Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

Abstract

As the main link of ground engineering, crude oil gathering and transportation systems require huge energy consumption and complex structures. It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps. In this paper, the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established. Combined with the big data analysis method, the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems. The comprehensive energy consumption, gas consumption, power consumption, energy utilization rate, heat utilization rate, and power utilization rate of crude oil gathering and transportation systems are predicted. Considering the efficiency and unit consumption index of the crude oil gathering and transportation system, the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method, and the subjective weight is determined by the triangular fuzzy analytic hierarchy process. The entropy weight method determines the objective weight, and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems. Finally, the weak links in energy utilization are identified, and energy conservation and consumption reduction are improved. The above research provides technical support for the green, efficient and intelligent development of crude oil gathering and transportation systems.