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Research Output

  • 7 Journal article
  • 1 Article in proceedings

A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea

Nam, K., Hwangbo, S. & Yoo, C., 2020, In : Renewable and Sustainable Energy Reviews. 122, 18 p., 109725.

Research output: Contribution to journalJournal articleResearchpeer-review

Development of an integrated network for waste-to-energy and central utility systems considering air pollutant emissions pinch analysis

Hwangbo, S., Sin, G., Rhee, G. & Yoo, C. K., 2020, In : Journal of cleaner production. 252, 17 p., 119746.

Research output: Contribution to journalJournal articleResearchpeer-review

Optimal utility supply network under demand uncertainty for operational risk assessment on a petrochemical industrial park

Vilela, P., Park, S. K. H., Hwangbo, S. & Yoo, C. K., 2020, In : Korean Journal of Chemical Engineering. 37, 7, p. 1116-1129

Research output: Contribution to journalJournal articleResearchpeer-review

Transitioning of localized renewable energy system towards sustainable hydrogen development planning: P-graph approach

Lim, J. Y., How, B. S., Rhee, G., Hwangbo, S. & Yoo, C. K., 2020, In : Applied Energy. 263, 17 p., 114635.

Research output: Contribution to journalJournal articleResearchpeer-review

Design of smart liquid-liquid extraction columns for downstream separations of biopharmaceuticals using deep Q-learning algorithm

Hwangbo, S., Öner, M. & Sin, G., 2019, Proceedings of the 29th European Symposium on Computer Aided Process Engineering. Anton, K., Zondervan, E., Lakerveld, R. & Özkan, L. (eds.). Elsevier, p. 271-276 (Computer Aided Chemical Engineering, Vol. 46).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review