate the best energy fraction, this research also aims to find a balanced mixture of the composition of the integrated energy mix. The generation system, which is ideally worked in 24 hours, is subjected to technological constraints and environmental criteria in this study. In terms of contamination, the part of outflows is measured within the Over Rate Emission Coefficient. The results showed that the total power is generated dynamically in 9,990.21 MW to supply energy where the power production is also balanced in various portions of the combination every hour. Besides, the system is penetrated at 1,450.00 MW from solar energy sources and 2,522.93 MW from wind energy sources. [ABSTRACT FROM AUTHOR] |
