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Synthesis and optimisation of biomass-based tri-generation systems with reliability aspects

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  • Andiappan, Viknesh
  • Tan, Raymond R.
  • Aviso, Kathleen B.
  • Ng, Denny K.S.

Abstract

Tri-generation systems are utility systems which produce heat, power and cooling simultaneously. Use of tri-generation systems in industrial sites reduces the importation of power and improves local power reliability; at the same time, their inherently higher efficiency also reduces environmental impacts. However, interdependencies among process units in tri-generation plants can lead to vulnerability to cascading failures. Process units may become non-functional during the course of operations as a result of planned or unplanned stoppages. This issue is normally handled by installing additional capacity to the process units based on heuristics. However, such heuristics may not be able to address complex decisions pertaining to the installation of multiple units to provide redundancy, and may result in excessive capital and/or maintenance costs. In this work, a systematic approach for the grassroots design of a reliable BTS (biomass-based tri-generation system) considering equipment redundancy is presented. Chance-constrained programming and k-out-of-m system modelling are used to develop a multi-period optimisation model for a generic BTS. Two case studies are then solved to illustrate this modelling approach.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:89:y:2015:i:c:p:803-818
    DOI: 10.1016/j.energy.2015.05.138
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    References listed on IDEAS

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    Cited by:

    1. Yuan, Jiahang & Luo, Xinggang & Li, Yun & Hu, Xiaoqing & Chen, Wenchong & Zhang, Yue, 2022. "Multi criteria decision-making for distributed energy system based on multi-source heterogeneous data," Energy, Elsevier, vol. 239(PD).
    2. Yan, Linbo & Yue, Guangxi & He, Boshu, 2015. "Exergy analysis of a coal/biomass co-hydrogasification based chemical looping power generation system," Energy, Elsevier, vol. 93(P2), pages 1778-1787.
    3. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    4. Cabral, Charlette & Andiappan, Viknesh & Aviso, Kathleen & Tan, Raymond, 2021. "Equipment size selection for optimizing polygeneration systems with reliability aspects," Energy, Elsevier, vol. 234(C).
    5. 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.
    6. Sadhukhan, Jhuma & Martinez-Hernandez, Elias & Murphy, Richard J. & Ng, Denny K.S. & Hassim, Mimi H. & Siew Ng, Kok & Yoke Kin, Wan & Jaye, Ida Fahani Md & Leung Pah Hang, Melissa Y. & Andiappan, Vikn, 2018. "Role of bioenergy, biorefinery and bioeconomy in sustainable development: Strategic pathways for Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1966-1987.
    7. 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.

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