Multi-objective optimization of energy consumption in crude oil pipeline transportation system operation based on exergy loss analysis

2019 ◽  
Vol 332 ◽  
pp. 100-110 ◽  
Author(s):  
Yang Liu ◽  
Qinglin Cheng ◽  
Yifan Gan ◽  
Yuxin Wang ◽  
Zhidong Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Crude Oil ◽  
Transportation System ◽  
Exergy Loss ◽  
Multi Objective Optimization ◽  
Pipeline Transportation ◽  
System Operation ◽  
Oil Pipeline ◽  
Multi Objective ◽  
Loss Analysis

Deduction and Analysis of Driving Exergy Loss in Oil Pipeline System

2013 ◽  
Vol 291-294 ◽  
pp. 688-692 ◽  
Author(s):  
Qing Lin Cheng ◽  
Meng Zhang ◽  
Xuxu Wang
Keyword(s):  
Energy Consumption ◽  
Fluid Mechanics ◽  
Analytic Formula ◽  
Exergy Loss ◽  
Pipeline System ◽  
Pipeline Transportation ◽  
Element Analysis ◽  
Oil Pipeline ◽  
Insulation Thickness ◽  
Operation Parameters

Pipeline transportation is a substance conveying process that makes crude oil flowing from first station to ultimate station and at the same time takes a certain amount of driving energy for cost. Based on related theories of engineering fluid mechanics, mathematics analytic formula of driving exergy in oil pipeline transportation is deduced by micro-element analysis. We can get the conclusion that driving exergy loss has a positive correlation with diameter and throughput, and also a contrary trend with insulation thickness and outbound temperature by analyzing the influence on driving exergy loss from operation parameters in pipeline process,. This research can provide theoretical guidance for energy consumption classification, and further more, the technical support for energy consumption in pipeline system.

Establishment of Exergy Consumption Evaluation System and Analysis of Energy Efficiency for Crude Oil Pipeline Transportation System

2019 ◽  
Author(s):  
Cheng Qinglin ◽  
Ma Yanxin ◽  
Yang Jinwei ◽  
Pan Chenlin ◽  
Gan Yifan ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Crude Oil ◽  
Evaluation System ◽  
Transportation System ◽  
Evaluation Index System ◽  
Pipeline Transportation ◽  
Analytic Hierarchy ◽  
Index Set ◽  
Oil Pipeline ◽  
Exergy Consumption

Abstract In order to establish a comprehensive exergy consumption evaluation system for crude oil pipeline transportation system, this paper proposed the definition and calculation method of unavoidable exergy loss based on the exergy analysis method and basic process of pipeline transportation. Then combined with the exergy flow classification, the exergy consumption index set was established and selected with correlation coefficient method. Furthermore, the exergy consumption evaluation index system was established including four hierarchies of object, intensity, efficiency and target using analytic hierarchy process and the weight of each part was calculated. Finally by means of all the exergy consumption indexes, the status of using energy was analyzed and evaluated. The analysis results showed that optimizing the transportation amount and temperature, energy efficiency could be improved. The evaluation system of exergy consumption established in this paper could improve operation efficiency and reduce energy consumption.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

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