Study on the optimal operation scheme of a heated oil pipeline system under complex industrial conditions

Considering mixed discrete-continuous decision variables and complex constraint conditions of a heated oil pipeline system under industrial conditions, a general operation optimization model with the optimal goal of minimum energy cost is established. Besides, an intelligent optimization method combining the hybrid binary -real-coded genetic algorithm (BRCGA) and the penalty method coupled with the simulation of a heated oil pipeline system is proposed to solve the optimization model. The optimization model and solution method are applied to the operation optimization of a complex actual heated oil pipeline system, and an optimal operation scheme is intelligently determined, in which the energy cost is reduced from 24,367 RMB.h(-1) to 19,818 RMB.h(-1) with a remarkable saving proportion of 18.7%. Furthermore, considering the dramatic changes in fuel prices under complex international circumstances, the influence of fuel prices on the optimal operation scheme of a heated oil pipeline system is investigated. It is found that the optimal operation scheme varies with fuel prices. The total energy cost increases with the rise of fuel prices, in which both fuel cost and electricity cost increase, whereas the consumed amount of fuel decreases.

Automated summary

In this study, a general operation optimization model with the optimal goal of minimum energy cost is established for a heated oil pipeline system considering mixed discrete-continuous decision variables and complex constraint conditions. An intelligent optimization method combining the hybrid binary-real-coded genetic algorithm (BRCGA) and the penalty method coupled with the simulation of a heated oil pipeline system is proposed to solve the optimization model. The optimization model and solution method are applied to the operation optimization of a complex actual heated oil pipeline system, and an optimal operation scheme is intelligently determined, resulting in a significant saving of 18.7% in energy cost.