{"title":"中国环星天然气田管网通用布局优化设计方法","authors":"","doi":"10.1016/j.ngib.2024.09.005","DOIUrl":null,"url":null,"abstract":"<div><div>The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design, which restricts the intelligentization of gas gathering pipeline layout optimization. Currently, there are no generic design studies on the loop-star pipeline network. Therefore, this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables, such as pipe connection relationships, pipe sizes, pipe length, and pipe specifications. In the solution section, drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics, an improved particle swarm optimization algorithm based on hormone regulation (HRPSO) is proposed, and it obtains the favorable parameters range of the HRPSO algorithm. The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1. In comparison to manual design, the comprehensive costs of the optimized scheme are saved by 22.71% with the HRPSO algorithm. Compared to the four PSO variants in the paper, it can save costs by 5.38%, 4.95%, 4.09%, and 3.65%, respectively.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generic layout optimization design methodology for China's loop-star natural gas field pipeline network\",\"authors\":\"\",\"doi\":\"10.1016/j.ngib.2024.09.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design, which restricts the intelligentization of gas gathering pipeline layout optimization. Currently, there are no generic design studies on the loop-star pipeline network. Therefore, this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables, such as pipe connection relationships, pipe sizes, pipe length, and pipe specifications. In the solution section, drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics, an improved particle swarm optimization algorithm based on hormone regulation (HRPSO) is proposed, and it obtains the favorable parameters range of the HRPSO algorithm. The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1. In comparison to manual design, the comprehensive costs of the optimized scheme are saved by 22.71% with the HRPSO algorithm. Compared to the four PSO variants in the paper, it can save costs by 5.38%, 4.95%, 4.09%, and 3.65%, respectively.</div></div>\",\"PeriodicalId\":37116,\"journal\":{\"name\":\"Natural Gas Industry B\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Natural Gas Industry B\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352854024000706\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Natural Gas Industry B","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352854024000706","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Generic layout optimization design methodology for China's loop-star natural gas field pipeline network
The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design, which restricts the intelligentization of gas gathering pipeline layout optimization. Currently, there are no generic design studies on the loop-star pipeline network. Therefore, this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables, such as pipe connection relationships, pipe sizes, pipe length, and pipe specifications. In the solution section, drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics, an improved particle swarm optimization algorithm based on hormone regulation (HRPSO) is proposed, and it obtains the favorable parameters range of the HRPSO algorithm. The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1. In comparison to manual design, the comprehensive costs of the optimized scheme are saved by 22.71% with the HRPSO algorithm. Compared to the four PSO variants in the paper, it can save costs by 5.38%, 4.95%, 4.09%, and 3.65%, respectively.