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Design and Analysis of Bioenergy Networks

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  • Ruud Kempener
  • Jessica Beck
  • Jim Petrie

Abstract

This article presents a new methodology for designing industrial networks and analyzing them dynamically from the standpoint of sustainable development. The approach uses a combination of optimization and simulation tools. Assuming “top‐down” overarching control of the network, we use global dynamic optimization to determine which evolutionary pathways are preferred in terms of economic, social, and environmental performance. Considering the autonomy of network entities and their actions, we apply agent‐based simulation to analyze how the network actually evolves. These two perspectives are integrated into a powerful multiscale modeling framework for evaluating the consequences of new policy instruments or different business strategies aimed at stimulating sustainable development as well as identifying optimal leverage points for improved performance of the network in question. The approach is demonstrated for a regional network of interdependent organizations deploying a set of bioenergy technologies within a developing‐economy context.

Suggested Citation

  • Ruud Kempener & Jessica Beck & Jim Petrie, 2009. "Design and Analysis of Bioenergy Networks," Journal of Industrial Ecology, Yale University, vol. 13(2), pages 284-305, April.
    • Handle: RePEc:bla:inecol:v:13:y:2009:i:2:p:284-305
    DOI: 10.1111/j.1530-9290.2009.00120.x
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    Cited by:

    1. Tim Schröder & Lars-Peter Lauven & Beatriz Beyer & Nils Lerche & Jutta Geldermann, 2019. "Using PROMETHEE to assess bioenergy pathways," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(2), pages 287-309, June.
    2. Dale, Virginia H. & Kline, Keith L. & Buford, Marilyn A. & Volk, Timothy A. & Tattersall Smith, C. & Stupak, Inge, 2016. "Incorporating bioenergy into sustainable landscape designs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1158-1171.
    3. Barbosa-Póvoa, Ana Paula & da Silva, Cátia & Carvalho, Ana, 2018. "Opportunities and challenges in sustainable supply chain: An operations research perspective," European Journal of Operational Research, Elsevier, vol. 268(2), pages 399-431.
    4. Knight, Christopher J.K. & Penn, Alexandra S. & Hoyle, Rebecca B., 2014. "Comparing the effects of mutualism and competition on industrial districts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 541-557.
    5. Bekkering, J. & Hengeveld, E.J. & van Gemert, W.J.T. & Broekhuis, A.A., 2015. "Designing a green gas supply to meet regional seasonal demand – An operations research case study," Applied Energy, Elsevier, vol. 143(C), pages 348-358.
    6. Li, Francis G.N. & Trutnevyte, Evelina & Strachan, Neil, 2015. "A review of socio-technical energy transition (STET) models," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 290-305.
    7. Busch, Jonathan & Roelich, Katy & Bale, Catherine S.E. & Knoeri, Christof, 2017. "Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks," Energy Policy, Elsevier, vol. 100(C), pages 170-180.
    8. Lerche, Nils & Wilkens, Ines & Schmehl, Meike & Eigner-Thiel, Swantje & Geldermann, Jutta, 2019. "Using methods of Multi-Criteria Decision Making to provide decision support concerning local bioenergy projects," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).

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