IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v260y2022ics0360544222020497.html
   My bibliography  Save this article

Environmental and economic assessment of the efficiency of heat exchanger network retrofit options based on the experience of society and energy price records

Author

Listed:
  • Boldyryev, Stanislav
  • Gil, Tatyana
  • Ilchenko, Mariia

Abstract

Retrofit of the heat exchanger network is one of the vehicles of energy efficiency and emission reduction in the process industry. For further implementation, several alternative retrofit options exist, and better economic indicators provide the selection of the best one. Usually, the analysis is made using a forecasting model of energy prices, but the last pandemic and political crises demonstrate unpredictable changes. This paper proposed an approach for the economic and environmental assessment of retrofit options based on the experience of society from 1861 to 2021 and the corresponding energy price trends. Essential financial, e.g. NPV, IRR, DPP, and environmental criteria of retrofit options of heat exchanger network, are analysed considering different trends of energy prices. The most effective project is selected, providing the decision-makers with all data on overdetermined or lost benefits in all possible conditions. The case study analyses three alternative retrofit options for crude oil distillation. Two scenarios presume implementation after 1 and 3 years after project acceptance. The analysis shows IRR is on average 28, 99 and 61% for retrofit options 1, 2 and 3 when a preparatory period is 3 years and low energy prices. NPV is on average 21, 15 and 9 million USD, respectively. The DPPs are 3.8, 2.3, and 2.6 years and the reduction of carbon footprint is by 152, 71 and 45 ktCO2/year. It was also found that the retrofit option with the most extensive energy and emission saving is the most effective for periods with high energy prices regardless of a project implementation period. The retrofit option with the minor network changes is better for low and average energy prices regardless of a project implementation period. The method allows decision-makers to assess the alternative retrofit project in different economic conditions and could be applied in other process industries.

Suggested Citation

  • Boldyryev, Stanislav & Gil, Tatyana & Ilchenko, Mariia, 2022. "Environmental and economic assessment of the efficiency of heat exchanger network retrofit options based on the experience of society and energy price records," Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:energy:v:260:y:2022:i:c:s0360544222020497
    DOI: 10.1016/j.energy.2022.125155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222020497
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125155?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. Bühler, Fabian & Zühlsdorf, Benjamin & Nguyen, Tuong-Van & Elmegaard, Brian, 2019. "A comparative assessment of electrification strategies for industrial sites: Case of milk powder production," Applied Energy, Elsevier, vol. 250(C), pages 1383-1401.
    2. Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
    3. Akpomiemie, Mary O. & Smith, Robin, 2018. "Cost-effective strategy for heat exchanger network retrofit," Energy, Elsevier, vol. 146(C), pages 82-97.
    4. Liu, Linlin & Li, Chenying & Gu, Siwen & Zhang, Lei & Du, Jian, 2020. "Optimization-based framework for the synthesis of heat exchanger networks incorporating controllability," Energy, Elsevier, vol. 208(C).
    5. Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    6. Bakar, Suraya Hanim Abu & Hamid, Mohd. Kamaruddin Abd. & Alwi, Sharifah Rafidah Wan & Manan, Zainuddin Abdul, 2016. "Selection of minimum temperature difference (ΔTmin) for heat exchanger network synthesis based on trade-off plot," Applied Energy, Elsevier, vol. 162(C), pages 1259-1271.
    7. Baldoni, Edoardo & Coderoni, Silvia & D'Orazio, Marco & Di Giuseppe, Elisa & Esposti, Roberto, 2019. "The role of economic and policy variables in energy-efficient retrofitting assessment. A stochastic Life Cycle Costing methodology," Energy Policy, Elsevier, vol. 129(C), pages 1207-1219.
    8. Abbasi, Kashif & Jiao, Zhilun & Khan, Arman & Shahbaz, Muhammad, 2020. "Asymmetric impact of renewable and non-renewable energy on economic growth in Pakistan: New evidence from a nonlinear analysis," MPRA Paper 101854, University Library of Munich, Germany, revised 13 Jul 2020.
    9. Zhang, Zhikun & Liu, Lina & Shen, Boxiong & Wu, Chunfei, 2018. "Preparation, modification and development of Ni-based catalysts for catalytic reforming of tar produced from biomass gasification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1086-1109.
    10. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    11. Wang, Bohong & Klemeš, Jiří Jaromír & Varbanov, Petar Sabev & Chin, Hon Huin & Wang, Qiu-Wang & Zeng, Min, 2020. "Heat exchanger network retrofit by a shifted retrofit thermodynamic grid diagram-based model and a two-stage approach," Energy, Elsevier, vol. 198(C).
    12. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    13. Prasad Sankar Bhattacharya & Dimitrios D. Thomakos, 2018. "Robust model rankings of forecasting performance," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 676-690, September.
    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. Boldyryev, Stanislav & Gil, Tatyana & Krajačić, Goran & Khussanov, Alisher, 2023. "Total site targeting with the simultaneous use of intermediate utilities and power cogeneration at the polymer plant," Energy, Elsevier, vol. 279(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. Ulyev, Leonid & Boldyryev, Stanislav & Kuznetsov, Maxim, 2023. "Investigation of process stream systems for targeting energy-capital trade-offs of a heat recovery network," Energy, Elsevier, vol. 263(PD).
    2. Wang, Bohong & Klemeš, Jiří Jaromír & Li, Nianqi & Zeng, Min & Varbanov, Petar Sabev & Liang, Yongtu, 2021. "Heat exchanger network retrofit with heat exchanger and material type selection: A review and a novel method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    3. Seferlis, Panos & Varbanov, Petar Sabev & Papadopoulos, Athanasios I. & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2021. "Sustainable design, integration, and operation for energy high-performance process systems," Energy, Elsevier, vol. 224(C).
    4. Li, Nianqi & Klemeš, Jiří Jaromír & Sunden, Bengt & Wu, Zan & Wang, Qiuwang & Zeng, Min, 2022. "Heat exchanger network synthesis considering detailed thermal-hydraulic performance: Methods and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    5. Chao Liang & Yaojie Zhang & Xiafei Li & Feng Ma, 2022. "Which predictor is more predictive for Bitcoin volatility? And why?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1947-1961, April.
    6. Zhang, Zhikun & Zhu, Zongyuan & Shen, Boxiong & Liu, Lina, 2019. "Insights into biochar and hydrochar production and applications: A review," Energy, Elsevier, vol. 171(C), pages 581-598.
    7. Edoardo Baldoni & Silvia Coderoni & Elisa Di Giuseppe & Marco D’Orazio & Roberto Esposti & Gianluca Maracchini, 2021. "A Software Tool for a Stochastic Life Cycle Assessment and Costing of Buildings’ Energy Efficiency Measures," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    8. Zhou, Zhongbao & Gao, Meng & Liu, Qing & Xiao, Helu, 2020. "Forecasting stock price movements with multiple data sources: Evidence from stock market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    9. Viziniuc, Mădălin, 2021. "Winners and losers of central bank foreign exchange interventions," Economic Modelling, Elsevier, vol. 94(C), pages 748-767.
    10. Anwar Hasan Abdullah Othman & Salina Kassim & Romzie Bin Rosman & Nur Harena Binti Redzuan, 2020. "Prediction accuracy improvement for Bitcoin market prices based on symmetric volatility information using artificial neural network approach," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(5), pages 314-330, October.
    11. Abdul Rehman & Hengyun Ma & Magdalena Radulescu & Crenguta Ileana Sinisi & Loredana Maria Paunescu & MD Shabbir Alam & Rafael Alvarado, 2021. "The Energy Mix Dilemma and Environmental Sustainability: Interaction among Greenhouse Gas Emissions, Nuclear Energy, Urban Agglomeration, and Economic Growth," Energies, MDPI, vol. 14(22), pages 1-21, November.
    12. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    13. Khanh Hoang & Cuong C. Nguyen & Kongchheng Poch & Thang X. Nguyen, 2020. "Does Bitcoin Hedge Commodity Uncertainty?," JRFM, MDPI, vol. 13(6), pages 1-14, June.
    14. Zhu, Xiaochen & Fuli, Wang, 2023. "Energy savings bottleneck diagnosis and optimization decision method for industrial auxiliary system based on energy efficiency gap analysis," Energy, Elsevier, vol. 263(PE).
    15. Ron-Hendrik Hechelmann & Jan-Peter Seevers & Alexander Otte & Jan Sponer & Matthias Stark, 2020. "Renewable Energy Integration for Steam Supply of Industrial Processes—A Food Processing Case Study," Energies, MDPI, vol. 13(10), pages 1-20, May.
    16. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    17. Karl Oton Rudolf & Samer Ajour El Zein & Nicola Jackman Lansdowne, 2021. "Bitcoin as an Investment and Hedge Alternative. A DCC MGARCH Model Analysis," Risks, MDPI, vol. 9(9), pages 1-22, August.
    18. Paulo Afonso & Vishad Vyas & Ana Antunes & Sérgio Silva & Boris P. J. Bret, 2021. "A Stochastic Approach for Product Costing in Manufacturing Processes," Mathematics, MDPI, vol. 9(18), pages 1-23, September.
    19. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    20. Zdeněk Jegla & Vít Freisleben, 2020. "Practical Energy Retrofit of Heat Exchanger Network Not Containing Utility Path," Energies, MDPI, vol. 13(11), pages 1-16, May.

    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:260:y:2022:i:c:s0360544222020497. 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.