Risk-Based Decision Support Model for the Optimal Operation of a Smart Energy Distribution Company for Enabling Emerging Resources

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dc.contributor.author Sadati, S. M. B.
dc.contributor.author Moshtagh, J.
dc.contributor.author Shafie-khah, Miadreza
dc.contributor.author Catalao, Joao
dc.date.accessioned 2019-01-02T23:50:12Z
dc.date.available 2019-01-02T23:50:12Z
dc.date.issued 2019-01-08
dc.description.abstract In this paper, a risk-based decision support model is developed for a smart energy distribution company, enabling emerging resources like renewable energy sources, electric vehicles and demand response programs in a holistic approach. Because of the inherent uncertainties of these emerging resources, the conditional value-at-risk (CVaR) method is adopted to restrict the distribution company’s risk. A risk aversion parameter sensitivity analysis is also provided on the optimal operation of the smart energy distribution company. The proposed model is thoroughly tested on a 15-bus distribution grid system, and the numerical results prove the effectiveness of the model in risk management.
dc.format.extent 8 pages
dc.identifier.doi 10.24251/HICSS.2019.147
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59560
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Decision Support for Complex Networks
dc.subject Decision Analytics, Mobile Services, and Service Science
dc.subject Risk; Decision Support; Optimal Operation; Distribution Company; Emerging Resources.
dc.title Risk-Based Decision Support Model for the Optimal Operation of a Smart Energy Distribution Company for Enabling Emerging Resources
dc.type Conference Paper
dc.type.dcmi Text
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