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An optimization model for economic feasibility analysis and design of decentralized waste-to-energy systems

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  • Xiong, Jie
  • Ng, Tsan Sheng Adam
  • Wang, Shuming

Abstract

This paper considers a methodology for economic feasibility analysis of a decentralized hybrid WTE (waste-to-energy) system, when input waste streams and technical parameters can be uncertain. A hybrid WTE system is decentralized when there are possibly different owners of the waste treatment units. A two-stage stochastic programming model is proposed to evaluate and optimize the joint probability that each installed unit is able to achieve its own financial target, while adhering to stipulated environmental requirements. A case study is performed based on the city state of Singapore. The results show that, the proposed model can help provide the effective decision support for policy-makers in evaluating the appropriate technological mix of WTE alternatives. Furthermore, the designs generated by the proposed model can significantly improve the economic feasibility of the overall system without sacrificing certain installed unit's financial position. Finally, the optimized hybrid WTE system obtained by the proposed model achieves an optimal mix and balance of implemented treatment technologies, which is more practical than the current incineration only design in the MSW (municipal solid waste) management future in Singapore.

Suggested Citation

  • Xiong, Jie & Ng, Tsan Sheng Adam & Wang, Shuming, 2016. "An optimization model for economic feasibility analysis and design of decentralized waste-to-energy systems," Energy, Elsevier, vol. 101(C), pages 239-251.
    • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:239-251
    DOI: 10.1016/j.energy.2016.01.080
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    Cited by:

    1. Liu, J. & Goel, A. & Kua, H.W. & Wang, C.H. & Peng, Y.H., 2021. "Evaluating the urban metabolism sustainability of municipal solid waste management system: An extended exergy accounting and indexing perspective," Applied Energy, Elsevier, vol. 300(C).
    2. Jie Xiong & Shuming Wang & Tsan Sheng Ng, 2021. "Robust Bilevel Resource Recovery Planning," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 2962-2992, September.
    3. Liu, Jianrui & Kua, Harn Wei & Wang, Chi-Hwa & Tong, Yen Wah & Zhang, Jingxin & Peng, Yinghong, 2023. "Extended exergy accounting theory to design waste-to-energy management system under uncertainty," Energy, Elsevier, vol. 278(PB).
    4. Kung, Chih-Chun & McCarl, Bruce A., 2020. "The potential role of renewable electricity generation in Taiwan," Energy Policy, Elsevier, vol. 138(C).
    5. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    6. Rafiq Muhammad Aftab & Liguo Zhang & Chih-Chun Kung, 2021. "Renewable Power Potential from Municipal Solid Waste: A Case Study in Jiangxi, China," SAGE Open, , vol. 11(4), pages 21582440211, November.
    7. He, Zhou & Xiong, Jie & Ng, Tsan Sheng & Fan, Bo & Shoemaker, Christine A., 2017. "Managing competitive municipal solid waste treatment systems: An agent-based approach," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1063-1077.
    8. Anna E. Tovkach & John C. Boyle & Enoch A. Nagelli & Corey M. James & Pamela L. Sheehan & Andrew R. Pfluger, 2023. "Structured decision making for assessment of solid waste-to-energy systems for decentralized onsite applications," Environment Systems and Decisions, Springer, vol. 43(1), pages 54-71, March.
    9. Kuznetsova, Elizaveta & Cardin, Michel-Alexandre & Diao, Mingzhen & Zhang, Sizhe, 2019. "Integrated decision-support methodology for combined centralized-decentralized waste-to-energy management systems design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 477-500.

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