IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v112y2016icp599-605.html
   My bibliography  Save this article

Towards an energy information system architecture description for industrial manufacturers: Decomposition & allocation view

Author

Listed:
  • Effenberger, Frank
  • Hilbert, Andreas

Abstract

This paper contributes to the development of a consolidated and standardized energy information system architecture description for industrial manufacturers. Based on the latest scientific achievements and data from industrial manufacturers, cross-industry informational requirements were collected and the results were transformed into functional system requirements and allocated elements for the development of an architecture view based on the ISO/IEC/IEEE 42010:2011 and the ISO/IEC/IEEE 15288:2015. The results were then used to extend an energy framework for industrial manufacturers. The results can be utilized to further develop a consolidated and standardized architecture description for energy information systems and to support architecture rationales in industrial manufacturing in the future.

Suggested Citation

  • Effenberger, Frank & Hilbert, Andreas, 2016. "Towards an energy information system architecture description for industrial manufacturers: Decomposition & allocation view," Energy, Elsevier, vol. 112(C), pages 599-605.
  • Handle: RePEc:eee:energy:v:112:y:2016:i:c:p:599-605
    DOI: 10.1016/j.energy.2016.06.106
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216308805
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.06.106?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. Cagno, E. & Trucco, P. & Trianni, A. & Sala, G., 2010. "Quick-E-scan: A methodology for the energy scan of SMEs," Energy, Elsevier, vol. 35(5), pages 1916-1926.
    2. Zare, Kazem & Moghaddam, Mohsen Parsa & Sheikh El Eslami, Mohammad Kazem, 2010. "Electricity procurement for large consumers based on Information Gap Decision Theory," Energy Policy, Elsevier, vol. 38(1), pages 234-242, January.
    3. Wade D. Cook & Joe Zhu, 2015. "DEA Cross Efficiency," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 2, pages 23-43, Springer.
    4. Behrangrad, Mahdi, 2015. "A review of demand side management business models in the electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 270-283.
    5. Han, Yongming & Geng, Zhiqiang & Zhu, Qunxiong & Qu, Yixin, 2015. "Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry," Energy, Elsevier, vol. 83(C), pages 685-695.
    6. Zare, Kazem & Moghaddam, Mohsen Parsa & Sheikh El Eslami, Mohammad Kazem, 2010. "Demand bidding construction for a large consumer through a hybrid IGDT-probability methodology," Energy, Elsevier, vol. 35(7), pages 2999-3007.
    7. O׳Connell, Niamh & Pinson, Pierre & Madsen, Henrik & O׳Malley, Mark, 2014. "Benefits and challenges of electrical demand response: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 686-699.
    8. Palamutcu, S., 2010. "Electric energy consumption in the cotton textile processing stages," Energy, Elsevier, vol. 35(7), pages 2945-2952.
    9. Oliveira, Fernando S. & Ruiz, Carlos & Conejo, Antonio J., 2013. "Contract design and supply chain coordination in the electricity industry," European Journal of Operational Research, Elsevier, vol. 227(3), pages 527-537.
    10. Granderson, Jessica & Price, Phillip N., 2014. "Development and application of a statistical methodology to evaluate the predictive accuracy of building energy baseline models," Energy, Elsevier, vol. 66(C), pages 981-990.
    11. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    12. Giacone, E. & Mancò, S., 2012. "Energy efficiency measurement in industrial processes," Energy, Elsevier, vol. 38(1), pages 331-345.
    13. Moradi-Dalvand, M. & Mohammadi-Ivatloo, B. & Amjady, N. & Zareipour, H. & Mazhab-Jafari, A., 2015. "Self-scheduling of a wind producer based on Information Gap Decision Theory," Energy, Elsevier, vol. 81(C), pages 588-600.
    14. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
    15. Salta, Myrsine & Polatidis, Heracles & Haralambopoulos, Dias, 2009. "Energy use in the Greek manufacturing sector: A methodological framework based on physical indicators with aggregation and decomposition analysis," Energy, Elsevier, vol. 34(1), pages 90-111.
    16. Florian Stroh & Robert Winter & Felix Wortmann, 2011. "Method Support of Information Requirements Analysis for Analytical Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 3(1), pages 33-43, February.
    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. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    2. Chou, Jui-Sheng & Truong, Ngoc-Son, 2019. "Cloud forecasting system for monitoring and alerting of energy use by home appliances," Applied Energy, Elsevier, vol. 249(C), pages 166-177.

    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. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2016. "Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 421-432.
    2. Majidi, M. & Mohammadi-Ivatloo, B. & Soroudi, A., 2019. "Application of information gap decision theory in practical energy problems: A comprehensive review," Applied Energy, Elsevier, vol. 249(C), pages 157-165.
    3. Jordehi, A. Rezaee, 2018. "How to deal with uncertainties in electric power systems? A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 145-155.
    4. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    5. Geng, ZhiQiang & Dong, JunGen & Han, YongMing & Zhu, QunXiong, 2017. "Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes," Applied Energy, Elsevier, vol. 205(C), pages 465-476.
    6. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    7. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    8. Deng, Yuanwang & Liu, Huawei & Zhao, Xiaohuan & E, Jiaqiang & Chen, Jianmei, 2018. "Effects of cold start control strategy on cold start performance of the diesel engine based on a comprehensive preheat diesel engine model," Applied Energy, Elsevier, vol. 210(C), pages 279-287.
    9. 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.
    10. Ben-Haim, Yakov, 2021. "Feedback for energy conservation: An info-gap approach," Energy, Elsevier, vol. 223(C).
    11. Yue Xu & Zebin Wang & Yung-Ho Chiu & Fangrong Ren, 2020. "Research on energy-saving and emissions reduction efficiency in Chinese thermal power companies," Energy & Environment, , vol. 31(5), pages 903-919, August.
    12. Shermeh, H. Ebrahimzadeh & Najafi, S.E. & Alavidoost, M.H., 2016. "A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies," Energy, Elsevier, vol. 112(C), pages 686-697.
    13. Bian, Yiwen & Hu, Miao & Wang, Yousen & Xu, Hao, 2016. "Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 990-998.
    14. Zhu, Qun-Xiong & Zhang, Chen & He, Yan-Lin & Xu, Yuan, 2018. "Energy modeling and saving potential analysis using a novel extreme learning fuzzy logic network: A case study of ethylene industry," Applied Energy, Elsevier, vol. 213(C), pages 322-333.
    15. Good, Nicholas & Ellis, Keith A. & Mancarella, Pierluigi, 2017. "Review and classification of barriers and enablers of demand response in the smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 57-72.
    16. Geng, Zhiqiang & Li, Yanan & Han, Yongming & Zhu, Qunxiong, 2018. "A novel self-organizing cosine similarity learning network: An application to production prediction of petrochemical systems," Energy, Elsevier, vol. 142(C), pages 400-410.
    17. Kühnlenz, Florian & Nardelli, Pedro H.J. & Karhinen, Santtu & Svento, Rauli, 2018. "Implementing flexible demand: Real-time price vs. market integration," Energy, Elsevier, vol. 149(C), pages 550-565.
    18. Yu Yu & Weiwei Zhu & Qian Zhang, 2019. "DEA cross-efficiency evaluation and ranking method based on interval data," Annals of Operations Research, Springer, vol. 278(1), pages 159-175, July.
    19. 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.
    20. Gong, Shixin & Shao, Cheng & Zhu, Li, 2019. "Multi-level and multi-granularity energy efficiency diagnosis scheme for ethylene production process," Energy, Elsevier, vol. 170(C), pages 1151-1169.

    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:112:y:2016:i:c:p:599-605. 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.