A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty-Reference-Cited by-同舟云学术

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A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty

Published:2022-11-30 Issue: Volume: Page:
ISSN:1868-3967
Container-title:Energy Systems
language:en
Short-container-title:Energy Syst

Author:

Gulcan Berkay,Song Yongjia^ORCID,Eksioglu Sandra D.,Roni Mohammad

Funder

Office of Energy Efficiency and Renewable Energy

Publisher

Springer Science and Business Media LLC

Subject

General Energy,Economics and Econometrics,Modeling and Simulation

Link

https://link.springer.com/content/pdf/10.1007/s12667-022-00544-1.pdf

Reference46 articles.

1. Frank, A.G., Dalenogare, L.S., Ayala, N.F.: Industry 4.0 technologies: Implementation patterns in manufacturing companies. Int. J. Prod. Econ. 210, 15–26 (2019). https://doi.org/10.1016/j.ijpe.2019.01.004

2. Dalenogare, L.S., Benitez, G.B., Ayala, N.F., Frank, A.G.: The expected contribution of industry 4.0 technologies for industrial performance. Int. J. Prod. Econ. 204, 383–394 (2018). https://doi.org/10.1016/j.ijpe.2018.08.019

3. Snetterton Renewable Energy Plant: Behind the project. https://www.snettertonbiomass.com/behind-the-project/. Accessed: 2021-06-25 (2015)

4. Birge, J.R.: Aggregation bounds in stochastic linear programming. Math. Progr. 31(1), 25–41 (1985)

5. Domac, J., Richards, K., Risovic, S.: Socio-economic drivers in implementing bioenergy projects. Biomass Bioenerg. 28(2), 97–106 (2005). https://doi.org/10.1016/j.biombioe.2004.08.002

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