EXPERIMENTAL DATA-DRIVEN OPTIMIZATION FOR ALRAR-HASSI R’MEL LPG TRANSMISSION NETWORK

Abstract

Energy plays a pivotal role in the development and functioning of the global economy. The Algerian National Hydrocarbons Transport and Marketing Company (SONATRACH) is a major supplier of crude oil, natural gas, condensates, and liquefied petroleum gas (LPG). As the demand for these energy sources continues to rise, the need for an efficient logistics strategy to complement the primary transport of petroleum products becomes critical, optimizing the balance between production, transportation, and cost management.

This study examines an experimental data-driven approach to optimize the operation of the 989-km pipeline system using the generalized reduced gradient (GRG) method, with particular attention to the network connecting Alrar to Hassi-R'mel (Algeria). The objective is to identify the optimal operational scheme for the LPG transportation network. A numerical approach based on GRG equations was implemented, and the results were compared with other experimental methods. This work aims to achieve a balance between two conflicting objectives: maximizing the flow rate at specific nodes and minimizing both energy consumption and transportation costs at pumping stations. The decision variables include both continuous and discrete factors, such as node flow rates, the number of pumps in operation, and their rotational speeds.

The optimization process incorporates real operational data to validate and refine the model. It focuses on optimizing a 989-km LPG transmission network with a tree-topology, which includes three pumping stations (SP0, SP1, SP02), three LPG injection nodes (LR1, DLR1, ELR1) and sixteen LPG injection fields. The optimization outcomes were verified by comparing them to the actual operational setup, resulting in a 49.85% reduction in energy consumption and a significant decrease in transportation costs within a single day.