IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v134y2017icp1038-1052.html
   My bibliography  Save this article

Design Operability and Retrofit Analysis (DORA) framework for energy systems

Author

Listed:
  • Andiappan, Viknesh
  • Ng, Denny K.S.
  • Tan, Raymond R.

Abstract

A systematic framework for Design Operability and Retrofit Analysis (DORA) is presented. DORA is a framework explicitly analyzing energy system design containing process units functioning at different levels of operability. To express the operability of individual process units, DORA uses inoperability input-output modeling (IIM) approach. Based on IIM, a simple mixed integer linear programming (MILP) model is developed to analyze the impact of individual process unit inoperability on the flexibility of an energy system design. In the case where a design is deemed to possess insufficient flexibility to meet demands, DORA framework subsequently entails a step-by-step guide to debottleneck and retrofit a given design based on benefit-cost ratio (BCR). In this work, the DORA framework is demonstrated using a biomass-based tri-generation system (BTS) case study. As shown in the case study, DORA framework is used to determine whether a BTS facing a drop in individual unit efficiency, would require debottlenecking and retrofitting to increase its energy production.

Suggested Citation

  • Andiappan, Viknesh & Ng, Denny K.S. & Tan, Raymond R., 2017. "Design Operability and Retrofit Analysis (DORA) framework for energy systems," Energy, Elsevier, vol. 134(C), pages 1038-1052.
    • Handle: RePEc:eee:energy:v:134:y:2017:i:c:p:1038-1052
    DOI: 10.1016/j.energy.2017.06.054
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217310484
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.06.054?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. Andiappan, Viknesh & Tan, Raymond R. & Aviso, Kathleen B. & Ng, Denny K.S., 2015. "Synthesis and optimisation of biomass-based tri-generation systems with reliability aspects," Energy, Elsevier, vol. 89(C), pages 803-818.
    2. Kasivisvanathan, Harresh & Barilea, Ivan Dale U. & Ng, Denny K.S. & Tan, Raymond R., 2013. "Optimal operational adjustment in multi-functional energy systems in response to process inoperability," Applied Energy, Elsevier, vol. 102(C), pages 492-500.
    3. Worrell, Ernst & Biermans, Gijs, 2005. "Move over! Stock turnover, retrofit and industrial energy efficiency," Energy Policy, Elsevier, vol. 33(7), pages 949-962, May.
    4. Voll, Philip & Jennings, Mark & Hennen, Maike & Shah, Nilay & Bardow, André, 2015. "The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis," Energy, Elsevier, vol. 82(C), pages 446-456.
    5. Voll, Philip & Klaffke, Carsten & Hennen, Maike & Bardow, André, 2013. "Automated superstructure-based synthesis and optimization of distributed energy supply systems," Energy, Elsevier, vol. 50(C), pages 374-388.
    6. Herder, Paulien M. & Weijnen, Margot P. C., 2000. "A concurrent engineering approach to chemical process design," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 311-318, March.
    7. Panjeshahi, Mohammad Hassan & Tahouni, Nassim, 2008. "Pressure drop optimisation in debottlenecking of heat exchanger networks," Energy, Elsevier, vol. 33(6), pages 942-951.
    8. Lai, Sau Man & Hui, Chi Wai, 2009. "Feasibility and flexibility for a trigeneration system," Energy, Elsevier, vol. 34(10), pages 1693-1704.
    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. Süle, Zoltán & Baumgartner, János & Dörgő, Gyula & Abonyi, János, 2019. "P-graph-based multi-objective risk analysis and redundancy allocation in safety-critical energy systems," Energy, Elsevier, vol. 179(C), pages 989-1003.
    2. Henrik Engelbrecht Foldager & Rasmus Camillus Jeppesen & Muhyiddine Jradi, 2019. "DanRETRO: A Decision-Making Tool for Energy Retrofit Design and Assessment of Danish Buildings," Sustainability, MDPI, vol. 11(14), pages 1-19, July.
    3. Ling, Wen Choong & Verasingham, Arati Banu & Andiappan, Viknesh & Wan, Yoke Kin & Chew, Irene M.L. & Ng, Denny K.S., 2019. "An integrated mathematical optimisation approach to synthesise and analyse a bioelectricity supply chain network," Energy, Elsevier, vol. 178(C), pages 554-571.
    4. Sinha, Rakesh Kumar & Chaturvedi, Nitin Dutt, 2019. "A review on carbon emission reduction in industries and planning emission limits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    5. Andiappan, Viknesh, 2022. "Optimization of smart energy systems based on response time and energy storage losses," Energy, Elsevier, vol. 258(C).
    6. Cabral, Charlette & Andiappan, Viknesh & Aviso, Kathleen & Tan, Raymond, 2021. "Equipment size selection for optimizing polygeneration systems with reliability aspects," Energy, Elsevier, vol. 234(C).
    7. Shankar Ganesh Pariasamy & Vinod Kumar Venkiteswaran & Jeyanandan Kumar & Mohamed M. Awad, 2022. "Industrial CHP with Steam Systems: A Review of Recent Case Studies, Trends and Relevance to Malaysian Industry," Energies, MDPI, vol. 15(20), pages 1-15, October.
    8. Teng, Sin Yong & Leong, Wei Dong & How, Bing Shen & Lam, Hon Loong & Máša, Vítězslav & Stehlík, Petr, 2021. "Debottlenecking cogeneration systems under process variations: Multi-dimensional bottleneck tree analysis with neural network ensemble," Energy, Elsevier, vol. 215(PB).

    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. Aviso, Kathleen B. & Tan, Raymond R., 2018. "Fuzzy P-graph for optimal synthesis of cogeneration and trigeneration systems," Energy, Elsevier, vol. 154(C), pages 258-268.
    2. Aviso, Kathleen B. & Marfori, Isidro Antonio V. & Tan, Raymond R. & Ubando, Aristotle T., 2020. "Optimizing abnormal operations of off-grid community utility systems with fuzzy P-graph," Energy, Elsevier, vol. 202(C).
    3. Sun, Li & Doyle, Stephen & Smith, Robin, 2016. "Understanding steam costs for energy conservation projects," Applied Energy, Elsevier, vol. 161(C), pages 647-655.
    4. Bahl, Björn & Kümpel, Alexander & Seele, Hagen & Lampe, Matthias & Bardow, André, 2017. "Time-series aggregation for synthesis problems by bounding error in the objective function," Energy, Elsevier, vol. 135(C), pages 900-912.
    5. Yokoyama, Ryohei & Shinano, Yuji & Taniguchi, Syusuke & Wakui, Tetsuya, 2019. "Search for K-best solutions in optimal design of energy supply systems by an extended MILP hierarchical branch and bound method," Energy, Elsevier, vol. 184(C), pages 45-57.
    6. Cabral, Charlette & Andiappan, Viknesh & Aviso, Kathleen & Tan, Raymond, 2021. "Equipment size selection for optimizing polygeneration systems with reliability aspects," Energy, Elsevier, vol. 234(C).
    7. Aristotle T. Ubando & Isidro Antonio V. Marfori & Kathleen B. Aviso & Raymond R. Tan, 2019. "Optimal Operational Adjustment of a Community-Based Off-Grid Polygeneration Plant using a Fuzzy Mixed Integer Linear Programming Model," Energies, MDPI, vol. 12(4), pages 1-17, February.
    8. Sy, Charlle L. & Aviso, Kathleen B. & Ubando, Aristotle T. & Tan, Raymond R., 2016. "Target-oriented robust optimization of polygeneration systems under uncertainty," Energy, Elsevier, vol. 116(P2), pages 1334-1347.
    9. Sun, Li & Gai, Limei & Smith, Robin, 2017. "Site utility system optimization with operation adjustment under uncertainty," Applied Energy, Elsevier, vol. 186(P3), pages 450-456.
    10. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    11. Bahl, Björn & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "Optimization-based identification and quantification of demand-side management potential for distributed energy supply systems," Energy, Elsevier, vol. 135(C), pages 889-899.
    12. Mah, Angel Xin Yee & Ho, Wai Shin & Hassim, Mimi H. & Hashim, Haslenda & Ling, Gabriel Hoh Teck & Ho, Chin Siong & Muis, Zarina Ab, 2021. "Optimization of photovoltaic-based microgrid with hybrid energy storage: A P-graph approach," Energy, Elsevier, vol. 233(C).
    13. Jing, Rui & Kuriyan, Kamal & Kong, Qingyuan & Zhang, Zhihui & Shah, Nilay & Li, Ning & Zhao, Yingru, 2019. "Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    14. Hinker, Jonas & Hemkendreis, Christian & Drewing, Emily & März, Steven & Hidalgo Rodríguez, Diego I. & Myrzik, Johanna M.A., 2017. "A novel conceptual model facilitating the derivation of agent-based models for analyzing socio-technical optimality gaps in the energy domain," Energy, Elsevier, vol. 137(C), pages 1219-1230.
    15. Lennox, James A. & Witajewski-Baltvilks, Jan, 2017. "Directed technical change with capital-embodied technologies: Implications for climate policy," Energy Economics, Elsevier, vol. 67(C), pages 400-409.
    16. Fábio de Oliveira Neves & Henrique Ewbank & José Arnaldo Frutuoso Roveda & Andrea Trianni & Fernando Pinhabel Marafão & Sandra Regina Monteiro Masalskiene Roveda, 2022. "Economic and Production-Related Implications for Industrial Energy Efficiency: A Logistic Regression Analysis on Cross-Cutting Technologies," Energies, MDPI, vol. 15(4), pages 1-19, February.
    17. Lawrence, Akvile & Karlsson, Magnus & Nehler, Therese & Thollander, Patrik, 2019. "Effects of monetary investment, payback time and firm characteristics on electricity saving in energy-intensive industry," Applied Energy, Elsevier, vol. 240(C), pages 499-512.
    18. Yokoyama, Ryohei & Tokunaga, Akira & Wakui, Tetsuya, 2018. "Robust optimal design of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 153(C), pages 159-169.
    19. Monjurul Hasan, A S M & Trianni, Andrea & Shukla, Nagesh & Katic, Mile, 2022. "A novel characterization based framework to incorporate industrial energy management services," Applied Energy, Elsevier, vol. 313(C).
    20. Halmschlager, Daniel & Beck, Anton & Knöttner, Sophie & Koller, Martin & Hofmann, René, 2022. "Combined optimization for retrofitting of heat recovery and thermal energy supply in industrial systems," Applied Energy, Elsevier, vol. 305(C).

    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:134:y:2017:i:c:p:1038-1052. 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.