IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v188y2019ics0360544219317645.html
   My bibliography  Save this article

Comprehensive method of natural gas pipeline efficiency evaluation based on energy and big data analysis

Author

Listed:
  • Fan, Mu-wei
  • Ao, Chu-chu
  • Wang, Xiao-rong

Abstract

Pipeline companies deploy a series of pipeline resource optimal configurations and efficiency enhancement strategies with the purpose of improving financial benefits. Thus far, pipeline owners and stakeholders have usually focused on efficiency evaluation processes based on the technological aspects of transmission. In this context, here we derive a pipeline efficiency evaluation method from the perspective of the pipeline energy input–output by monitoring the energy and transmission amount changes along the pipeline. The parameter of volumetric work, which is defined as the energy consumption required for transporting a certain amount of gas over a certain distance along the pipeline, measures the energy change except for the intrinsic energy and mechanical pressure energy. With no distribution stations being taken into consideration, the gas amount change due to the pipeline's self-energy consumption is regarded as the equivalent fuel gas while also considering the volumetric work change caused by gas consumption. Upon accounting for all factors via volumetric work and pressure energy, we utilise the input–output variation to develop a data envelopment analysis (DEA) model, which affords the relative efficiency via calculation and evaluation of the operating efficiency of the pipeline and related facilities. Subsequently, analytic hierarchy process (AHP) is introduced to determine the impact from different facilities. Our result, which presents the difference between the ideal objective efficiency and current efficiency based on the measured volumetric work can aid in identifying the most efficient situation. Here, we note that owing to factors such as the inlet pressure and equipment configuration, the first station usually exhibits lower efficiency than the other stations. In terms of energy for the whole pipeline, the efficiency (unit consumption) grows in inverse proportion to the transmission amount. In the final phase of the study, we consider an actual pipeline case study in our analysis and verify the practical utility of this method. Our results also indicate that the transmission efficiency and economic efficiency exhibit a trade-off relationship.

Suggested Citation

  • Fan, Mu-wei & Ao, Chu-chu & Wang, Xiao-rong, 2019. "Comprehensive method of natural gas pipeline efficiency evaluation based on energy and big data analysis," Energy, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317645
    DOI: 10.1016/j.energy.2019.116069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219317645
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Verma, Aman & Nimana, Balwinder & Olateju, Babatunde & Rahman, Md. Mustafizur & Radpour, Saeidreza & Canter, Christina & Subramanyam, Veena & Paramashivan, Deepak & Vaezi, Mahdi & Kumar, Amit, 2017. "A techno-economic assessment of bitumen and synthetic crude oil transport (SCO) in the Canadian oil sands industry: Oil via rail or pipeline?," Energy, Elsevier, vol. 124(C), pages 665-683.
    2. Guo, Xiaolu & Yan, Xingqing & Yu, Jianliang & Yang, Yang & Zhang, Yongchun & Chen, Shaoyun & Mahgerefteh, Haroun & Martynov, Sergey & Collard, Alexander, 2017. "Pressure responses and phase transitions during the release of high pressure CO2 from a large-scale pipeline," Energy, Elsevier, vol. 118(C), pages 1066-1078.
    3. Daşdemir, Ali & Ertürk, Mustafa & Keçebaş, Ali & Demircan, Cihan, 2017. "Effects of air gap on insulation thickness and life cycle costs for different pipe diameters in pipeline," Energy, Elsevier, vol. 122(C), pages 492-504.
    4. Witkowski, Andrzej & Rusin, Andrzej & Majkut, Mirosław & Stolecka, Katarzyna, 2017. "Comprehensive analysis of hydrogen compression and pipeline transportation from thermodynamics and safety aspects," Energy, Elsevier, vol. 141(C), pages 2508-2518.
    5. Zhang, Haoran & Liang, Yongtu & Liao, Qi & Wu, Mengyu & Yan, Xiaohan, 2017. "A hybrid computational approach for detailed scheduling of products in a pipeline with multiple pump stations," Energy, Elsevier, vol. 119(C), pages 612-628.
    6. Kabirian, Alireza & Hemmati, Mohammad Reza, 2007. "A strategic planning model for natural gas transmission networks," Energy Policy, Elsevier, vol. 35(11), pages 5656-5670, November.
    7. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach," Energy, Elsevier, vol. 36(5), pages 2765-2772.
    8. Guo, Chuanyin & Abbasi Shureshjani, Roohollah & Foroughi, Ali Asghar & Zhu, Joe, 2017. "Decomposition weights and overall efficiency in two-stage additive network DEA," European Journal of Operational Research, Elsevier, vol. 257(3), pages 896-906.
    9. Makridou, Georgia & Andriosopoulos, Kostas & Doumpos, Michael & Zopounidis, Constantin, 2016. "Measuring the efficiency of energy-intensive industries across European countries," Energy Policy, Elsevier, vol. 88(C), pages 573-583.
    10. Lin, Boqiang & Wang, Ting, 2012. "Forecasting natural gas supply in China: Production peak and import trends," Energy Policy, Elsevier, vol. 49(C), pages 225-233.
    11. Blanco, Jesús M. & Vazquez, L. & Peña, F., 2012. "Investigation on a new methodology for thermal power plant assessment through live diagnosis monitoring of selected process parameters; application to a case study," Energy, Elsevier, vol. 42(1), pages 170-180.
    12. Yu, Weichao & Song, Shangfei & Li, Yichen & Min, Yuan & Huang, Weihe & Wen, Kai & Gong, Jing, 2018. "Gas supply reliability assessment of natural gas transmission pipeline systems," Energy, Elsevier, vol. 162(C), pages 853-870.
    13. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    14. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Zhaoming & Liu, Zhe & Zhou, Jing & Song, Chaofan & Xiang, Qi & He, Qian & Hu, Jingjing & Faber, Michael H. & Zio, Enrico & Li, Zhenlin & Su, Huai & Zhang, Jinjun, 2023. "A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks," Energy, Elsevier, vol. 278(C).
    2. Zhang, Jinrui & Meerman, Hans & Benders, René & Faaij, André, 2021. "Techno-economic and life cycle greenhouse gas emissions assessment of liquefied natural gas supply chain in China," Energy, Elsevier, vol. 224(C).
    3. Zhou, Dengji & Jia, Xingyun & Ma, Shixi & Shao, Tiemin & Huang, Dawen & Hao, Jiarui & Li, Taotao, 2022. "Dynamic simulation of natural gas pipeline network based on interpretable machine learning model," Energy, Elsevier, vol. 253(C).
    4. Zhu, Zhu & Liao, Qi & Liang, Yongtu & Qiu, Rui & Zhang, ZeZhou & Zhang, Haoran, 2022. "The era of renewables: Infrastructure disposal strategies under market decline of oil products," Energy, Elsevier, vol. 249(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Chang, Ming-Chung, 2016. "Applying the energy productivity index that considers maximized energy reduction on SADC (Southern Africa Development Community) members," Energy, Elsevier, vol. 95(C), pages 313-323.
    3. Weibin Lin & Jin Yang & Bin Chen, 2011. "Temporal and Spatial Analysis of Integrated Energy and Environment Efficiency in China Based on a Green GDP Index," Energies, MDPI, vol. 4(9), pages 1-15, September.
    4. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    5. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    6. Vladimír Baláž & Eduard Nežinský & Tomáš Jeck & Richard Filčák, 2020. "Energy and Emission Efficiency of the Slovak Regions," Sustainability, MDPI, vol. 12(7), pages 1-18, March.
    7. Zheng, Saina & Lam, Chor-Man & Hsu, Shu-Chien & Ren, Jingzheng, 2018. "Evaluating efficiency of energy conservation measures in energy service companies in China," Energy Policy, Elsevier, vol. 122(C), pages 580-591.
    8. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    9. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    10. Barut, Zeliha Bereket & Ertekin, Can & Karaagac, Hasan Ali, 2011. "Tillage effects on energy use for corn silage in Mediterranean Coastal of Turkey," Energy, Elsevier, vol. 36(9), pages 5466-5475.
    11. Shuangjie Li & Li Li & Liming Wang, 2020. "2030 Target for Energy Efficiency and Emission Reduction in the EU Paper Industry," Energies, MDPI, vol. 14(1), pages 1-17, December.
    12. Unakıtan, Gökhan & Aydın, Başak, 2018. "A comparison of energy use efficiency and economic analysis of wheat and sunflower production in Turkey: A case study in Thrace Region," Energy, Elsevier, vol. 149(C), pages 279-285.
    13. Fernández, David & Pozo, Carlos & Folgado, Rubén & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2018. "Productivity and energy efficiency assessment of existing industrial gases facilities via data envelopment analysis and the Malmquist index," Applied Energy, Elsevier, vol. 212(C), pages 1563-1577.
    14. Naseri, Hakim & Parashkoohi, Mohammad Gholami & Ranjbar, Iraj & Zamani, Davood Mohammad, 2021. "Energy-economic and life cycle assessment of sugarcane production in different tillage systems," Energy, Elsevier, vol. 217(C).
    15. Wang, Donglin & Feng, Hao & Li, Yi & Zhang, Tibin & Dyck, Miles & Wu, Feng, 2019. "Energy input-output, water use efficiency and economics of winter wheat under gravel mulching in Northwest China," Agricultural Water Management, Elsevier, vol. 222(C), pages 354-366.
    16. De Clercq, Djavan & Wen, Zongguo & Caicedo, Luis & Cao, Xin & Fan, Fei & Xu, Ruifei, 2017. "Application of DEA and statistical inference to model the determinants of biomethane production efficiency: A case study in south China," Applied Energy, Elsevier, vol. 205(C), pages 1231-1243.
    17. Kumar, Ajeet & Vachan Tirkey, Jeevan & Kumar Shukla, Shailendra, 2021. "“Comparative energy and economic analysis of different vegetable oil plants for biodiesel production in India”," Renewable Energy, Elsevier, vol. 169(C), pages 266-282.
    18. Houshyar, Ehsan & Azadi, Hossein & Almassi, Morteza & Sheikh Davoodi, Mohammad Javad & Witlox, Frank, 2012. "Sustainable and efficient energy consumption of corn production in Southwest Iran: Combination of multi-fuzzy and DEA modeling," Energy, Elsevier, vol. 44(1), pages 672-681.
    19. Sara Ilahi & Yongchang Wu & Muhammad Ahsan Ali Raza & Wenshan Wei & Muhammad Imran & Lyankhua Bayasgalankhuu, 2019. "Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    20. Blancard, Stéphane & Martin, Elsa, 2014. "Energy efficiency measurement in agriculture with imprecise energy content information," Energy Policy, Elsevier, vol. 66(C), pages 198-208.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317645. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.