Symbiotic Organisms Search for Determining Optimal Generator Capacity

• Published in: International journal on advanced science, engineering and information technology Vol. 14; no. 5; pp. 1720 - 1727
• Main Authors: Hong, Thang Phan Van, Ngoc, Dieu Vo, Tuan, Khanh Dang
• Format: Journal Article
• Language: English
• Published: 09.10.2024
• ISSN: 2088-5334; 2088-5334
• DOI: 10.18517/ijaseit.14.5.16803

This article proposes a method to optimize generation capacity (GC) according to the load diagram for a generator system by adopting the Symbiotic Organisms Search algorithm (SOS). In this paper, the generator system operates as an off-grid including Diesel Generator (DG), Solar Panels (PV), and Wind Turbine (WT). Regarding the applied algorithm, the SOS algorithm is used to solve the optimization problem to minimize electricity generation costs while still ensuring meeting load capacity according to demand within 24 hours with many other scenarios. Calculation results are performed with 3 cases, each corresponding to a specific generator system. They will be compared with DE-HS, DSM, and FO algorithms. The comparison results show the effectiveness of the SOS algorithm compared to the DE-HS, DSM, and FO algorithms. On the other hand, analyzing the obtained results, the convergence speed of the SOS algorithm in finding solutions achieves stability when increasing the number of iterations by ten times. However, the SOS algorithm still has some problems that need to be improved. That is to minimize the time to find the optimal solution because the algorithm has to perform many intermediate solution steps. Generator systems operating in off-grid mode are increasingly popular. In this system, generators have a variety of energy sources, including Diesel generators, solar power, and wind power. Many energy sources are integrated into a system, requiring a method to handle the optimal problem.