Energy efficiency evaluation of a natural gas pipeline based on an analytic hierarchy process

Abstract

A long-distance natural gas pipeline system consists of considerable equipment and many pipe segments, but the conventional energy efficiency index of a natural gas pipeline is considered as a whole. Because the specific energy consumption of each unit cannot be determined, the index system is not perfect, and evaluating the energy efficiency of a natural gas pipeline system is difficult. The energy efficiency evaluation model for a natural gas pipeline was established using the analytic hierarchy process. A judgment matrix was constructed based on the energy efficiency index system of a longdistance natural gas pipeline, and the weight coefficient was calculated using the characteristic root method. Then, the consistency of the established judgment matrix was verified. The energy efficiency evaluation model successfully quantified the qualitative factors that affect natural gas pipelines. The comprehensive energy efficiency coefficient G of the natural gas pipeline was obtained from the operational data of the natural gas pipeline; then, the equipment or pipe segments with high energy consumption can be identified. The energy efficiency evaluation program of the natural gas pipeline was developed using Visual Basic for Applications, which significantly reduced the evaluation workload. The natural gas pipeline energy efficiency evaluation model is used to evaluate the energy efficiency of a natural gas pipeline, to identify the high energy consumption equipment or pipe segments, and to propose measures to improve the energy efficiency. The results show that the gas pipeline energy efficiency evaluation model and evaluation procedures can identify high energy consumption equipment or pipe sections in complex natural gas pipelines.

An evaluation method for green logistics system design of agricultural products: A case study in Shandong province, China

“…The AHP, which is proposed by Saaty in the early 1970s, is a hierarchical weight decision analysis method. [36][37][38] Based on AHP, we can decompose the elements associated with decisions into goals, criteria, plans, and so on and develop qualitative and quantitative analyses. AHP is applied to calculate index weights for APGL.…”

Calculation of theoretical transmission loss in trunk gas pipeline

“…There are 29 metering branches along the route, including 15 gas stations and one underground gas storage, as shown in Figure 4. 22 The standard uncertainty of various types of flow rates and instruments is shown in Table 1, and the monthly operating dates of gas transmission trunk lines in the first half of 2018 are given in Table 2. Here, USG in and USG out , respectively, represent the gas production volume and gas injection volume of the underground gas storage, from which the relevant data of actual transmission loss can be obtained (Table 3).…”