Primary Energy Supply Chain Optimization: Delivery Time Analysis

Primary energy supply arrangements play a crucial role in the planning and scheduling power plants to meet varying electricity demands. The primary energy supply arrangements also include the quantity, specification, and delivery time of the primary energy supply. When the delivery times of primary energy supplies become unpredictable or unreliable, it can negatively impact the planning and scheduling process. This study aims to develop the best primary energy supply arrangement method by optimizing the primary energy supply delivery time to each power plant in the power system. Data processing in this research uses descriptive analysis methods combined with Genetic algorithms (evolutionary), followed by a numerical simulation process to obtain a primary energy supply schedule. The simulation results show that the descriptive analysis combined with the Genetic Algorithm performs better than the existing methods by applying the manual descriptive analysis method to meet the best delivery time and various required constraints. From the simulation results, a deviation of 13% was obtained compared to the actual data for January-April 2023. This optimization method has been simulated at three power plants in the Java-Bali area with a significant supply contribution to the electric power system. To improve accuracy in making predictions about the delivery time of primary energy supplies, it is necessary to do data processing by adding factors such as weather, sea wave height, and other factors.